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HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY SCHOOL OF INFORMATION AND COMMUNICATION TECHNOLOGY ──────── * ─────── THESIS SUBMITTED FOR PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF ENGINEER IN INFORMATION TECHNOLOGY ENVIRONMENT MONITORING SYSTEM BASED ON INTERNET OF THINGS FOR GREENHOUSE Author: Nguyen Khoi Nguyen Class ICT-55 Supervisor: Dr. Ngo Quynh Thu HANOI 05-2015

MultiPath in WSN

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introducce the multipath protocols

Text of MultiPath in WSN

  • HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY

    SCHOOL OF INFORMATION AND COMMUNICATION TECHNOLOGY *

    THESIS

    SUBMITTED FOR PARTIAL FULFILLMENT OF

    THE REQUIREMENTS FOR THE DEGREE OF

    ENGINEER

    IN

    INFORMATION TECHNOLOGY

    ENVIRONMENT MONITORING SYSTEM

    BASED ON INTERNET OF THINGS FOR

    GREENHOUSE

    Author: Nguyen Khoi Nguyen

    Class ICT-55

    Supervisor: Dr. Ngo Quynh Thu

    HANOI 05-2015

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 2

    REQUIREMENTS FOR THE THESIS

    1. Student information

    Student name: Nguyen Khoi Nguyen

    Tel: 0986209900 Email: [email protected]

    Class: ICT-55 Program: ICT

    This thesis is performed at: Network and Communication TechnologyLab, Room 901, B1

    Building, Hanoi University of Science and Technology

    From 24/02/2015 to 24/05/2015

    2. Goal of the thesis

    Design an environment monitoring system for Greenhouses model using Wireless Sensor Network over Internet of Things.

    Improve the system's performance by using enchanted multi-path RPL.

    3. Main tasks

    Study the characteristic of particular plants in Vietnam.

    Study the concept of Precision Agriculture and deployed Greenhouses in the world.

    Study the concept of Wireless Sensor Network over Internet of Things, RPL and multi-path RPL.

    Design the Greenhouse based on Wireless Sensor Network over Internet of Things, apply RPL multi-path.

    Analyze the results and evaluate the system's performance.

    Propose recommendation for future works.

    4. Declaration of student:

    I Nguyen Khoi Nguyen - hereby warrants that the Work and Presentation in this thesis are performed by myself under the supervision of Dr.Ngo Quynh Thu.

    All results presented in this thesis are truthful and are not copied from any other work.

    Hanoi, 24/5/2015 Author

    Nguyen Khoi Nguyen

    5. Attestation of the supervisor on the fulfillment of the requirements of the thesis:

    Hanoi, 29/5/2015

    Supervisor

    Dr. Ngo Quynh Thu

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 3

    ACKNOWLEDGEMENT

    I would like to thank my advisor Dr. Ngo Quynh Thu, Department of

    DataCommunication and Computer Networks, School of Information

    andCommunication and Technology, for accepting to supervise my graduation

    thesis,and for providing me with research background related to Precision

    Agriculture and Wireless Sensor Network.

    Special thanks to my classmate, my friend, Le Manh Nien, with whom I have

    worked with since the very first days on various projects. It was a pleasure working

    with you in an interesting and highly motivated atmosphere and to profit from

    group discussion. I hope you will success with your own research.

    I also want to thank Mr. Le Quan and your thesis about RPL protocol, as well

    asyour RPL simulation implementation. Without your system, I could not complete

    my research.

    Last, but not least, I am especially grateful to my family and my friends who

    haveencouraged me during the research. I am also thankful to everyone had

    supported me to overcome any difficulties and complete this research successfully.

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 4

    TM TT NI DUNG N TT NGHIP

    Internet of Things v ang l 1 trong nhng xu th pht trin mi trong lnh vc

    Cng ngh thng tin. Trong , mng cm bin khng dy l mt nn tng khng th

    khng nhc n. Mng cm bin khng dy m ra nhng hng nghin cu v ng

    dng mi trong lnh vc ty bin khng dy. Mt trong nhng ng dng in hnh i vi

    cc h thng mng cm bin khng dy l kim sot v o c cc yu t mi trng trong

    nng nghip. Bng vic s dng nhng nt cm bin tch hp kh nng thu thp thng s

    mi trng, chng ta c th thit lp 1 h thng gim st v iu khin nhng yu t nh

    hng n s pht trin ca cy trng.

    Vit Nam, h thng nng nghip thng minh cha thc s c u t v ch trng

    do nhng hn ch v cng ngh cng nh hiu qu kinh t cha c kim chng. Tuy

    nhin, trong nhng nm gn y, bin i kh hu c nhng tc ng khng nh n

    nng nghip ti Vit Nam. ng thi, nhng thnh cng nht nh t nhng m hnh nh

    knh v nng nghip chnh xc trn th gii cho thy y l 1 hng i ha hn cho

    nng nghip Vit Nam trong tng lai.

    Trong cc m hnh mng cm bin khng dy, vi in hnh rng buc nng lng

    thp, thi gian s dng di, RPL ang l giao thc nh tuyn c s dng rng ri v

    cho hiu nng cao. Tuy nhin, bn thn RPL vn c nhng hn ch ca n, c th k n l

    kh nng cn bng nng lng thp v qu trnh khc phc li mt nhiu thi gian. Hu

    qu ca vic ny l s mt gi tin trong qu trnh truyn d liu, khin cho hiu nng ca

    ton b h thng b gim, tin cy ca d liu khng cao.

    n ny tp trung vo 2 cng vic chnh: thit k m hnh kim sot cc yu t mi

    trng da trn mng cm bin khng dy, ph hp vi nhng bi ton thc t Vit Nam

    v p dng giao thc truyn tin a ng da trn RPL ci thin hiu nng h thng.

    nh gi hiu nng, n m phng h thng da trn nhng tiu chun ca IoT, vi

    nhng ci t tng ng trn thit b tht.

