A Protocol Framework for Adaptive Real-Time Communication ...miun.diva-portal.org/smash/get/diva2:722303/FULLTEXT02.pdf · for Adaptive Real-Time Communication in Industrial Wireless

Thesis for the degree of Doctor of Technology

Sundsvall 2014

A Protocol Frameworkfor Adaptive Real-Time

Communication in IndustrialWireless Sensor andActuator Networks

Wei Shen

Supervisors: Professor Tingting Zhang

Professor Mikael Gidlund

Department of Information and Communication Systems

Mid Sweden University, SE-851 70 Sundsvall, Sweden

ISSN 1652-893X

Mid Sweden University Doctoral Thesis 178

ISBN 978-91-87557-31-6

Akademisk avhandling som med tillstand av Mittuniversitetet i Sundsvallframlaggs till offentlig granskning for avlaggande av teknologie doktorsexamen,tisdagen den 06 mars 2014, klockan 13:15 i sal L111, Mittuniversitetet Sundsvall.Seminariet kommer att hallas pa engelska.

A Protocol Framework for Adaptive

Real-Time Communication in Industrial

Wireless Sensor and Actuator Networks

Wei Shen

c©Wei Shen, 2014

Department of Information and Communication SystemsMid Sweden University, SE-851 70 Sundsvall,Sweden

Telephone: +46 (0)70 8569165

Printed by Kopieringen Mittuniversitetet, Sundsvall, Sweden, 2014

To My Wife

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Abstract

Low-power and resource-constrained wireless technology has been regarded asan emerging technology that introduces a paradigm shift in a wide range of appli-cations such as industrial automation, smart grid, home automation and so on. Theautomation industry has significant contributions to economic revenues, job oppor-tunities and world-class research. The low-power and resource-constrained wirelesstechnology has brought new opportunity and challenges for industrial automation.The solutions of such wireless technology offer benefits in relation to lower cost andmore flexible deployments/maintenances than the wired solutions, and new appli-cations that are not possible with wired communication. However, these wirelesssolutions have been introducing new challenges. Wireless links are inherently un-reliable, especially in industrial harsh environment, and wireless interference makesthe problem even worse. Low-power consumption is required and real-time com-munication is generally crucial in industrial automation applications.

This research work addresses that industrial wireless sensor and actuator net-work (IWSAN) should even be designed to provide service differentiation for wire-less medium access and adapt to link dynamics for scheduling algorithms on topof real-time services. Specifically, exceeding the required delay bound for unpre-dictable and emergency traffic in industrial automation applications could lead tosystem instability, economic and material losses, system failure and, ultimately, athreat to human safety. Therefore, guaranteeing the timely delivery of the IWSANcritical traffic and its prioritization over regular traffic (e.g. non-critical monitoringtraffic) is a significant topic. In addition, the state-of-the-art researches address amultitude of objectives for scheduling algorithms in IWSAN. However, the adapta-tion to the dynamics of a realistic wireless sensor network has not been investigatedin a satisfactory manner. This is a key issue considering the challenges within indus-trial applications, given the time-constraints and harsh environments.

In response to those challenges, a protocol framework for adaptive real-time com-munication in IWSAN is proposed. It mainly consists of a priority-based mediumaccess protocol (MAC) and its extension for routing critical traffic, a hybrid schemefor acyclic traffic, and adaptive scheduling algorithms. To the best of our knowledge,the priority-based MAC solution is the first priority-enhanced MAC protocol com-patible with industrial standards for IWSAN. The proposed solutions have been im-plemented in TinyOS and evaluated on a test-bed of Telosb motes and the TOSSIMnetwork simulator. The experimental results indicate that the proposed priority-

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based solutions are able to efficiently handle different traffic categories and achieve asignificant improvement in the delivery latency. The hybrid scheme for acyclic trafficincreases the throughput and reduces the delay compared to the current industrialstandards. Numerical results show that the adaptive scheduling algorithms improvethe quality of service for the entire network. They achieve significant improvementsfor realistic dynamic wireless sensor networks when compared to existing schedul-ing algorithms with the aim to minimize latency for real-time communication.

Sammanfattning

Tradlosa teknologier med mycket lag effektforbrukning och liten minneskapacitethar blivit populara sista decenniet och manga nya applikationer inom olika domanersom industriell automation, smarta elnat, och hemautomation har mojliggjorts. Au-tomationsindustrin har lange bidragit till ekonomisk tillvaxt, nya arbetstillfallen samtintressanta och nya spannande forskningsproblem har introducerats. Inom indus-triell automation sa erbjuder tradlos kommunikation en del fordelar jamfort medtradbunden kommunikation genom storre flexibilitet, lagre installationskostnadersamt mojligheter till nya applikationer som tidigare inte var mojligt med tradbundenkommunikation. Tradlos kommunikation innebar aven en utmaning eftersom ra-diomiljon inte ar tillforlitlig i samma utstrackning som i tradbunden kommunika-tion, speciellt i industriella miljoer dar det kan vara mycket smuts, fukt, och interfer-ens fran andra tradlosa sensorer och system.

Detta forskningsarbete fokuserar pa industriella tradlosa sensornatverk och hurman pa basta satt ska designa tradlosa sensornatverk for bra tradlos access i kraftigtvarierande radiomiljo samt algoritmer for effektiv schemalaggning av real-tids app-likationer. Inom industriell automation ar det viktigt att realtidskraven pa datakom-munikation halls for att inte skapa problem i produktionsprocessen som kan leda tillinstabilitet i systemen, oplanerade produktionsstopp som skapar ekonomisk forlustoch i absolut varsta fall skador pa manniskor. Darfor ar det av yttersta vikt attman kan garantera att datatrafiken over de tradlosa sensornatverken haller de tid-skonstanter som ar givna och att viktig datatrafik prioriteras fore data for mindrekritiska applikationer som t.ex monitorering. Vidare i detta forskningsarbete saundersoks schemalaggningsalgoritmer for industriella tradlosa sensornatverk somhanterar varierande radiomiljoer.

I denna avhandling presenteras ett ramverk for protokoll passande till indus-triella tradlosa sensornatverk. Fokus ligger pa adaptiv schemalaggning och prior-itetsbaserad accessprotokoll. De foreslagna losningarna har implementerats i TinyOSoch sedan utvarderats i en testbadd bestaende av TelosB sensornoder och i TOSSIMnatverkssimulator. Numeriska resultat visar att adaptiv schemalaggning forbattrarkvaliteten i hela natverket jamfort med existerande algoritmer for schemalaggning.Speciellt visar resultaten pa att man kan minska fordrojningen i de tradlosa sen-sornatverken med adaptiv schemalaggning. Vidare sa visar experimentella resultatatt det foreslagna prioritetsbaserade accessprotokollet pa ett effektivt satt hanterardatatrafik med olika prioritet pa ett foredomligt satt.

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Acknowledgements

First of all, I would like to thank my supervisor Prof. Tingting Zhang for her greatsupervisions during my PhD study. She has guided me past many obstacles in the-oretical work. Thanks to Tingting for all the guidance, suggestions and ideas on myresearch work during these years, and for always believing me and supporting me.Without her patience and encouragement, this thesis would not have been possible.

Thanks to my co-supervisor Prof. Mikael Gidlund for all his help and guidancein my research work. He has always given me supports and encouragements whatI need. I have been taught by him that thinking the academic issues from the indus-trial application point of views.

Thanks to Prof. Youzhi Xu for introducing me to this opportunity to start myPh.D. study at Mid Sweden University. Thanks to Filip Barac and Felix Dobslaw forthe excellent cooperations and friendliness during my research work.

Thanks to Prof. Marten Sjostrom for his suggestions to improve the thesis writ-ing. I would also like to thank Victor Kardeby, Stefan Forsstrom, Patrik Osterberg,Ulf Jennehag, Stefan Petterson, Annika Berggren and all other colleagues at the De-partment of Information and Communication Systems, Mid Sweden University fortheir kindness and friendliness.

Last but not least, thanks to my families for their endless love and support. Spe-cial thanks to my dear wife, Jinlan Gao, for standing behind me in all that I do.

This research work is financially supported by KKS COINS project (20100258),Sensible Things That Communicate (STC) and Mid Sweden University.

Sundsvall, February 2014

Wei Shen

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Contents

Abstract v

Sammanfattning vii

Acknowledgements ix

List of Papers xiii

Terminology xix

1 Introduction 1

1.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

1.2 Problem Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.3 Objective and Research Topics . . . . . . . . . . . . . . . . . . . . . . . . 4

1.4 Research Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

1.5 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

1.6 Thesis Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

2 Background and Related Work 9

2.1 Low-Power and Resource-Constrained Wireless Technology . . . . . . 9

2.2 Industrial Wireless Sensor and Actuator Networks . . . . . . . . . . . . 11

2.3 Standardization Evolution of IWSAN . . . . . . . . . . . . . . . . . . . 14

2.4 MAC Protocols for WSN . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

2.4.1 Fundamentals of Wireless MAC Protocols . . . . . . . . . . . . . 17

2.4.2 CSMA/CA Protocols . . . . . . . . . . . . . . . . . . . . . . . . . 21

2.4.3 MAC Protocols in Industrial Standards . . . . . . . . . . . . . . 23

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xii CONTENTS

2.4.4 Open Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

2.5 TDMA Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

2.5.1 Scheduling Problems . . . . . . . . . . . . . . . . . . . . . . . . . 26

2.5.2 Network Model and Wireless Conflict Model . . . . . . . . . . . 27

2.5.3 Scheduling Algorithms . . . . . . . . . . . . . . . . . . . . . . . 28

2.5.4 Open Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

2.6 Routing Protocols in WSN . . . . . . . . . . . . . . . . . . . . . . . . . . 31

2.6.1 Collection Tree Protocol . . . . . . . . . . . . . . . . . . . . . . . 33

2.7 Implementation of Communication Protocols in WSN . . . . . . . . . . 35

3 Summary of Contributed Papers 37

4 Conclusions and Future Work 45

4.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

4.2 Future work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

Bibliography 47

PAPER I 57

PAPER II 85

PAPER III 117

PAPER IV 147

PAPER V 161

Biography 177

List of Papers

This thesis is mainly based on the following papers, herein referred by their Romannumerals:

Paper I PriorityMAC: A Priority-Enhanced MAC Protocol for Critical Traffic inIndustrial Wireless Sensor and Actuator NetworksW. Shen, T. Zhang, F. Barac, and M. GidlundJournal article, IEEE Transactions on Industrial Informatics, Vol. 10, No. 1,pp. 824-835, Feb. 2014.

Paper II CCA-Embedded TDMA Enabling Acyclic Traffic in Industrial WirelessSensor NetworksD. Yang, M. Gidlund, W. Shen, Y. Xu, T. Zhang, and H. ZhangJournal article, Ad Hoc Networks, Vol. 11, Issue 3, pp. 1105-1121, May 2013.

Paper III SAS-TDMA: A Source Aware Scheduling Algorithm for Real-Time Com-munication in Industrial Wireless Sensor NetworksW. Shen, T. Zhang, M. Gidlund, and F. DobslawJournal article, Wireless Networks, Vol. 19, No. 6, pp. 1155-1170, Aug. 2013.

Paper IV Distributed Data Gathering Scheduling Protocol for Wireless SensorActor and Actuator NetworksW. Shen, T. Zhang, and M. GidlundProceeding of Communications (ICC), 2012 IEEE International Conference on,pp. 7120-7125, Ottawa, Canada, 10-15 June 2012.

Paper V Joint Routing and MAC for Critical Traffic in Industrial Wireless Sensorand Actuator NetworksW. Shen, T. Zhang, and M. GidlundProceeding of Industrial Electronics (ISIE), 2013 IEEE International Symposiumon, pp.1-6, 28-31 May 2013.

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Related articles, but not included in the thesis:

Paper VI Smart Border Routers for eHealthCare Wireless Sensor NetworksW. Shen, Y. Xu, D. Xie, T. Zhang, and A. Johansson.Proceeding of 7th International Conference on Wireless Communications, Net-working and Mobile Computing (WiCOM), pp.1-4, 23-25 Sept. 2011.

Paper VII An ANT Based Wireless Body Sensor Biofeedback Network for Med-ical E-Health CareA. Johansson, W. Shen, and Y. Xu.Proceeding of 7th International Conference on Wireless Communications, Net-working and Mobile Computing (WiCOM), pp.1-5, 23-25 Sept. 2011.

Paper VIII A Virtual Hypercube Routing Algorithm for Wireless Healthcare Net-worksH. Huo, W. Shen, Y. Xu, and H. Zhang.Journal article, Chinese Journal of Electronics,Vol.19, No.1, Jan. 2010.

List of Figures

1.1 An example of future industrial automation networks [34] . . . . . . . 2

1.2 The protocol framework proposed in the thesis . . . . . . . . . . . . . . 6

2.1 Standardization of low-power and resource-constrained wireless tech-nologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.2 A brief comparison of WirelessHART, ISA-100.11a, WIA-PA and IEEE802.15.4e . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

2.3 An example of the preamble sampling technique [47] . . . . . . . . . . 19

2.4 Illustration of IEEE 802.15.4 superframe structure [2] . . . . . . . . . . . 23

2.5 Summary of WirelessHART packet format . . . . . . . . . . . . . . . . 24

2.6 WirelessHART time slot and superframe [5] . . . . . . . . . . . . . . . . 24

2.7 An example of cluster tree network architecture in IEEE 802.15.4 [5] . . 32

2.8 Illustration of the operation of CTP protocol . . . . . . . . . . . . . . . . 34

2.9 A typical commercial development stack for WSNs . . . . . . . . . . . 35

3.1 PriorityMAC experiment shows it is able to efficiently handle differentcategories with different latency requirements. . . . . . . . . . . . . . . 39

3.2 A comparison of nodes proportions with different PDR levels for SAS-TDMA algorithm and level-based algorithm with the refresh intervalof 3.1s. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

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List of Tables

2.1 A comparison of low-power and resource-constrained wireless tech-nologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

2.2 Typical MCUs used in IEEE 802.15.4-compliant wireless devices . . . . 12

2.3 Typical transceivers used in IEEE 802.15.4-compliant wireless devices . 12

2.4 Notations of network model for scheduling algorithms . . . . . . . . . 28

2.5 Notations of network model for the level-based algorithm . . . . . . . 29

3.1 Objective, topics and my participation associated with correspondingpapers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

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Terminology

Abbreviations and Acronyms

WSN Wireless Sensor Networks

WPAN Wireless Personal Area Network

LR-WPAN Low Rate Wireless Personal Area Network

SoC System on Chip

IWSAN Industrial Wireless Sensor and Actuator Network

MAC Medium Access Control

DSSS Direct Sequence Spread Spectrum

O-QPSK Offset Quadrature Phase-Shift Keying

BPSK Binary Phase-Shift Keying

PSSS Parallel Sequence Spread Spectrum

ASK Amplitude Shift Keying

FHSS Frequency Hopping Spread Spectrum

GFSK Gaussian Frequency-Shift Keying

OFDM Orthogonal Frequency-Division Multiplexing

QAM Quadrature Amplitude Modulation

PDR Packet Delivery Ratio

nesC Network Embedded System C (programming language)

MCU Microcontroller

DCF Distributed Coordination Function

DIFS Distributed Interframe Space

CAP Contention Access Period

CFP Contention Free Period

GTS Guaranteed Time Slot

AFS Adaptive Frequency Switch

AFH Adaptive Frequency Hopping

DSME Deterministic and Synchronous Multi-channel Extension

GW Gateway

CCA Clear Channel Assessment

RTS Request To Send

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xx LIST OF TABLES

CTS Clear To Send

ETX Expected Transmission count

RSS Received Signal Strength

RAM Random Access Memory

ROM Read Only Memory

Standards Organizations

IETF Internet Engineering Task Force

IEC International Electrotechnical Commission

IPSO Alliance Internet Protocol for Smart Objects Alliance

ISA International Society of Automation

ROLL Routing Over Low power and Lossy networks (IETF workinggroup)

CORE Constrained RESTful Environments (IETF working group)

MANET Mobile Ad-hoc Networks (IETF working group)

Standards, Protocols and Algorithms

HART Highway Addressable Remote Transducer

TDMA Time Division Multiple Access

WirelessHART Wireless Highway Addressable Remote Transducer

DBR Delay Bounded Routing protocol

6LoWPAN IPv6 over Low power WPAN

RPL Routing Protocol for Low Power and Lossy Networks

CoAP Constrained Application Protocol

HTTP HyperText Transfer Protocol

BT-LE Bluetooth Low Energy

CSMA/CA Carrier Sense Multiple Access with Collision Avoidance

WIA-PA Wireless network for Industrial Automation - Process Automa-tion

TSMP Time Synchronized Mesh Protocol

FDMA Frequency Division Multiple Access

AES Advanced Encryption Standard

TSCH Time-Synchronized Channel Hopping

CDMA Code Division Multiple Access

SDMA Space Division Multiple Access

SMAC Sensor Medium Access Control protocol

BMAC Berkeley Medium Access Control protocol

WiseMAC Wireless Sensor Medium Access Control protocol

UDP User Datagram Protocol

LIST OF TABLES xxi

LEACH Low-Energy Adaptive Clustering Hierarchy protocol

TEEN Threshold sensitive Energy Efficient sensor Network protocol

HEED Hybrid Energy-efficient Distributed clustering protocol

GBR Gradient Based Routing protocol

GRAB GRAdient Broadcast protocol

AODV Ad hoc On-Demand Distance Vector routing protocol

OLSR Optimized Link State Routing protocol

TBRPF Topology Dissemination Based on Reverse-Path Forwarding pro-tocol

DSR Dynamic Source Routing protocol

CTP Collection Tree Protocol

FTSP Flooding Time Synchronization Protocol

PriorityMAC Priority-enhanced Medium Access Control protocol

SAS-TDMA Source Aware Scheduling algorithm for TDMA based IWSAN

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Chapter 1

Introduction

1.1 Overview

Low-power and resource-constrained wireless technology offering low data ratehas been regarded as an emerging technology that introduces a paradigm shift ina wide range of applications such as industrial automation, smart grid, smart citiesand urban networks, home automation, and structural health monitoring. Early con-ceptual designs of such technology can be traced back to the emergence of the dis-tributed sensor networks program at the MIT Lincoln Labs in 1983 [1]. It aimedat developing and extending target surveillance and tracking technology in sys-tems that employ multiple spatially distributed sensors and processing resources.In the following years, wireless sensor networks (WSN) have not only been demon-strated in research communities, but also attracted commercial interest. In orderto facilitate interoperability that existing proprietary systems cannot provide, IEEE802.15.4 Low Rate Wireless Personal Area Network (LR-WPAN) standard was ini-tially released in 2003. The standard is a simple and low-cost communication net-work that allows wireless connectivity in applications with limited power and re-laxed throughput requirements [2]. It has been worldwide accepted and adoptedfar beyond its expected applications areas. Zigbee Alliance, Internet EngineeringTask Force (IETF), International Electrotechnical Commission (IEC), Internet Pro-tocol for Smart Objects (IPSO) Alliance, Highway Addressable Remote Transducer(HART) Communication Foundation, International Society of Automation (ISA) andother international standards organizations have leveraged IEEE 802.15.4 as a baseto build their upper standards. Multitude of leading semiconductors manufacturersworldwide made IEEE 802.15.4-compatible single-chip transceivers and/or system-on-chip (SoC) chips. Thousands of worldwide researchers have been attracted toconduct theoretical research, create prototypes and open pioneering companies. Agrowing number of global companies have been promoting IEEE 802.15.4-compatibleproducts evolutions.

Industrial automation is a wide area including process automation, factory au-

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2 Introduction

Figure 1.1: An example of future industrial automation networks [34]

tomation, substation automation, building automation [3]. Obviously, automationindustry has been significantly contributing to economic revenues, job opportuni-ties and world-class research. According to a report from a number of Swedishautomation companies and organizations in 2012, 60 percent of Swedish nationalhousehold’s total export earnings comes from the process industry, which representsaround 13% of Sweden’s total GDP [4]. The process automation will be regarded asthe main case study to discuss in the thesis. Unless otherwise stated, “industrialautomation” refers to “industrial process automation” in the rest of the thesis.

Low-power and resource-constrained wireless technology has been bringing newopportunity and challenges for industrial automation, especially for communicationtechnology in field networks. In a field network, industrial control and instrumenta-tion devices (such as sensors, actuators) provide process applications such as mon-itoring, measurement, alarms, diagnostics and process control [5–8] (an example offuture industrial automation networks is shown in Fig. 1.1). Then, the concept, In-dustrial Wireless Sensor and Actuators Networks (IWSAN), is formed to representthe emerging technology. These applications typically have low-data-rate transmis-sions and small-size packets. Low-power consumption is required and real-timecommunication is generally crucial [8]. Industrial automation networks includingfield networks traditionally utilize wired communication such as HART protocol.HART communication foundation addresses that there are approximately 30 mil-lion HART devices installed and in service worldwide. The solutions of low-powerand resource-constrained wireless technology offer benefits in relation to lower cost,

1.2 Problem Description 3

easier deployments and maintenance than the wired solutions. Therefore, a notabletrend in industrial automation in recent years has been the replacement of wiredcommunication with low power and low cost wireless sensor and actuator networks.

However, such wireless solutions have been introducing new challenges. Wire-less links are inherently unreliable, especially in industrial harsh environments, andwireless interference makes the problem even worse. How to guarantee timely, re-liable and secure communication becomes more significant research topics. This re-search work addresses two vital issues on top of real-time service discussed in thefollowing section. A series of novel solutions have been proposed, analyzed andevaluated after exploring related academic work and industrial standards.

1.2 Problem Description

Most of the existing WSN protocols primarily focusing on energy efficiency areunable to meet the real-time requirement in industrial automation applications. Thatis because most of them adopt contention-based or similar Medium Access Con-trol (MAC) protocols, which cannot provide deterministic behavior. But real-timecommunications require timely, reliable and predictable transmissions [9]. There-fore, standards in industrial automation, WirelessHART, ISA100.11a and WIA-PA,IEEE 802.15.4e which leverage IEEE 802.15.4 physical layer, introduce scheduling-based MAC protocols to provide a guaranteed access or bounded latency. The stan-dards also adopt packet-level channel hopping to improve the reliability of individ-ual wireless links by combating external interference and multi-path fading. Thisresearch work addresses that IWSAN should also be designed to provide and enhanceservice differentiation for wireless medium access and adapt to link dynamics for schedulingalgorithms on top of real-time service.

Firstly, a typical wireless industrial automation network deployment consists offield devices equipped with sensors and actuators that communicate with the plantnetwork. Three categories of data traffic in industrial automation applications are:safety, control and monitoring [6]. The safety category refers to emergency actiontraffic, which is the most critical traffic class. The closed loop regulatory control,closed loop supervisory control and open loop control classes constitute the controlcategory. The monitoring category consists of alerting class, in addition to the log-ging and downloading/uploading classes. The current standards mentioned aboveare able to provide guaranteed access (with a suitable scheduling algorithm) for pe-riodic traffic such as monitoring. However, they are unable to provide lower latencyin relation to unpredictable and emergency traffic because it is impossible for thistype of traffic to have a priori assigned dedicated transmission time due to its non-deterministic occurrence. Exceeding a required delay bound for this type of traffic(e.g. an emergency safety action, an unpredictable critical control or an acyclic re-transmission of critical control data) could lead to system instability, incur financiallosses and even pose a threat to human safety [10]. Therefore, granting the prioriti-zation of this critical traffic over regular traffic (e.g. non-critical and periodic traffic)is a fundamental problem. This is challenging for wireless technologies because the

4 Introduction

unpredictability regarding the arrival of the aperiodic traffic cause difficulties withregarding to making a suitable scheduling or reserving wireless bandwidth in orderto guarantee its deadline. In order to solve this problem, the guaranteed access fornon-critical traffic can be deferred or even destroyed. Thus, the real-time communi-cation mechanisms with service differentiation for priority of critical traffic over noncritical traffic is vital in IWSAN.

Secondly, the requirement of dynamic is illustrated as follows. As mentioned,Time Division Multiple Access (TDMA), which is a typical scheduling-based proto-col, is utilized in IWSAN standards. TDMA scheduling algorithms are not specifiedin the standards. Previous work on TDMA scheduling for WSN addressed severalobjectives, such as the determination of shortest schedules, or the finding of trade-offs between delay and energy consumption. Nevertheless, the majority of existingapproaches do not consider the effects of unreliable wireless links on scheduling al-gorithms. Link failures can result in schedules of broken order. Individual wirelesslinks are inherently unreliable. Observations on real-platform testbeds with low-power wireless sensor networks show that links have wide ranges of packet deliveryratio (PDR) which can vary significantly over time, even without intra-collisions orhigh portions of external interference [11–13]. The dynamics of individual links areeven more unpredictable in industrial environments, because of the human block-age, machinery and products obstacles. A centralized scheduling mechanism forindustrial applications is thus taken as an example to describe this issue. In cen-tralized scheduling, schedule requests come with topology and routing informationwhen sent to the sink. The sink then runs a centralized scheduling algorithm anddistributes the schedules to the sensors. Neighbors and routing information maychange very frequently because of the unreliable nature of the individual wirelesslinks and obstacles, thus generating heavy configurational overhead. This overheadin return increases the end-to-end delay. Therefore, IWSAN require scheduling al-gorithms which can adapt to link dynamics in real environment.

1.3 Objective and Research Topics

The overall aim of the research project is to propose solutions to solve vital chal-lenges (such as real-time, service differentiation, adaption to link dynamics, secu-rity, wireless coexistence) in terms of applying emerging low-power and resource-constrained wireless technology to industrial automation applications.

Objective: The objective of this research work is to design algorithms and proto-cols on top of real-time communications in IWSAN to:

• enhance service differentiation for TDMA-based wireless medium access

• adapt to link dynamics for scheduling algorithms

and to develop a prototype to evaluate and demonstrate potential of proposedsolutions.

1.4 Research Methodology 5

Research topics: Specifically, the research topics are formulated into the follow-ing questions.

• (Paper I and V) Why is it a vital issue and challenge to provide service dif-ferentiation for TDMA-based wireless medium access? How to enable unpre-dictable critical traffic to timely delivery and to have priority over real-timeguaranteed non- or less-critical traffic?

• (Paper II) How to improve the transmission efficiency for burst acyclic trafficin WirelessHART and ISA100.11a based IWSAN?

• (Paper III) What are limitations of state-of-the-art scheduling algorithms intime division multiple access based wireless sensor networks in terms of indus-trial automation applications? How to adapt to link dynamics for schedulingalgorithms in real environment?

• (Paper IV) Applications in industrial automation typically have low-data-ratetransmissions and small-size packets, thus, there is typically a short-length sen-sor data with a relatively large overhead in each packet. How to efficientlyschedule the transmissions in real environments to reduce traffic load, which,in turn, is useful for cost efficiency?

1.4 Research Methodology

The research methodologies used throughout the research work will be discussedin this section.

• Motivated by the realistic issues and challenges, exploring state-of-the-art workhas been conducted. Then, a series of novel algorithms and protocols havebeen proposed after establishing a specific research objective. A layered archi-tecture has been used to design protocols. Each layer has its own protocolsand offers services to the layer above. The protocols of the various layers arecalled the protocol stack. The seven-layer OSI model is a well-known refer-ence model for protocol stack design. This thesis work adopts five layers ofthe model: physical layer, data ink layer, network layer, transport layer andapplication layer, since the session layer and presentation layer are normallynot specified in wireless sensor networks.

• The analytical methods using probability and random processes have beenused to analyze the performance of proposed algorithms and protocols fromtheoretical standpoint. The performance such as delay has been formulatedinto mathematical equations to provide an intuition on the high level of theproposed algorithms and protocols. The theoretical results have been furthercompared with simulation results to evaluate to what extent they match eachother. Besides, the equations can also be useful for the design purposes for realsystems by deriving corresponding parameters in practice.

6 Introduction

• An implementation and the empirical evaluation on the implementation in atestbed is one of the most important methods in WSN research community.In order to develop a prototype to evaluate and demonstrate potential of pro-posed solutions, I have used a pragmatic approach to realize proposed solu-tions in a hardware testbed consisting of about 100 battery-powered resource-constrained embedded wireless devices. I have programmed using TinyOS[14] based on open sources such as TinyOS community [15], Contiki commu-nity [16], Berkeley OpenWSN [17].

• Most of the proposed solutions have been implemented in a simulator, TOSSIM[18], and some of them have been implemented in Matlab. The Matlab sim-ulation has similar assumptions to ones in theoretical analysis so that it canbe used to evaluated the correctness of theoretical analysis and vice versa.TOSSIM emulates the behavior of underlying raw hardware and it capturesreal-world environmental noise. Besides, TinyOS and TOSSIM is a widely ac-cepted and used simulator in academic research community of wireless sensornetwork so that researchers can make fair comparisons between different solu-tions.

• The statistical methods (e.g., mean squared errors) have been utilized to evalu-ate differences between mathematical and simulation results; the experimentalmethods have been adopted to compare the proposed algorithms and proto-cols with state-of-the-art algorithms, protocols and standards.

1.5 Contributions

Figure 1.2: The protocol framework proposed in the thesis

1.6 Thesis Outline 7

The thesis proposes a protocol framework for adaptive real-time communicationin industrial wireless sensor and actuator networks to achieve the research objective.Fig. 1.2 illustrates this protocol framework and specific components associated withcontributed papers.

Specifically speaking, the protocol framework consists of two MAC protocolspresented in Paper I and II, two cross-layer scheduling protocols in Paper III andIV, and a routing protocol in Paper V.

• Paper I addresses a vital issue of IWSAN, namely, service differentiation forpriority of critical traffic over non critical traffic, in real-time industrial au-tomation applications. The paper proposes PriorityMAC, a Priority enhancedMAC protocol. To the best of our knowledge, this is the first priority-enhancedMAC protocol compatible with industrial standards for IWSAN. Paper V pro-poses Delay Bounded Routing (DBR) and extends the PriorityMAC to networklayer by joint DBR and the PriorityMAC, designed for routing critical traffic inIWSAN.

• Paper II proposes a CCA-Embedded TDMA scheme that improves the trans-mission efficiency for burst acyclic traffic in WirelessHART and ISA-100.11abased industrial wireless networks.

• Paper III presents SAS-TDMA, a Source-Aware Scheduling algorithm whichuses a cross-layer solution to adapt to link dynamics in real environments. Pa-per IV further proposes a novel distributed scheduling protocol for data gath-ering transmission. It is also able to adapt the dynamics of links in a realisticlow-power wireless network. In addition, the protocol reduces the schedulingtraffic through maintaining distributed lightweight conflict-links tables. Thepurpose to adapt to link dynamics for scheduling algorithms significantly dif-ferentiates the contributions in the two papers from ones in most of state-of-the-art scheduling algorithms articles.

1.6 Thesis Outline

The remainder of the thesis is organized as follows. The background and relatedwork about the topics covered in the thesis are discussed in Chapter 2. Chapter3 presents summary of contributed papers. The conclusion and future work areprovided in Chapter 4.

8

Chapter 2

Background and Related Work

In this chapter, a comprehensive overview of low power and resource constrainedwireless technology, IWSAN and the standardization evolution of IWSAN, MACprotocols, TDMA scheduling, routing protocols and implementation in WSN is givenand discussed.

2.1 Low-Power and Resource-Constrained Wireless

Technology

Low power and resource constrained wireless technology and the advanced sen-sors/actuators technologies have been regarded as an emerging technology (i.e.,WSN) applying in a wide range of applications. In order to facilitate interoperabilitythat existing proprietary systems cannot provide, IEEE 802.15.4 LR-WPAN standardwas initially released in 2003 [2]. As mentioned in Chapter 1, it has been worldwideaccepted and applied far beyond its expected applications areas. Zigbee Alliance,IETF, IEC, IPSO Alliance, HART Communication Foundation, ISA and other interna-tional standards organizations have leveraged IEEE 802.15.4 as a base to build theirupper standards. Multitude of leading semiconductors manufacturers worldwidemade IEEE 802.15.4-compatible single-chip transceivers and/or SoC chips. Thou-sands of worldwide researchers have been attracted to conduct theoretical research,create prototypes and open pioneering companies. IEEE 802.15.4 becomes a de-factostandard in WSN. In 2012, the IEEE 802.15.4e standard [19] released with defininga MAC amendment to the existing standard IEEE 802.15.4-2006 to better supportindustrial markets.

Besides, various IETF working groups, IPv6 over Low power WPAN (6LoW-PAN), Routing Over Low power and Lossy networks (ROLL) and IETF ConstrainedRESTful Environments (CORE), have accomplished the integration of IEEE 802.15.4-compliant networks into the Internet, as shown in Fig. 2.1. In the network layer,the IETF 6LoWPAN working group has started in 2007 to specify a protocol, 6LoW-

9

10 Background and Related Work

Figure 2.1: Standardization of low-power and resource-constrained wireless technologies

PAN [20], for transmitting IPv6 over IEEE 802.15.4 networks by introducing 6LoW-PAN adaptation layer. On top of that, the IETF ROLL working group has standard-ized a Routing Protocol for Low Power and Lossy Networks (RPL) [21]. In applica-tion layer, a Constrained Application Protocol (CoAP) has been defined by the IETFCORE working group with the purpose of running RESTful architectures such asthe client/server model defined by HyperText Transfer Protocol (HTTP) over lowpower and constrained wireless networks, meeting very low overhead and simplic-ity for constrained environments [22].

Recently, low-energy Bluetooth and low-power WiFi [23] become realistic. Fig.2.1 also shows associated standardizations. Bluetooth Low Energy (BT-LE) [24], in-cluded in Bluetooth 4.0 released by Bluetooth Special Interest Group in 2010, is aradio technology targeted for devices that operate with coin cell batteries, whichmeans that low power consumption is essential. BT-LE can also be integrated intoexisting Bluetooth devices so that devices such as mobile phones and computerscan operate with existing Bluetooth accessories as well as BT-LE accessories. IEEE802.11ah, targeting applications of wireless sensor networks, backhaul networks forsensor and meter and extended range of Wi-Fi, is being designed for supporting ap-plications with the following requirements [25]: up to 8191 devices associated to anaccess point, adoption of power saving strategies, minimum network data rate of100 kbps, operating carrier frequencies around 900 MHz, coverage up to 1 km inoutdoor areas, one-hop network topology and short infrequent data transmissions.

2.2 Industrial Wireless Sensor and Actuator Networks 11

The standardization shall be completed approximately by March 2016 [26].

Table 2.1 shows a comparison of low-power and resource-constrained wirelesstechnologies above regarding to radio modulation, transmission range, data rate,power saving mechanism, MAC and supported topology. As can be seen, the mainfeatures of low power and resource constrained wireless technologies include lowdata rate, low complexity of physical and MAC layer, low power consumption andetc. In order to further understand theses feature, typical Microcontrollers (MCUs)and transceivers used in IEEE 802.15.4-compliant wireless devices have been shownin Tables 2.2 and 2.3. We can see that theses MCUs have constrained computationalcapability with small size of memory and support ultra low power operating mode.Table 2.3 also shows that radios draw about the same current in transmit and receivemode. Improving the efficiency of power consumption for a system therefore con-sists in lowering the duty cycle of the radio as a whole, i.e. having the radio off mostof the time [1].

Table 2.1: A comparison of low-power and resource-constrained wireless technologies

IEEE 802.15.4 Bluetooth-LE IEEE 802.11ah

Sub-1 GHz OFDM BPSK,

2.4 GHz DSSS O-QPSK 2.4 GHz FHSS GFSK QPSK,

Modulation 868/915 MHz DSSS O-QPSK/BPSK (lower complexity than 16/64/256-QAM

868/915 MHz PSSS BPSK and ASK classic Bluetooth) (Ten times down clocking

of 802.11ac)

Range up to 100 m up to 50 m up to 1 km

1 Mbps >100 Kbps

Data rate up to 250 Kbps (up to 3Mbps

in Classic Bluetooth) (one-tenth of 802.11ac)

Power saving Active/Inactive period Active/Low-power state Awake/Doze duty cycle

Enhanced Distributed

MACCSMA/CA/

FDMA/TDMACoordination Function (EDCF)

TDMA + channel hopping +

contention-free access method

Topology Star, tree, mesh Star Star

2.2 Industrial Wireless Sensor and Actuator Networks

Recent years, wireless monitoring and control solutions in industrial automa-tion have the benefits of low cost and flexible deployments and maintenance overwired solutions (e.g., Fieldbus system and wired HART) [27–31]. The low-powerand resource-constrained wireless has been regarded as one of main appropriate


Table 2.2: Typical MCUs used in IEEE 802.15.4-compliant wireless devices

MCU coreManufacturer Size of RAM

Other featuresand/or Module and Flash

STM32L:e.g., 16 KB RAM 1.65 V to 3.6 V power supply

32-bit ARM Cortex M3 STMicroelectronics’ 128 KB Flash 9 µA low power run modeSTM32L series (typically) 0.9 µA standby mode

< 8 µs wakeup time

10 KB RAM 1.8 V to 3.6 V power supply16-bit MSP430 TI 128 KB Flash 2.1 µA standby mode

(typically) 3.5 µs wakeup time

18 KB RAM 2.7 V to 3.3 V power supply8-bit ATmega Atmel 128 KB Flash 8 mA in Active mode

(typically) < 15 µA in Sleep mode

Table 2.3: Typical transceivers used in IEEE 802.15.4-compliant wireless devices

Current consumptionChips Manufacturer Supply voltage

Sleep RX ON TX ON

CC2420 TI < 1 µA 18.8 mA 17.4 mA 2.1 V - 3.6 V

AT86RF231 Atmel 0.02 µA 12.3 mA 14.0 mA 1.8 V - 3.6 V

CC2530 (SoC,TI

0.4µA, 1µA, 24.0 mA 29.0 mA2.0 V - 3.6 V

MCU+Transceiver) 0.2 mA (MCU Idle) (MCU Idle)

2.2 Industrial Wireless Sensor and Actuator Networks 13

wireless technologies to apply in the industrial automation applications, especiallyfor applications in field networks. In a field network, industrial control and instru-mentation devices (such as sensors, actuators) provide process applications such asmonitoring, measurement, alarms, diagnostics and process control [5–8]. Then, theconcept, IWSAN, is formed to represent the emerging technology. A notable trendin industrial automation in recent years has been the replacement of wired commu-nication with IWSAN.

The unique challenges and constraints of IWSANs have been attracting signifi-cant attentions in research community. The authors in [7,27,32–34] have investigatedstate-of-the-art and future requirements and challenges for IWSANs.

Industrial automation networks traditionally utilize wired communication. Somerequirements, such as real-time, safety, security, low-power consumption, backwardcompatibility, low-cost hardware, are essential for both wired and wireless solutions.But the major technical challenges between wired and wireless are different in orderto meet those common requirements.

• Real-time: The real-time communications, which require timely, reliable andpredictable transmissions [9], are essential for industrial automation applica-tions.

• Safety: The automation devices should be designed to avoid or reduce the riskof uncontrolled or dangerous situations for safety of humans, environment andproperty [34].

• Security: The communication of IWSAN should be designed to avoid or reducethe denial-of-service attacks and intrusions [32].

• Low-power consumption: Wireless enables sensors and actuators to be flexi-ble for deployment. IWSAN devices equipped with batteries may be deployedin bearings of motors, oil pumps, or hazardous environment [35] so as to beimpractical to change batteries within a few years. Thus, low-power consump-tions of processor, transceivers, software communication stack are necessaryand important.

• Backward compatibility: Unlike short-lifetime products in consumer marketsuch as smart phones, devices in industrial automation normally have longlifetimes, e.g., 10 years [8]. Thus, it is important for IWSAN devices to havebackward compatibility.

• Integration: The integration here refers to IWSAN should be efficiently andsmoothly integrated into other existing infrastructures [34]. For example, atypical wireless field network consists of field devices normally communicatewith the plant network.

• Low-cost hardware: The low-cost hardware is realized by the design of resource-constraint devices.


In summary, on the one hand, real-time and secure communication, design forsafety are required for IWSAN. On the other hand, IWSAN has to meet the require-ments of low-power consumption and low-cost hardware with limited computa-tional ability. The major challenges come when attempting to meet the “conflicting”requirements.

Furthermore, IWSAN has been introducing new challenges due to the inher-ent features of shared communication medium in wireless, self-organized and self-configured multi-hop networks and etc.

• Adapt to topology dynamics: As mentioned in Chapter 1, individual wirelesslinks are inherently unreliable, which incurs topology. The dynamics of indi-vidual links are even more unpredictable in industrial environments, becauseof the human blockage, machinery and products obstacles. Thus, the adaptionto topology changes is one of the challenges when designing communicationstack for IWSAN. This is one of the two key issues addressed in this thesis.

• Service differentiation for wireless medium access: This research work also ad-dresses that IWSAN should also be designed to provide service differentiationfor wireless medium access. The challenge is how to enable unpredictable crit-ical traffic to timely delivery and to have priority over real-time guaranteednon- or less-critical traffic.

• Wireless coexistence: IWSANs, such as WirelessHART and ISA-100.11a basedwireless networks, share wireless medium with other wireless devices, whichincurs the collisions of spectrum resource [36], i.e. coexistence problem.

• Interoperability: The evolution of IWSAN in industrial automation applica-tions is suffering from the interoperability problem among different indus-trial standards, such as WirelessHART, ISA-100.11a, WIA-PA, IEEE 802.15.4eand other standards. The new wireless technologies and resource-constrainedIP based technologies may promote convergence solutions from a techniquestandpoint.

Industrial automation is a wide area and thus, there are wide variety of applica-tion requirements. Recent years, there are a series of industrial standards targetingat the process automation, especially for field networks.

2.3 Standardization Evolution of IWSAN

The needs of low data rate and low power consumption for long battery lives andfor large device amount have become significant for sensors and control/actuatorsdevices since more than ten years ago in wireless communication market. In orderto facilitate interoperability that existing proprietary systems cannot provide, IEEE802.15.4 standard was initially released in 2003, which becomes a de-facto standardin low-power and resource-constrained wireless sensor and actuator networks in thefollowing years.

2.3 Standardization Evolution of IWSAN 15

ZigBee [37] is the most common standard among commercially available off-the-shelf solutions in the consumer market [38] and it is based on the IEEE 802.15.4 speci-fication. It utilizes carrier sense multiple access with collision avoidance (CSMA/CA)as the multiple access control method, which can provide both a low delay and po-tentially sufficient throughput at low traffic loads without heavy external interfer-ence. This is particularly true for unpredictable traffic. Nevertheless, CSMA/CA isunable to provide guaranteed access to the wireless channel as the network densityincreases. It is also unable to serve the high number of devices within the specifiedcycle time in industrial applications [32]. Thus, CSMA/CA-based mechanisms areunsuitable for industrial automation applications, which have strict timing require-ments [39, 40]. As a result, a series of industrial communication standards such asWirelessHART [5], ISA-100.11a [6], IEEE 802.15.4e [19] and WIA-PA [41] which haveadopted IEEE 802.15.4 Physical layer have been released in recent years.

TSMP A Time Synchronized Mesh Protocol (TSMP) which leverages IEEE 802.15.4PHY was published in 2008. It is a medium access and networking protocol de-signed for the ratified WirelessHART standard in 2007 [42]. TSMP was standardizedas one of the main proposed contributions in WirelessHART, ISA-100.11a and IEEE802.15.4e.

WirelessHART (IEC 62591) WirelessHART was the first open standard specifi-cally designed for wireless communication in process measurement and control ap-plications [43]. It officially presented by the HART Communication Foundation inSeptember, 2007 aiming to be compatible with existing HART devices by addingwireless communication capability to the HART protocol. At the very bottom, itadopts IEEE 802.15.4-2006 as the physical layer. On top of that, WirelessHARTdefines its own time-synchronized MAC layer. The network layer supports self-organizing and self-healing mesh networking techniques. In this way, messages canbe routed around interferences and obstacles [5, 43]. WirelessHART adopts a cen-tralized routing scheme, in which a network manager is responsible for maintainingup-to-date routes and communication schedules for devices in the network. Wire-lessHART specification was approved by IEC as a full international standard (IEC62591) in March 2010. A growing number of WirelessHART compatible productsare available from major global suppliers such as ABB, Emerson, Endress+Hauser,Pepperl+Fuchs, Siemens.

ISA-100.11a (IEC 62734) The ISA initiated work on a family of standards defin-ing wireless systems for industrial automation and control applications. The mainpurpose of the ISA100 committee is to provide a family of standards for industrialwireless networks, which will address the needs of the whole plant, such as processcontrol, personnel and asset tracking and identification convergence of networks,and long-distance applications. ISA-100.11a is the first standard of the family andit was ratified in September 2009. It describes a mesh network designed to providesecure wireless communication to process control. ISA-100.11a received the IEC ap-proval as international standard (IEC 62734) in 2011. The global suppliers that makecompatible products such as Honeywell, Yokogawa, Invensys, General Electric, Ma-soneilan, Yamataki, Fuji.


Figure 2.2: A brief comparison of WirelessHART, ISA-100.11a, WIA-PA and IEEE 802.15.4e

WIA-PA (IEC 62601) Chinese Industrial Wireless Alliance was established (inthe leading of the Shenyang Institute of Automation, Chinese Academy of Science)in 2007 aiming to develop standards for industrial wireless network [44]. Wirelessnetwork for Industrial Automation - Process Automation (WIA-PA) is the first stan-dard developed by the alliance for the urgent needs of process industries. WIA-PAdefines the system architecture and communication specifications for the process au-tomation. It was approved by IEC as international standard (IEC 62601) in 2011.

IEEE 802.15.4e The IEEE802.15.4e standard released in 2012 [19] defines a MACamendment to the existing standard IEEE 802.15.4-2006 to better support industrialmarkets. It announces to achieve better reliability and lower power consumptionthrough time-synchronized channel hopping (TSCH).

Fig. 2.2 presents a comparison of WirelessHART, ISA-100.11a, WIA-PA and IEEE802.15.4e. As can be seen, they all build on top of IEEE 802.15.4 PHY with modi-fied MAC protocols. They have the same features in physical layer such as 250 kbpsdata rate, 16 channel direct sequence spread spectrum radio with 128-bit AES se-curity encryption. In data link layer, TDMA and channel hopping are deployed inall of the standards with individual channel hopping mechanisms (TSCH in IEEE802.15.4e is also TDMA based protocol). WirelessHART uses a slot time of 10 ms.

2.4 MAC Protocols for WSN 17

ISA-100.11a, WIA-PA and IEEE 802.15.4e uses a variable slot time, but defaults to10 ms. In network layer, All of the standards specifies or supports mesh networkarchitecture with individual routing protocols to overcome obstacles, reach longerdistances, create resilient paths for increasing reliability and etc. However, Wire-lessHART and WIA-PA do not support IPv6 packet format, while ISA-100.11a doesby employing IETF 6LoWPAN protocol as an adaptation sublayer. WIA-PA does notspecify any transport-layer protocols, while ISA-100.11a uses User Datagram Proto-col (UDP) and WirelessHART utilizes its own proprietary protocol. In applicationlayer, HART-compliant protocol is used in WirelessHART to be compliant with ex-isting HART devices. WIA-PA uses a proprietary protocol while ISA-100.11a doesnot specify any protocols in this layer.

2.4 MAC Protocols for WSN

MAC protocols of the data link layer in wireless communication are essentiallyused to determine the times during which a number of contending and collidingnodes access to a shared wireless medium. The problem solved by MAC protocolsis a fundamental issue in any a wireless network. Thus, MAC protocols have beenattracting a huge number of researchers to develop new MAC protocols for emerg-ing wireless technologies during the past more than thirty years. When consideringthe choice of MAC protocols for a wireless technology, several factors have to bebalanced: the feature of communication requirement, implementation complexity,antenna complexity, signal processing ability, and etc. This section will present thefundamentals of wireless MAC protocols, CSMA/CA protocol in detail, and MACprotocols in industrial automation standards.

2.4.1 Fundamentals of Wireless MAC Protocols

Traditionally, MAC protocols for wireless communications can be roughly classi-fied [45] as: fixed assignment protocols, demand assignment protocols and randomaccess protocols.

Fixed assignment protocols: wireless bandwidth resources are divided and as-signed to nodes or links in a long term. Each node or link uses its own dedicatedresource without the risk of collisions. The typical protocols include Frequency Di-vision Multiple Access (FDMA), Code Division Multiple Access (CDMA), Space Di-vision Multiple Access (SDMA), and Time Division Multiple Access (TDMA). FDMAdivides the available frequency band into a number of subchannels and assigns thesubchannels to dedicated nodes which can transmit exclusively on their subchan-nels. It requires frequency synchronization, relatively narrow-band filters, and theability of a receiver to tune to the channel used by a transmitter [45]. In CDMA sys-tems, the narrow-band message signal is multiplied by a very large bandwidth sig-nal called the spreading signal. The spreading signal is pseudo-noise code sequencethat has a chip rate which is orders of magnitudes greater than the data rate of themessage. The receiver in CDMA needs to know a codeword used by the transmitter.


Each user operates independently with no knowledge of the the other uses. SDMAcontrols the radiated energy for each user in space. SDMA serves different usersby using spot beam antennas. These different areas covered by the antenna beammay be served by the same frequency or different frequencies. Sectorized antennasmay be thought of as a primitive application of SDMA [46]. Due to the high imple-mentation complexity, antenna complexity and/or sophisticated signal processingability [45], FDMA, CDMA and SDMA has not been considered as the main tech-nologies for WSN MAC protocols. However, TDMA has been utilized in industrialWSN since TDMA is able to provide a guaranteed access to the wireless channel andlow complexity requirement to transceivers and microcontrollers.

Demand assignment protocols: this type of protocols can be classified as cen-tralized and distributed protocols. In centralized protocols, nodes send out requestsfor bandwidth allocation to a central node that either accepts or rejects the requests.In case of successful allocation, a confirmation is transmitted back to the request-ing node along with a description of the allocated resource. The node can use theseresources exclusively. Resource deallocation is often done implicitly: when a nodedoes not use its time slots any more, the central node can allocate it to others. An ex-ample of distributed demand assignment protocols are token-passing protocols. Theright to initiate transmissions is tied to reception of a small special token frame. Thetoken frame is rotated among nodes organized in a logical ring on top of a broad-cast medium. Both of the two types of protocols require lots of energy consumptiondue to transceiver must be switched on most of the time. Therefore, they are notconsidered as appropriate protocols for WSN.

Random access protocols: they are also known as contention based protocols.ALOHA and CSMA are typical examples. The basic idea of Slotted ALOHA issimple: let a wireless sender transmit at the beginning of the next transaction slotwhenever they have packets to be sent. Slotted ALOHA exhibits poor performancebecause whenever one sender has a packet to transmit it does so without consid-eration of the others. CSMA improves Slotted ALOHA to transmit acyclic packets.The philosophy of CSMA is that when a sender generates a new packet, the channelis sensed, and if it is found to be idle, then the packet is transmitted. The chan-nel sense scheme is generally known as clear channel assessment (CCA) in the IEEEwireless standards. The advantages of a contention-based protocol include: easy im-plementation; full bandwidth being available to any node; and suitability for use indynamic networks without pre-scheduling. However, a contention-based protocolalso has drawbacks: real-time communication cannot be guaranteed; fairness cannotbe guaranteed because one node can occupy the medium for a long time; and thereceiver must be active for the channel sense mechanism; therefore, it is difficult todetermine the wake up time if the protocol allows sleep to save power. CSMA proto-cols are widely adopted in WSN protocols, while ALOHA protocols are also utilizedin some special cases, e.g., shared slots in WirelessHART and ISA-100.11a standards.

Considering the low energy consumption and resource constrained devices, thedesigns of MAC protocols for WSN generally focus on energy efficiency and lowcomplexity. Abdelmalik et al. summarize WSN MAC protocols which regard energyefficiency as the prime design driver in [47]. The classifications include protocols


Figure 2.3: An example of the preamble sampling technique [47]

with common active period, preamble sampling protocols, scheduled protocols andhybrid protocols.

Protocols with common active period: this type of protocols is an extension ofconventional type of random access or contention based protocols. Nodes work ina duty-cycling mode with active/sleep periods. During active periods, nodes accessto the wireless medium using contention based approaches. The typical protocolsinclude SMAC (Sensor MAC) [48] and IEEE 802.15.4. The latter will be discussedin the next subsection. SMAC is briefly illustrated as follows. The primary designgoal of SMAC is reducing energy consumption, meanwhile, it is also designed tosupport scalability and collision avoidance. Nodes are periodically enter active andsleep periods [49]. Nodes are locally time synchronized and neighboring nodes formvirtual clusters to share a schedule, i.e., a common sleep and active periods, whichis updated by a SYNC packet. Lacking of global synchronization, there are still col-lisions which are avoided by a carrier sense. In order to further reduce collisions(such as Hidden Terminal problem), SMAC utilizes request-to-send (RTS) and clear-to-send (CTS) prior to a series of short data packets transmissions and ACK. Besides,SMAC introduces a concept of message passing which fragment a long frame intoshort frames and transmit them in burst. The technique achieves energy saving byretransmitting corrupted short frames instead of a long frame, at the expense of un-fairness in medium access [49].

Preamble sampling protocols: in this approaches, a preamble sampling tech-nique shown in Fig. 2.3 is utilized to further increase the proportion of sleep periodsin a duty-cycling work mode. BMAC (Berkeley MAC) [50] and WiseMAC (WirelessSensor MAC) [51] are typical protocols. BMAC is the origin of MAC implementationof TinyOS which is widely adopted in academic research. BMAC improve energy ef-ficiency by accurately determine if the sensing channel is clear or not. As mentionedearlier, SMAC achieves collision avoidance by carrier sensing, which is realized byCCA. The common approach to implement CCA is to take single sample of receivedsignal strength (RSS). If the value is larger than the noise floor, the channel is busy.Otherwise, the channel is clear. BMAC searches outliers in a certain samples. If asample has significantly lower than noise floor during a sampling period, the chan-nel is clear. WiseMAC improves energy efficiency by reducing preamble length in


the regular preamble sampling technique [52], where a wake up preamble of sizeequal to the sampling period is transmitted prior to every data frame so as to ensurethe receiver is able to awake when data arrives [51]. WiseMAC enables every node tolearn the sampling schedule information of other nodes so that a transmitter knowsthe wakeup time of the receiver. It is therefore able to shorten the preamble lengthand save energy.

Scheduled protocols: this type of protocols is identical to the one of traditionalfixed assignment protocols.

Hybrid protocols combine the above protocols to achieve different objectives.ZMAC is a typical protocol in such category. ZMAC achieves high throughput andlow latency under low contention using a contention based access approach, andachieved high throughput under high contention using a fixed assignment approach[53]. Thus, ZMAC achieves a high channel utilization with variable traffic patterns.

As mentioned before, WSN in industrial automation, i.e., IWSAN, have real-timeand reliable communication requirements on design of MAC protocols. Petcharat etal. explores to what extent existing MAC protocols for WSN can meet timely andreliable communication requirements [40]. The authors utilize SMAC as a referencepoint to evaluate delay and reliability of reviewed MAC protocols. The authors drawsome conclusions as follows. Most existing WSN MAC protocols primarily focus-ing on energy consumption are unable to meet the requirement on both timely andreliable transmissions for mission critical applications. The authors addresses thatWirelessHART is able to guarantee end-to-end delay and improve end-to-end reli-ability. Besides, Burst algorithm [54] and GinMAC protocol [55] have mechanismsto deliver the delay and reliability bounds for mission critical applications. The au-thors also reveal that only WirelessHART among reviewed protocols is evaluated inpractical scenarios and the others are based theoretical studies which might be notrealistic due to lacking of evaluations in real application scenarios. WirelessHARTwill be illustrated later and the burst algorithm and GinMAC are briefly discussedas follows.

Burst algorithm introduces a new link-quality metric, Bmax, which is definedas the maximum number of time slots where packets transmission can fail due to aburst. After a long-term measurements (such as 21 days), links are classified into fourcategories: stationary links, asymptote-stationary links, epsilon-stationary links andnon-stationary links, in which lower Bmax means higher stationary. Non-stationarylinks should be avoided for real-time transmissions; Epsilon-stationary links can beused for some real-time applications with some probability of missing deadline; Sta-tionary and asymptote-stationary links can be used for hard real time applications,addressed by the authors. The solution shows a better performance than widelyused packet receipt rate. On top of that, the authors propose a least-burst-routeto produce latency bounds of the streams considering link bursts and interference.Burst algorithm requires a pre-deployment measurement in plants and links qualityis given based on the measurement, which is a limitation because of failing to captureshort-term link dynamics due to movable obstacles or others. Suriyachai et al. haveproposed GinMAC that considers timely and reliable data delivery by exclusivelyusing guaranteed time slots and providing deterministic communications [55].


The CSMA/CA protocols in general and MAC protocols in industrial automationstandards will be illustrated in detail in the following subsections.

2.4.2 CSMA/CA Protocols

IEEE 802.11 is a widely accepted standard which adopts single channel mode.The fundamental access method of IEEE 802.11 MAC is a distributed coordinationfunction (DCF) known as Carrier Sense Multiple Access with Collision Avoidance(CSMA/CA) protocol [56, 57]. Before transmitting a packet, a node operating inDCF scheme shall sense the channel to determine if another node is transmitting.If the channel is idle for a period of time equal to a distributed interframe space(DIFS), the node just starts transmitting. Otherwise, if the channel is busy, the nodedefers until the end of the current transmission. After the deferral, the node selectsa random backoff interval and shall decrement the backoff interval counter whilethe medium is idle (this is the collision avoidance feature of the protocol), to reducethe probability of collision with packets being transmitted by other nodes. In or-der to further reduce collisions (such as Hidden Terminal problem), DCF utilizes afour-way handshaking mechanism, that is, exchanging short frames (known as RTSand CTS) prior to data transmission and ACK. In addition, to avoid channel cap-ture, a node must wait a random backoff time between two consecutive new packettransmissions, even if the medium is sensed idle in the DIFS time.

DCF adopts an exponential backoff scheme. At each packet transmission, thebackoff time is uniformly chosen in the range (0, w − 1). The value w is called con-tention window, and depends on the number of transmissions failed for the packet.At the first transmission attempt, w is set equal to a value CWmin called minimumcontention window. After each unsuccessful transmission, w is doubled, up to amaximum value CWmax = 2mCWmin.

IEEE 802.11 was originally designed to offer high throughput to wireless com-munications without taking energy consumption into account. Besides, it requiresa high-performance MCU and a relatively high-complexity transceiver chip. There-fore, it is not considered suitable for applications of low power and low cost WSNs.

Inspired by IEEE 802.11 MAC, IEEE 802.15.4 MAC also employs CSMA/CA asthe fundamental access mechanism [2]. Compared with the former, CSMA/CA issimplified in IEEE 802.15.4, such as excluding the exchange mechanism of RTS andCTS control frames. Besides, some different schemes are adopted to support low-power mode, e.g., during the random backoff periods, nodes in the latter can entersleep mode instead of sending the channel; the coordinator in the latter may entersleep mode during the supported inactive portion of a superframe. IEEE 802.15.4protocol has been analyzed and evaluated by [58–60] in detail. A brief description ofthe IEEE 802.15.4 MAC shall be given below.

The IEEE 802.15.4 standard allows the optional use of a superframe structure.The superframe is bounded by network beacons sent by the coordinator and is di-vided into 16 equally sized slots. All transactions shall be completed by the time ofthe next network beacon. The beacons are used to synchronize the attached devices,


to identify the network, and to illustrate the superframe structure defined by a coor-dinator. The superframe can have an active and an inactive portion, as shown in Fig.2.4. The active portion of each superframe is composed of three parts: a beacon, acontention access period (CAP) and a contention free period (CFP). The beacon shallbe transmitted, without listen the channel or any backoff at the start of slot 0. TheCAP period just starts after the beacon. Devices communicate during CAP periodusing a slotted CSMA/CA mechanism. The CFP, if present, follows immediatelyafter the CAP and extends to the end of the active portion of the superframe. Thenetwork coordinator assigns so called guaranteed time slots (GTSs) in CFP to dedi-cated devices. Thus, there are no contentions for those devices to access the channelduring CFP. Up to 7 GTSs can be assigned to devices in a network.

The CSMA/CA algorithm in IEEE 802.15.4 is used before the transmission of dataor MAC command frames transmitted within the CAP. The IEEE 802.15.4 uses twotypes of channel access mechanism: Unslotted CSMA/CA ( known as beacon basedCSMA/CA) and slotted CSMA/CA (known as non-beacon based CSMA/CA).

Unslotted CSMA/CA: When a device wishes to transmit a packet, it shall detectthe channel using CCA after waiting for a random period. If the channel is idle, thedevice shall transmit its data. Otherwise, after the random backoff, the device shallwait for another random period before trying to access the channel again [2].

Slotted CSMA/CA: Beacon-enabled networks utilize slotted CSMA/CA mecha-nism. Unlike unslotted scheme, the backoff slots in the mechanism are aligned withthe start of the beacon transmission. Each time a device wishes to transmit dataframes during the CAP, it firstly locates the boundary of the next backoff slot, thenwaits for a random number of backoff slots. If the channel is busy, following thisrandom backoff, the device shall wait for another random number of backoff slotsbefore trying to access the channel again. Otherwise, the device can begin transmit-ting on the next available backoff slot boundary [2].

In both of the above cases, the CSMA/CA algorithm is implemented using unitsof time called backoff periods, where one backoff period shall be equal to a constant,i.e. aUnitBackoffPeriod (20 symbols) [2]. The CSMA/CA algorithm shall not beused for the transmission of beacon frames, acknowledgment frames, or data framestransmitted in the CFP.

During the inactive period, devices can enter a low power mode for saving en-ergy. One of the main considerations of the design of IEEE 802.15.4 CSMA/CA al-gorithm is to achieve energy efficiency. Energy consumption has attracted signifi-cant attentions in wireless sensor networks [61] and energy-efficient CSMA-basedmedium access control protocols have been well explored. But these protocols areunable to guarantee real-time transmissions, which is unacceptable in industrial ap-plications with stringent timing requirements [33, 62, 63].

As discussed above, IEEE 802.15.4 provides a GTS mechanism to allocate a spe-cific duration within a superframe for time-critical transmissions. The authors in [64–67] have proposed a series of adaptive scheduling or allocation mechanisms for GTSso as to achieve a low latency, improve bandwidth utilization or fairness for timecritical messages. Zdenek et al. [68] have utilized a time division cluster schedul-


Figure 2.4: Illustration of IEEE 802.15.4 superframe structure [2]

ing mechanism to meet the deadlines while minimizing the energy consumptionin beacon-enabled IEEE 802.15.4 network. Seong-eun et al. [69] have proposed areal-time offline message-scheduling algorithm which not only schedules periodicmessages in GTSs but also configures parameters of a superframe to meet timingconstraints. However, the standard and the above scheduling algorithms are basedon a CSMA/CA dominant and hybrid mechanism with a limited number of GTSslots.

Therefore, worldwide standards that meet the requirements in industrial au-tomation need to be developed. MAC protocols of recent industrial standards shallbe discussed as follows.

2.4.3 MAC Protocols in Industrial Standards

Industrial standards, WirelessHART, ISA-100.11a and WIA-PA, IEEE 802.15.4eleverage IEEE 802.15.4 physical layer with a low rate of maximum 250 kbps anda low implementation complexity for resource-constrained devices. They mainlyutilize TDMA mechanism to provide guaranteed access to the wireless medium. Anadaptive scheduling algorithm can effectively improve the QoS by means of delayoptimization or mitigation [70, 71]. The standards also adopt packet-level channelhopping to improve the reliability of individual wireless links by combating externalinterference and multi-path fading. In 2.4 GHz IEEE 802.15.4 radio, there are 16wireless frequency channels ranging from 11 to 26.

WirelessHART (IEC 62591) MAC uses the TDMA access mechanism combinedwith channel hopping [5]. IEEE 802.15.4 superframe is not supported by the Wire-lessHART, where time is divided into consecutive time slots. A time slot in Wire-lessHART is a time unit that allows packet transaction once, which is similar to IEEE802.15.4 GTS. Fig. 2.5 summarizes the WirelessHART packet format. A superframe inWirelessHART (called TDMA superframe and superframe refers to TDMA superframeunless otherwise statement in the rest of the thesis) is a collection of consecutive timeslots shown in Fig. 2.6. Link transmissions are scheduled in the superframe and anadaptive scheduling algorithm can effectively improve QoS by means of delay opti-mization or mitigation [70, 71]. WirelessHART devices in a network share a channelhopping sequence determined by a centralized device called network manager. A


Figure 2.5: Summary of WirelessHART packet format

Figure 2.6: WirelessHART time slot and superframe [5]

channel blacklisting feature is provided to restrict the number of hopping sequence.Each link containing a transmitter and a receiver shall be assigned the channel hop-ping sequence and switch a channel after a transaction.

ISA-100.11a (IEC 62734) MAC employs the same superframe structure. It sup-ports three channel hopping operating modes: slotted channel hopping, slow chan-


nel hopping and hybrid combinations of slotted and slow hopping [6]. Just likeWirelessHART, a centralized network manager is responsible to generate a hoppingpattern. In slotted channel hopping mode, a time slot in a superframe is assigneda dedicated channel and the next time slot shall use the next successive channel inthe hopping pattern. The hopping pattern is repeatable as time progresses. In slowhopping mode, multiple consecutive time slots are assigned a common channel. Fora given hopping pattern, the standard provides a mapping between channel num-ber in hopping pattern and MAC channel numbers. As applied to the 2.4 GHz DSSSIEEE Std 802.15.4 radio, channel numbers shall be limited to the range of 0 to 15,corresponding to IEEE Std 802.15.4 channel numbers 11 to 26.

WIA-PA (IEC 62601) MAC has a compatible IEEE 802.15.4 superframe structureshown in Fig. 2.4, with redefined functions for CAP, CFP and inactive period. TheCAP is used for packet transmission of device joining, intra-cluster management andretransmissions. The access method in the CAP is CSMA/CA mechanism defined inIEEE 802.15.4, which is different from WirelessHART and ISA-100.11a. Each WIA-PA time slot duration in CFP is configurable and compatible with IEEE 802.15.4 GTS.Except the sleep mode, intra- and inter-cluster communication is allowed during theinactive period. WIA-PA supports three channel hopping mechanisms: adaptivefrequency switch (AFS), adaptive frequency hopping (AFH), time slot hopping (TH)in which channel is changed per time slot. The channel hopping sequence is deter-mined by the network manager.

IEEE 802.15.4e MAC defines a MAC amendment to the existing standard IEEE802.15.4-2006 to better support industrial markets, as mentioned before. All motesin an IEEE802.15.4e network are synchronized and time is split into time slots, eachtypically 10 ms long. Time slots are grouped into a super-frame which continuouslyrepeats over time. Each device in the network obtains its schedule from a distributedscheduling algorithm. The schedule then instructs the device what to do in eachtime slot: send, receive, or sleep. Channel diversity is obtained by specifying, foreach send and receive slot, a channel offset. The same channel offset translates intoa different frequency on which to communicate at each iteration of the super-frame.The resulting channel-hopping communication reduces the impact of external inter-ference and multipath fading, thereby increasing the reliability of the network [13].

2.4.4 Open Issues

As mentioned in Chapter 1, there are different traffic requirements with differentcritical classes. For example, the three categories of data traffic, safety, control andmonitoring, have critical classes in descending order. ISA 100.11a, WirelessHARTand WIA-PA provide a limited service differentiation in MAC schemes. They sup-port four traffic categories which are defined from the highest priority to the lowestpriority as: command, process-data, normal and alarm. High-priority packets areallowed to access the medium prior to low-priority packets. The deterministic andsynchronous multi-channel extension (DSME) mechanism in IEEE 802.15.4e is oneof the important extensions to IEEE 802.15.4. DSME supports prioritized channelaccess by reserving specific DSME guaranteed time slots for high priority traffic.


However, both of the priority mechanisms do not mean that a high-priority packetat a device can immediately be sent out after its generation. Each device or link hasits own dedicated slot and an immediate transmission may occupy another device’sslot thus causing a high risk of collisions. Thus, a high-priority packet has to waitfor the next assigned or reserved slot after the generation of the packet, which canbe after a number of slots and which may be even longer in case of retransmissions.

Exceeding the required delay bound for unpredictable and emergency trafficcould lead to system instability, economic and material losses, system failure and,ultimately, a threat to human safety. Guaranteeing the timely delivery of the IWSANcritical traffic and its prioritization over regular traffic (e.g. non-critical monitoringtraffic) is a significant challenge. A priority based MAC protocol for IWSAN, there-fore, need to be developed.

Besides, another challenge for the IWSAN is that: non-compatible channel hop-ping patterns, routing protocols and upper-layer protocols in WirelessHART, ISA-100.11a, WIA-PA, IEEE 802.15.4e (supported by different global suppliers in themarket) may incur a poor performance regarding to coexistence and interoperabilityamong devices using different standards, although these standards use the same ra-dio in almost an identical way to get long battery life, guaranteed medium access forreal-time communication and avoidance of multipath fading via channel hopping.

2.5 TDMA Scheduling

As mentioned, scheduled MAC protocols assigns divided wireless bandwidth tonodes or links in a long term, and each node or link uses its own dedicated resourcewithout the risk of collisions. Thus, scheduled protocols are generally suitable forperiodic and high-load traffic. Industrial standards in industrial automation intro-duces scheduled protocols, such as TDMA, to provide guaranteed access or boundedlatency to the wireless medium in order to meet the real-time transmission require-ment. In addition, TDMA is attractive because - once the schedule is set up - there areno collisions, no overhearing, and minimized idle listening [47]. Therefore, schedul-ing algorithms play an important role for TDMA-based wireless networks.

2.5.1 Scheduling Problems

Scheduling algorithms are inherently designed for resource allocation problems.Examples are scheduling algorithms for meeting timing constraints in real-time op-erating systems and scheduling mechanisms for railway transportation. Schedulingproblems are not new in wireless networks. The early problems and solutions canbe traced back to the mobile radio system: users are scheduled by a base station ondifferent traffic channels depending on their traffic requirements and channel condi-tions [72]. Scheduling algorithms in wireless multi-hop is more challenging.

Existing TDMA scheduling approaches [73–77] define the goal of TDMA schedul-ing in finding the minimum number of slots required to schedule link transmissions.

2.5 TDMA Scheduling 27

In these papers, the authors reduce the number of slots by means of spatial reuse.As a consequence, conflict-free links can be assigned to the same slot. Neverthe-less, the presented algorithms do not account for inbound-outbound delay incurredby TDMA scheduling, given that certain inbound links are scheduled after their re-spective outbound links. Thus, minimum length schedules do not automaticallyguarantee a minimal end-to-end delay.

In [78], Djukic and Valaee introduce a general TDMA scheduling problem formulti-hop wireless networks. The authors derive a worst-case inbound-outbounddelay in terms of link transmission orders and discuss min-max scheduling delayoptimization based on a conflict-free TDMA schedules, using an improved Bellman-Ford shortest path algorithm to find optimal round-trip paths. The algorithms showgood performance properties for delay and bandwidth efficiency. The algorithms inthe paper mainly targets TDMA scheduling over IEEE 802.16 and IEEE 802.11s basedwireless networks. Huan Li et al. in [79] propose a message scheduling algorithm,which provides timeliness guarantees for multi-hop real-time transmissions for ateam of robots equipped with sensors. The main wireless technology is based onIEEE 802.11. A proprietary MAC method is proposed together with the schedulingalgorithm, instead of CSMA/CA based MAC. The TDMA-based scheduling prob-lems have been attracting researchers in both IEEE 802.16, IEEE 802.11s or IEEE802.11 based wireless network, and researchers in IEEE 802.15.4 based WSN. Al-though both of IEEE 802.x and IEEE 802.15.4 based scheduling problems have similarnetwork models and conflict models, the scheduling problems and solutions are dif-ferent because of different data transmission requirement and network topologies.The former normally has high data rates and large packets, thus, continuously sub-sequent slots need to be assigned to a single pair of transmitter and receiver. Thereare periodic data transmissions with low data rates and small packets in the lattercase so that each transaction only occupies a single slot.

In [80], Ergen and Varaiya present TDMA scheduling problem for WSN to de-termine the shortest length conflict-free assignment of slots in a superframe, dur-ing which the generated packets from each node reach their destination. The au-thors prove this problem to be NP-complete and the authors propose a level-basedscheduling algorithm to solve it.

The remainder of the section will discuss network model, wireless interferencemodel and scheduling algorithms in detail.

2.5.2 Network Model and Wireless Conflict Model

In order to solve the scheduling problems, the TDMA based network is nor-mally modeled as a directed connectivity graph G(V,E), where the vertices V ={v0, · · · , vn} are the set of nodes with v0 denoting the Gateway or Sink. The edgesbetween vertices E = {e1, · · · , em} represent wireless communication links. Theresearch community has only recently developed practical full-duplex radios [81].Therefore, the half-duplex radio is considered throughput the thesis in which a trans-mitter cannot transmit and receive at the same time.


Table 2.4: Notations of network model for scheduling algorithms

V vertices that represent a set of nodes in the network

E edges that represent wireless links

C edges that represent conflict links

G(V,E) directed connectivity graph that model the network

G(V,C) a graph that models the network with nodes and conflict links

G(V,E,C) a graph that model the network with nodes, links, and conflict links

Spatial reuse is one of the mechanisms used by scheduling algorithms to mitigateend-to-end delay in TDMA-based multi-hop networks. As a consequence of spatialreuse, conflict-free links can be assigned to the same slot, while links whose trans-missions may conflict with each other cannot be allocated to the same time slot. Twosources for wireless transmission conflicts can be distinguished, namely primary con-flict and secondary conflict [78, 80]. Primary conflict occurs when one node performsmore than one action in a single time slot, i.e., receiving and transmitting messages,or concurrently receiving from different transmitters. Secondary conflict can occur ifa receiver is within the radio range of multiple transmitters, but is solely interestedin one of them.

Therefore, a conflict graph is necessary to model. Let edges C = {c1, · · · , ck} ⊂ E

represent conflicting wireless links. Then, G(V,C) can be used to model the networkwith nodes and conflict links, and G(V,E,C) represents the network with nodes,links, and conflict links. The notations of the network model is shown in Table 2.4.

2.5.3 Scheduling Algorithms

Existing scheduling algorithms in WSN can be roughly classified into schedulingfor broadcast traffic and scheduling for unicast traffic according to different traffictypes. Data collection is a fundamental traffic type in WSN where each sensor nodeperiodically transmits packets containing measured or sensed data to the destinationnode, i.e., Sink or Gateway. In [47], the authors classify scheduling methods in thecontext of WSNs as: scheduling of links (which consist of wireless transmitter andreceiver pairs), scheduling of transmitter and scheduling of receivers. The category ismade according to which a scheduling approach assign a dedicated slot: each link,transmitter or receiver in a network. Since transmitter and receiver know exactlywhen to wake up in the first approach, this is the most energy efficient solution,which have been attracting lots of researchers.

In order to illustrate how a scheduling algorithm works, a classic scheduling al-

2.5 TDMA Scheduling 29

Table 2.5: Notations of network model for the level-based algorithm

L a set of tree levels; the tree level of a node is the depth of the nodein the tree

VL vertices that represent a set of virtual “nodes”; a set of nodes in asame tree level is regarded as a single virtual “node”

EL edges that represent a set of virtual “links” between virtual “nodes”

CL edges that represent conflict virtual “links”

G(VL, EL, CL) a virtual “graph” that model the network with virtual “nodes”, vir-tual “link”, and virtual conflict “links”

Algorithm 1 Construct a virtual “graph” consisting of virtual “nodes”, “links” andconflict “links”

Input:V , E, and n which is the number of levels in the tree.

Output:VL, EL, and CL

1: construct VL = {vL1, · · · , vLn}, in which each element represent a virtual “node”,i.e., a set of nodes in the corresponding tree level.

2: construct EL, in which each element is a virtual “link” between two adjacentvirtual “nodes” in VL.

3: for i← 1 to n do4: if ∃ (u, v) ∈ CL, satisfying node u is at level i and node v is at a level j which

is smaller than i. then5: add edge (vLi, vLj) to CL

gorithm as an example will be discussed in detail as follows. The algorithm, whichadopts the method of scheduling of unicast links, is called level-based algorithm pro-posed by Sinem et al. in [80] for data collection in WSN. It is the main comparisonreference for evaluation in the Paper III of the contributed publications. The algo-rithm descriptions [80] have been re-organized here. The concepts of virtual “nodes”,virtual “links” and a virtual “graph” have been introduced to differentiate them fromnodes in the networks, links between nodes and a graph consisting of nodes andlinks. A virtual “node” is a set of nodes with the same tree level (depth). The no-tations for the algorithm is shown in Table 2.5. The algorithm assumes that a treetopology is used for data collection. It has three parts. Firstly, Algorithm 1 classifiesnodes into different level sets L according to their depths in the tree, and constructa virtual “graph” by generating virtual “nodes” (VL), virtual “links” (EL) and conflictvirtual “links” (CL). Secondly, Algorithm 2 assigns colors to the virtual “nodes” (VL).Lastly, Algorithm 3 determines the slots for each color group until all nodes are able


Algorithm 2 Color assignment for the virtual “nodes” in the virtual “graph”

Input:VL, EL, and CL

Output:{(vL1, c1), · · · , (vLn, cn)}, where, ci ∈ {1, 2, 3, ...,M} and M is the number of col-ors.

1: order the “nodes” as {k1, k2, ..., kn}.2: for l← 1 to n do3: i← 14: while ∃ j assigned to color i, satisfying (j, kl) ∈ CL do5: i← i+ 16: assign color i to kl

Algorithm 3 Color assignment for nodes in the graph G(V,E)

Input:G(V,E), G(V,C), and color assignment for the virtual “nodes” with M colors

Output:schedule for nodes of G(V,E)

1: while at least one packet has not reached Gateway do2: for l← 1 to M do3: construct a temporary set SETs containing “nodes” which have a color s4: construct T , T ← ∅

5: for j ← 1 to ‖SETs‖ do6: find a nonconflicting set of nodes ∈ SETs(j) {a virtual “node” represents

a set of nodes.}7: T ← T∪ the nonconflicting set8: if T 6= ∅ then9: construct a temporary set SETos containing “nodes” not corresponding

to color s10: for each node k belonging to a virtual “node” ∈ SETos do11: if (k, j) 6∈ C, ∀ j ∈ T then12: T ← T ∪ k

13: assign current slot to set T

to send one packet to the sink.

2.5.4 Open Issues

The majority of existing TDMA scheduling approaches [58, 73–77, 80, 82–84] donot consider the effects of unreliable wireless links on scheduling algorithms. Linkfailures can result in schedules of broken order. Individual wireless links are inher-ently unreliable. Observations on real-platform testbeds with low-power wirelesssensor networks show that links have wide ranges of packet delivery ratio which

2.6 Routing Protocols in WSN 31

can vary significantly over time, even without intra-collisions or high portions ofexternal interference [11–13]. The dynamics of individual links are even more un-predictable in industrial environments, because of the human blockage, machineryand products obstacles.

Furthermore, the majority of existing TDMA scheduling algorithms do not con-sider the configurational overhead. A centralized scheduling mechanism for indus-trial applications is thus taken as an example to describe this issue. In central-ized scheduling, schedule requests come with topology and routing informationwhen sent to the sink. The sink then runs a centralized scheduling algorithm anddistributes the schedules to the sensors. Neighbors and routing information maychange very frequently because of the unreliable nature of the individual wirelesslinks and obstacles, thus generating heavy configurational overhead. This overheadin return increases the end-to-end delay.

2.6 Routing Protocols in WSN

The routing function in network layer is important for a multi-hop network. Therouting algorithms are essential used to determine good paths consisting of a seriesof routers from a source node to an end-to-end destination node. This section isnot intended to comprehensively discuss about routing protocols in WSN. Instead,previous milestone protocols in WSN will be studied in brief.

Due to the complexity and importance, routing algorithms have been attract-ing thousands of researchers in WSN. The routing algorithms can be classified intolink-state algorithms and distance-vector algorithms according to whether they arecentralized or decentralized [85].

Previous work on routing protocols in WSN addressed various objectives accord-ing to the specific applications. Flooding and gossiping protocols are early solutionsfor relaying data in sensor networks [86]. They do not need any routing algorithmsand topology maintenance. This type of solutions is particularly useful for relayingdata for small groups of mobile nodes. Geographic routing protocols are location-awareness solutions [87], which may combine energy awareness [88] for sensor net-works. Cluster-based hierarchical routing is also an important type for routing solu-tions in WSN. It influences the design of the cluster tree network architecture in IEEE802.15.4. Fig. 2.7 shows an example given by IEEE 802.15.4. Nodes are grouped intoseveral clusters. In each cluster, there is one coordinator providing synchronizationservices. Among these coordinators, only one of them can be selected as the overallcoordinator, which may have greater computational resource than any other nodes.A typical and well-known approach is Low-Energy Adaptive Clustering Hierarchy(LEACH) [89]. LEACH is proposed for building an energy-efficient and low-latencyarchitecture combining routing and MAC in remote monitoring applications. A dis-tributed self-organization technique and routing protocols are proposed for formingthe clusters, and intra-clusters and inter-clusters communications. TDMA is used forintra-cluster communications, while CDMA is utilized for inter-cluster communica-tions. Other cluster-based routing protocols include the Threshold sensitive Energy


Figure 2.7: An example of cluster tree network architecture in IEEE 802.15.4 [5]

Efficient sensor Network protocol (TEEN) [90], the Hybrid, Energy-efficient, Dis-tributed clustering protocol (HEED) [91] and so on. Directed diffusion is regarded asa milestone in data-centric routing research in WSN [86]. In order to save energy, dif-fusing data schemes are used to reduce complexity of routing. Based on the idea ofdirected diffusion, a Gradient Based Routing (GBR) [92] has been proposed. Gradi-ents in GBR are established by flooding some a type of information for a sink, called“interest” message, in the network and each node finds a minimum hops to the sink.There are a series of routing protocols which further develop gradient-based rout-ing such as GRAdient Broadcast (GRAB) [93]. Please see the routing survey articlesin [86, 94, 95] for more detailed reviews on routing algorithms in WSN.

Mobile Ad-hoc Networks (MANET) working group in IETF has contributed sev-eral well-known routing protocols for wireless multihop ad-hoc networks. Theseprotocols include: Ad hoc On-Demand Distance Vector (AODV) routing protocol(2003) [96], Optimized Link State Routing protocol (OLSR) (2003) [97], Topology Dis-semination Based on Reverse-Path Forwarding (TBRPF) (2004) [98], The DynamicSource Routing protocol (DSR) for Mobile Ad Hoc Networks for IPv4 (2007) [99].They can be classified as reactive/on-demand protocols and proactive/table-drivenprotocols. AODV and DSR are reactive distance-vector protocols, while OLSR andTBRPF are proactive link-state protocols. The MANETs have mainly been describedas [100]: an autonomous system consisting of mobile nodes; multi-hop dynamictopologies which may randomly and rapidly change at unpredictable times; band-width constrained, variable capacity link; energy constrained operation; Limitedphysical security. These characteristics fit some early WSN applications, thus, many

2.6 Routing Protocols in WSN 33

protocols in WSN “embrace” MANET routing protocols, while, in turn, WSN widelyextends the applications of MANET. For example, Zigbee adopts AODV as its mainrouting protocols. Nevertheless, the needs of considering realistic applications forthe research work of WSN in recent years, the initial vision changed. In most realis-tic applications such as industrial automation applications, most of wireless sensorsor actuators are static or with low mobility.

Most of routing protocols in WSN are evaluated in simulators or limited ex-perimental tests. There are a series of practical protocols which have been widelyexperimented in multitude of test-beds. MintRoute [101], Collection Tree Protocol(CTP) [102] and TinyRPL [103] have been adopted as de-facto routing protocols indifferent versions of TinyOS which is the first open-source operating system de-signed for WSN. CTP has been implemented in different test-beds and simulatorsand have been widely used in research, teaching, and in commercial products. Pa-per III and IV among contributed papers of this research work have used CTP as therouting protocol. Thus, a brief introduction will be given in this section.

The routing protocols in WSN have been well explored. Recent years, IPv6-basedWSN routing protocols have been attracting a lot of researchers [104] in this area.The IETF 6LoWPAN working group has started in 2007 to work on specifications fortransmitting IPv6 over IEEE 802.15.4 networks. On top of that, the IETF charteredROLL working group to standardize a link-independent IPv6 routing protocol forresource constrained devices [105]. The RPL (pronounced Ripple) [95] has been de-fined to build a robust topology over lossy links with minimal state requirements.RPL has been implemented in widely used open-source platforms such as TinyOSand Contiki [106].

Besides, as the size of network scale in IWSAN increases, emerging routing pro-tocols which satisfy real-time requirement in IWSAN become more and more sig-nificant. In [107], Yanjun Li et al. proposes a two-hop information based routingwhich maps packet deadlines to a velocity and can reduce packet deadline missratio. In [108], the authors propose a gradient routing with two-hop information,which combines a two-hop velocity-based routing algorithm in [107] and gradientrouting to reduce delays and energy consumption. In [109], Kan Yu et al. proposea controlled flooding based real-time routing scheme for some industrial control ap-plications.

2.6.1 Collection Tree Protocol

Collection Tree Protocol (CTP) [102], a well-known protocol in WSN, is distancevector based protocol designed for WSN.

The distance vector algorithm is iterative, asynchronous, and distributed routingalgorithm [85]. It is distributed in that each node without global information, receivesinformation from one or more of its neighbors, performs a calculation, and thendistributes the results to its neighbors. It is iterative in that this process continueson until no more information is exchanged between neighbors. The algorithm isasynchronous in that it does not require all of the nodes to operate in lockstep with


Figure 2.8: Illustration of the operation of CTP protocol

each other.

Let dx(y) be the cost of the least-cost path from node x to y. Then the least costsare related by the celebrated Bellman-Ford equation, namely,

dx(y) = minv{c(x, v) + dv(y)}, (2.1)

where the minv is taken over all of x’s neighbors. After traveling from x to v,if we then take the least-cost path from v to y, the path cost will be c(x, v) + dv(y).Since we must begin by traveling to some neighbor v, the least cost from x to y is theminimum of c(x, v) + dv(y) taken over all neighbors v.

CTP computes the routes from each node in the network to Sink in the network.CTP uses the following mechanisms to overcome the challenges in a highly dynamicwireless network. It uses adaptive beacon broadcast messages to form and maintain aspanning tree topology. An adaptive beacon mechanism realized by a so called Tricklealgorithm [110] is adopted. When topological inconsistencies arise, beacons are sentmore frequently [102]. Otherwise, the beaconing rate is decreased exponentially.Specifically, in the absence of topological changes, the beaconing interval is regularlydoubled until it reaches a maximum value which triggers only a few beacons perhour. Upon topological changes, the interval is reduced to allow for fast gradientre-convergence.

Fig. 2.8 illustrates the operation of CTP protocol. Every node maintains an esti-mate of the cost of its route to a collection point. The expected transmission count(ETX) is the default cost metric, but any similar gradient metric can work just as well.

2.7 Implementation of Communication Protocols in WSN 35

Figure 2.9: A typical commercial development stack for WSNs

A node’s cost is the cost of its next hop plus the cost of its link to the next hop: thecost of a route is the sum of the costs of its links. Collection points (Sinks) advertisea cost of zero. Each data packet contains the transmitter’s local cost estimate. Whena node receives a packet to forward, it compares the transmitter’s cost to its own.Since cost must always decrease, if a transmitter’s advertised cost is not greater thanthe receiver’s, then the transmitter’s topology information is stale and there may bea routing loop. Using the data path to validate the topology in this way allows aprotocol to detect possible loops on the first data packet after they occur.

2.7 Implementation of Communication Protocols in

WSN

The methods for implementation of communication protocols in realistic testbedcan be roughly classified into commercial development kits and open source. Fig. 2.9presents a typical commercial development kit for software protocol stack. A real-time operating system, PowerPac, based architecture with multi-processors supportand ARM Cortex-M3 based hardware constitute the test-bed platform. IAR Em-bedded Workbench [111] (one of the most commonly used integrated developmentenvironments for embedded systems) and JTAG debugging tool have been used for


programming and debugging. The ST Simple MAC in the figure is a commercialMAC protocol that realizes basic IEEE 802.15.4 CSMA/CA (which can be disabled)mechanism. As can be seen, the black box of the operating system and stack protocol,on the one hand, reduces developers’ workload, and, on the other hand, degradesexecution efficiency and flexibility. Two well-known open-source based operatingsystems in WSNs will be discussed in the following.

TinyOS is an event-driven open-source operating system designed for low powerand low cost wireless devices [14] (e.g., microcontroller: MSP430 with 48 kB of ROMand 10 kB of RAM; low-power radio chip: CC2420 compatible with IEEE 802.15.4).It has been widely adopted by thousands of researchers worldwide in wireless sen-sor network community. On the one hand, TinyOS provides a series of principles,techniques, software structures and mechanisms to achieve computationally effi-cient programming/coding on resource limited embedded devices. For example,the principle of minimizing resource use is able to achieve efficiently and flexiblyminimizing the RAM and code ROM. On the other hand, it provides code modulesto run on a range of hardware platforms (e.g., Telosb with MSP430 and CC2420). Thecode modules include schedulers, timers, power managements, hardware drivers,radio stacks, network protocols and so on. The CC2420 radio stack in TinyOS isnon-synchronized CSMA/CA based MAC protocol in practice.

A lot of researchers have been attracting to use TinyOS to develop protocols andcontribute their codes. There is 25,000 downloads per year in average during thelast decade [112]. For example, the Flooding Time Synchronization Protocol (FTSP)[113], a well-known multi-hop time synchronization protocol for WSNs, is a typicalcontribution from researchers outside the core developers of TinyOS community.Another example is Berkeley OpenWSN [17] which have primarily implementedtheir proposed communication protocols in TinyOS. Berkeley OpenWSN is an open-source stack intending to implement low-power wireless standards such as IEEE802.15.4e, 6LoWPAN, RPL and CoAP. The implementation of time synchronizationmodule for this research work has absorbed the methods in FTSP and OpenWSN.

TOSSIM is a default simulator in TinyOS. It emulates the behavior of underlyingraw hardware by replacing several low-level hardware components with softwareequivalents [18]. Thus, the transition from the simulation environment to a real plat-form is relatively easy. The use of TOSSIM has another advantage. Its radio modelhas the ability to capture the short-term link dynamics of low-power radio, by ac-curately simulating real-world 2.4 GHz environmental noise. It simulates this noiseusing the closest-fit pattern matching model [60]. TOSSIM inherently supports onesingle wireless channel.

Contiki is an another well-known open-source for WSN and recently it is an-nounced to support a wide range of smart objects [23] for Internet of Things. Itis built around an event-driven kernel and provides optional preemptive multi-threading that can be applied to individual processes [106]. The most outstand-ing contributions are designs of IPv6 stacks such as µIP [114], ContikiRPL [104] forresource-constrained devices.

Chapter 3

Summary of Contributed

Papers

This chapter summarizes the contributed papers by addressing the achievementsand limitations. Table 3.1 shows the objective, topics and my participation associatedwith the corresponding contributed papers. The detailed summary will be discussedas follows.

Paper I

PriorityMAC: A Priority-Enhanced MAC Protocol for Crit-ical Traffic in Industrial Wireless Sensor and ActuatorNetworks

In this article, a vital issue of IWSAN, namely, service differentiation for priorityof critical traffic over non critical traffic, is addressed in real-time industrial automa-tion applications. Exceeding the required delay bound for unpredictable and emer-gency traffic could lead to system instability, economic and material losses, systemfailure and, ultimately, a threat to human safety. However, guaranteeing the timelydelivery of the IWSAN critical traffic and its prioritization over regular traffic (e.g.,noncritical monitoring traffic) is a significant challenge. The paper proposes Priority-MAC, a Priority enhanced MAC protocol, designed for critical traffic in IWSANs,and the first priority enhanced MAC protocol compatible with IWSAN industrialstandards. We present the design, implementation, performance analysis and eval-uation of PriorityMAC.

This paper has four original contributions. Firstly, our protocol provides a servicedifferentiation in wireless medium access for traffic categories (TC1, TC2, TC3 andTC4) of different priorities. It utilizes the industrial standards, WirelessHART and

37

38 Summary of Contributed Papers

Table 3.1: Objective, topics and my participation associated with corresponding papers

Objective Topics Papers My participation

ServicedifferentiationforTDMA-basedwirelessmediumaccess

How to enableunpredictablecritical traffic totimely deliveryand to havepriority overreal-timeguaranteed non-or less-criticaltraffic?

Paper I

I am fully responsible for ideas,implementation and experiments intestbed; I am also responsible formost of problem description, perfor-mance analysis, simulation evalua-tion, experimental evaluation, writ-ing, and revisions according to com-ments from reviewers.

How to improvethe transmissionefficiency forburst acyclictraffic inWirelessHARTand ISA100.11abased IWSAN?

Paper III merely contributed to test-bed im-plementation and corresponding per-formance evaluation.

Paper V

I am fully responsible for ideas,implementation and experiments intestbed; I am also responsible for mostof problem description, experimentalevaluation and writing.

Adapt to linkdynamics forschedulingalgorithms

How to adapt tolink dynamicsfor schedulingalgorithms inrealisticenvironment?

Paper III

I am fully responsible for ideas,implementation and simulations inTOSSIM; I am also responsible formost of the theoretical analysis, evalu-ation, writing and revisions accordingto comments from reviewers.

Paper IV

I am fully responsible for ideas, im-plementation and experiments; I amalso responsible for most of problemdescription, performance evaluationand writing.

ISA100.11a, as a baseline and employs a novel medium access control scheme toenhance access for the critical and aperiodic traffic.

Secondly, we provide a theoretical analysis of average access delay and utiliza-tion of wireless resource for different traffic priorities, which closely matches withthe corresponding simulations. PriorityMAC achieves a high channel utilization

Summary of Contributed Papers 39

0 2 4 6 8 10 12 14 1610

0

101

102

103

Dela

y(m

s)

Time(hour)

deferred TC4 TC3 TC2 TC1

Figure 3.1: PriorityMAC experiment shows it is able to efficiently handle different categories

with different latency requirements.

and low latency under low transmission rates of periodic traffic, because of the highprobability in relation to the hijacking of idle slots for periodic traffic. It achieveslow latency for delay-sensitive and unpredictable traffic at the expense of a slight de-crease in channel utilization under high transmission rates of periodic traffic. This isbecause the high probability of deference or even damage of periodic traffic may re-sult in a decrease of channel utilization. The effects on channel utilization of Priority-MAC become negligible when the transmission probabilities of TC1 and TC2 aresmall, while PriorityMAC achieves a significant improvement in latency.

Thirdly, PriorityMAC is implemented using TinyOS and is evaluated on a testbedof 40 TelosB motes. Telosb mote uses a microcontroller of MSP430 with 48kB of ROMand 10kB of RAM and a IEEE 802.15.4-compliant low-power radio chip, CC2420.

Lastly, PriorityMAC achieves a significant reduction regarding the latency in ex-perimental evaluation. Fig. 3.1 shows a delay experiment of TC1, TC2, TC3, anddeferred TC4 (due to an arrival of a higher priority packet prior to TC4) within 16hours. The TC4 devices which transmit TC4 packets changed the data refresh inter-val every 2 hours during the experiment. The figure indicates that the proposed so-lution can efficiently handle different categories with different latency requirements.The experimental comparison with the priority access methods in the current indus-trial standards shows that PriorityMAC achieves a reduction in latency of 94% forthe highest priority traffic and 93% for secondary priority traffic, on average. Thereduction is achieved at the expense of only a 0.17% increase in third priority trafficaccess delay and a 0.19% deferring ratio from the lowest-priority packets.

Limitations: PriorityMAC supports four types of access methods concurrentlyoperating within the protocol. Each access method corresponds to one traffic cat-egory. From a theoretical standpoint, the traffic categories appear to be arbitrary.Furthermore, there is a limitation about the highest priority traffic, that is, no colli-sion of two or more of this type of packet is assumed.


Paper II

CCA-Embedded TDMA enabling Acyclic Traffic in In-dustrial Wireless Sensor Networks

In this article, we propose a CCA-Embedded TDMA scheme that improves thetransmission efficiency and system stability of a TDMA-based system that generatesburst acyclic traffic, such as the WirelessHART protocol and ISA-100.11a. A Markovmodel is provided to analyze the performance of CCA-Embedded TDMA. Further-more, we have implemented CCA-Embedded TDMA in a testbed composed of 10Telosb devices using TinyOS. I merely contributed to the test-bed implementationand the corresponding performance evaluation. Thus, the summary here only cov-ers this contribution.

To evaluate the performance of the proposed CCA Embedded TDMA scheme,we deployed 10 field devices and a gateway in an indoor environment. The field de-vices were deployed in a circle around the gateway with a distance of 2.5 m betweenthe gateway and field devices. All of the transmissions are on the same channel. Inthe start-up phase, all of the field devices are notified of the frame generation rateupon receiving the beacon frames. Then, each field device generates and transmits94-byte frames for 5 min during a shared transaction slot. For every device, if thecurrent frame has not been sent out, no new frame is generated. This design guaran-tees a single buffer system. The obtained results show that CCA-Embedded TDMAimproves the throughput compared with the WirelessHART MAC.

Limitation: The limited number of devices used in the experiment and the lackof multihop network scenarios are the main limitations of this article.

Paper III

SAS-TDMA: A Source Aware Scheduling Algorithm forReal-Time Communication in Industrial Wireless SensorNetworks

Scheduling algorithms play an important role for TDMA-based wireless sensornetworks. Existing TDMA scheduling algorithms address a multitude of objectives.However, their adaptation to the dynamics of a realistic wireless sensor networkhas not been investigated in a satisfactory manner. This is a key issue consideringthe challenges within industrial applications for wireless sensor networks, given thetime-constraints and harsh environments.

In response to those challenges, we present SAS-TDMA, a source-aware schedul-ing algorithm in this article. It is a cross-layer solution which adapts itself to networkdynamics. It realizes a trade-off between scheduling length and its configurationaloverhead incurred by rapid responses to routes changes. We implemented a TDMAstack instead of the default CSMA stack and introduced a cross-layer for schedul-ing in TOSSIM, the TinyOS simulator. TOSSIM makes the program code transition


� � � � � � � � � � � � � � ��

� �� !" �#�" �$%& ' ( ( ) * + , - . / 0 1 23 4 5 6 7 8 6 ) 9 : 5 6 * + , - ; 0 1 < / 0 1 2* ( ( 7 * + , - = ; 0 1 2

Figure 3.2: A comparison of nodes proportions with different PDR levels for SAS-TDMA algo-

rithm and level-based algorithm with the refresh interval of 3.1s.

between the simulation and real platform by only replacing a small number of low-level components. It also has the ability to capture the link dynamics by simulatingthe real-world noises. The evaluation in our work is thus close to the experiments ina real system.

Fig. 3.2 shows the performance comparison of the proposed solution with a clas-sic scheduling algorithm, the level-based algorithm. During the simulation, we de-liberately uses a heavy noise so that the PDR of each individual link was poor. Theretransmission attempts stopped when hitting an upper bound of delay. Nodes weresaid to have poor PDR level if PDR was below 30%, intermediate between 30 and90%, and good otherwise. The figure indicates that the performance of the level-based algorithm decreases by about 30% for good PDR compared with our solution.Numerical results show that the SAS-TDMA improves the quality of service for theentire network. It achieves significant improvements for realistic dynamic wirelesssensor networks when compared to existing scheduling algorithms with the aim ofminimizing the latency for real-time communication.

Limitations: There are still differences between TOSSIM simulation and the realplatforms. The implementation of SAS-TDMA in TOSSIM did not include the timesynchronization. Additionally, the proposed SAS-TDMA was evaluated in the net-work based on the CTP for constructing and maintaining a routing tree. The effectsof other routing protocols, such as RPL, on the performance of SAS-TDMA need tobe further investigated.


Paper IV

Distributed Data Gathering Scheduling Protocol for Wire-less Sensor Actor and Actuator Networks

In this paper, we present a novel cross-layer scheduling protocol for data gath-ering transmission. In WSAN, there is typically a short-length sensor data with arelatively large overhead in each packet. Data gathering transmission is able to im-prove the QoS of the whole network by means of efficiently scheduling packets trans-mission and combining packets from multiple sources and then forwarding a newpacket. There are two key issues which have not been dealt with in a satisfactorymanner for the previous work involving data gathering transmission for sensor net-works. Firstly, most of the solutions have not considered the case involving topologychanges and retransmission in realistic wireless networks. Wireless sensor and ac-tuator networks undergo frequent topology changes due to physical environmentalchanges, node join, node failures, and time-varying channel conditions. An indi-vidual wireless link is inherently unreliable. It has been observed from using real-platform testbeds with a low power wireless network that links have a wide rangeof packet reception ratios, which can vary significantly over time even without intra-collisions and heavy external interference. It is even worse for industrial applicationsin harsh environments as both humans and machinery alter the RF environment. Inaddition, the case involving retransmission due to unreliable and asymmetric wire-less links has to be considered when designing the protocols. Secondly, most of theprevious gathering scheduling algorithms have not considered another importantproblem: the scheduling configuration overhead. The previous work needs to main-tain one-hop and two-hop neighbors. Each node has to construct its competitor setfrom two neighbors and has to make decisions regarding its schedule by itself.Wecall these algorithms as node dominant decision scheduling. They only consider thedelay after scheduling. However, the scheduling procedure should reduce the trafficload and delay.

A parent-dominant decision scheduling with collision free algorithm is proposedto adapt the dynamics of links in a realistic low-power wireless network. In ad-dition, the protocol reduces the scheduling traffic through maintaining distributedlightweight conflict-links tables. We have implemented the protocol in TinyOS andTelosb hardware. The results show that the protocol has robustness to the topologychanges and it has significant improvements to reduce the traffic load.

Limitations: The experiment has been carried out in an office environment, where24 Telosb motes were on the 2nd, 3rd, 4th and 5th floors in the building. We have col-lected the schedules of each node every 8 seconds through a single hop or multiplehops. However, other node deployments have not been investigated in the exper-imental evaluation. Additionally, performance comparisons with more schedulingprotocols need to be further investigated.


Paper V

Joint Routing and MAC for Critical Traffic in IndustrialWireless Sensor and Actuator Networks

This paper proposes Delay Bounded Routing (DBR) and extends the Priority-MAC to the network layer by means of the joint DBR and the PriorityMAC, designedfor routing critical traffic in IWSAN. Exceeding the required delay bound for unpre-dictable and emergency traffic could lead to system instability, economic and mate-rial losses, system failure and, ultimately, a threat to human safety. Guaranteeingthe timely delivery of the critical traffic and its prioritization over regular traffic (e.g.non-critical monitoring traffic) is a significant challenge. Therefore, we present thedesign, implementation and evaluation of DBR and PriorityMAC. DBR and Priority-MAC are implemented in TinyOS and evaluated on a testbed of Telosb motes. Theexperimental results indicate that our protocol achieves a significant improvementwith regards to the end-to-end delivery latency compared to the current industrialstandards.

Limitations: This paper lacks of a theoretical analysis on multi-hop end-to-enddelay performance. Additionally, a comparison with other routing protocols on topof PriorityMAC is not presented.

44

Chapter 4

Conclusions and Future Work

4.1 Conclusions

The emerging technology of industrial wireless sensor and actuator networkshas initiated a paradigm shift in industrial automation applications. However, suchwireless solutions have been introducing new challenges as well. The overall aim ofthe research project is to propose solutions to solve vital challenges such as real-time,service differentiation, adaption to link dynamics, security, wireless coexistence andetc. . The objective of this research work has been to design algorithms and pro-tocols to enhance service differentiation for TDMA-based wireless medium accessand adapt to link dynamics for scheduling algorithms on top of real-time commu-nications in IWSAN, and to develop a prototype to evaluate and demonstrate po-tential of proposed solutions. In order to achieve the objective, the thesis proposes aprotocol framework for adaptive real-time communication in IWSAN. The protocolframework mainly consists of proposed algorithms and protocols in five contributedarticles.

Firstly, the solutions in Paper I, Paper II and Paper V have been proposed to en-hance service differentiation for TDMA-based wireless medium access in IWSAN.Paper I proposes PriorityMAC, a Priority enhanced Medium Access Control proto-col. To the best of our knowledge, this is the first priority-enhanced MAC protocolcompatible with industrial standards for IWSAN. Paper V proposes Delay BoundedRouting to extend the PriorityMAC to network layer by joint DBR and the Priority-MAC, designed for routing critical traffic in IWSAN. The experimental results in-dicate that the solutions efficiently handles different traffic categories with differ-ent latency requirements, thereby achieving a significant improvement in the deliv-ery latency compared with the current industrial standards. The current industrialstandards provide a limited service differentiation for different traffic categories inmedium access control. Based on the schemes in these standards, Paper II proposes aCCA-Embedded TDMA scheme that improves the transmission efficiency for burstacyclic traffic. The analytical, simulation and experimental results show that the

45

46 Conclusions and Future Work

solution can efficiently increase the throughput and reduce the expected delay com-pared with WirelessHART.

Secondly, scheduling algorithms on top of real-time communications have beenproposed to adapt to link dynamics in IWSAN in Papers III and IV. Paper III presentsSAS-TDMA, a Source-Aware Scheduling algorithm which uses a cross-layer solu-tion to adapt to link dynamics in realistic environment. Paper IV further proposes anovel distributed scheduling protocol for data gathering transmission. It is also ableto adapt the dynamics of links in a realistic low-power wireless network. The pur-pose to adapt to link dynamics for scheduling algorithms significantly differentiatesthe contributions in the two papers from ones in most of state-of-the-art schedulingalgorithms articles. Numerical results show that the solutions achieve significantimprovements for realistic dynamic wireless sensor networks when compared to ex-isting scheduling algorithms with the aim to minimize latency for real-time commu-nication.

Lastly, a test-bed consisting of about 100 Telosb and Micaz devices has been builtup with a software stack. I have implemented the above proposed protocol frame-work in the stack and evaluated the proposed solutions in the test-bed.

4.2 Future work

Future work will deal with some specific improvements for the proposed proto-cols and algorithms. Firstly, collisions among highest-priority packets from nodesshared a medium can be solved in a smarter manner for PriorityMAC. Furthermore,SAS-TMDA and DBR need further evaluations in real platforms and comparisonswith other routing protocols such as ROLL RPL. Thirdly, the proposed protocolframework combining PriorityMAC, adaptive routing algorithms and cross-layerscheduling algorithms will be further evaluated in industrial harsh environment.

Furthermore, new challenges, such as lack of compatibility among the industrialstandards for industrial automation applications, require novel ideas and technolo-gies. For example, the dynamic spectrum access concept promoted by technologiessuch as cognitive radio systems might promote next-generation wireless technolo-gies to solve the practical issues in a much more satisfactory manner. The resource-constrained IP-based technologies can also promote convergence solutions from atechnique standpoint.

Last but not least, the low-power and resource-constrained wireless technologycombining Internet of Things will bring more new opportunities and challenges forthe future research.

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