    Kt qu m phng cho thy h thng t hiu qu v nng lng cng nh m bo

    tin cy ca d liu. ng thi, vic p dng giao thc truyn tin a ng cng cho

    thy hiu qu trong vic ci thin hiu nng h thng, vi t l nhn gi tng t 2% n 4%

    v t hiu sut cao trong cn bng nng lng.

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 5

    ABSTRACT OF THESIS

    Internet of things has been a trend in Information Technology for a few year. And its

    most notable application is Wireless Sensor Network(WSN). WSN, with the help of

    Internet of things, has opened up a brand new development and application area. One of

    which is environment monitoring and control in agriculture, or Precision Agriculture. By

    using the network of wireless nodes with embedded sensors which can sense their

    surrounding environment, we can establish a system to measure and control the paramters

    affecting the plants.

    In Vietnam, Precision Agriculture is still a new concept due to limitation in

    technologies as well as doubts in its effectiveness. However, global climate changes have

    greatly and badly affect agriculture in Vietnam. Moreover, many successful application of

    Precision Agriculture in the world show that this is a promising way of development in

    agriculture in Vietnam.

    In a wireless sensor network, which typically a lossy and lower powered one, RPL is

    proven to be very effective and is a routing protocol of choice of many WSN. However,

    there are still flaws within RPL, most notable is that RPL does not take into consideration

    the energy level the system as a whole and the repair process can be considered time

    consuming. This results in the the loss of package and overall, decrease the system's

    performance.

    This thesis focus on 2 main tasks: design a greenhouse model to monitor environment

    information based on the technologies of Wireless Sensor Network over Internet of things

    and apply multi-path RPL to the performance of system. For evaluation, this thesis include

    a simulation based on Internet of things technology, with the configuration paramenters

    closest to real world devices.

    The simulation results show the the system's effectiveness and trustworthy. Moreover,

    by applying the multi-path RPL, the system's performance is improved: package delivery

    rate go up by 2% to 4% and the system archives better energy balance.

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 6

    TABLE OF CONTENTS

    REQUIREMENTS FOR THE THESIS .......................................................... 2

    ACKNOWLEDGEMENT ................................................................................. 3

    TM TT NI DUNG N TT NGHIP.............................................. 4

    ABSTRACT OF THESIS .................................................................................. 5

    LIST OF FIGURES ........................................................................................... 8

    LIST OF TABLES ............................................................................................. 9

    LIST OF ABBREVIATIONS.......................................................................... 10

    PART I. PROBLEM STATEMENT AND SOLUTION ORIENTATION 12

    CHAPTER I. Introduction .......................................................................... 12

    I. Precision Agriculture and Greenhouse model ........................................ 12

    II. The concept ........................................................................................... 17

    III. Problem statement ................................................................................ 24

    PART II. RESEARCH RESULT ................................................................... 26

    CHAPTER I. The design of multipath RPL .............................................. 26

    I. Faster Local Repair ................................................................................. 26

    II. Energy Load Balancing: ........................................................................ 28

    III. ELB-FLR .............................................................................................. 32

    CHAPTER II. GreenHouse desgin and data acquisition requirements . 35

    I. Flowers and advantages of environment control system ........................ 35

    II. Greenhouse design................................................................................. 37

    III. Data acquisition requirements .............................................................. 39

    IV. Types of sensors and controlling parameters in greenhouse ............... 45

    CHAPTER III. System simulation ............................................................. 47

    I. OMNeT++ .............................................................................................. 47

    II. System simulation ................................................................................. 47

    III. OMNet++ project structure .................................................................. 48

    CHAPTER IV. Performance Evaluation ................................................... 49

    I. Network setup ......................................................................................... 49

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 7

    II. Result analysis ....................................................................................... 50

    CHAPTER V. Conclusion and future works ............................................. 56

    References ......................................................................................................... 57

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 8

    LIST OF FIGURES

    Figure 1: Basic construction of sensor node ...................................................... 14

    Figure 2: Wireless sensor network ..................................................................... 14

    Figure 3: Typical Greenhouse and remote control ............................................. 15

    Figure 4: Environment control system for Greenhouse model .......................... 16

    Figure 5:Un-beacon CSMA ............................................................................... 20

    Figure 6: FLR data forwarding .......................................................................... 27

    Figure 7: FLR package reception ....................................................................... 28

    Figure 8: ELB DIO processing .......................................................................... 30

    Figure 9: ELB data forwarding diagram. ........................................................... 31

    Figure 10: ELB-FLR data forwarding ............................................................... 33

    Figure 11: ELB-FLR package reception ............................................................ 34

    Figure 12: Idea temperature range of some flowers .......................................... 35

    Figure 13: Idea humidity range of some flowers ............................................... 36

    Figure 14: Photophilic characteristic (surveyed from 40 kind of flowers) ........ 36

    Figure 15: One of typical Greenhouse deployment ........................................... 37

    Figure 16: typical of small field ......................................................................... 38

    Figure 17: design for small size field ................................................................. 38

    Figure 18: design for normal size field .............................................................. 38

    Figure 19: design for large size field.................................................................. 39

    Figure 20: Effect of temperature on major physiological processes of plants ... 40

    Figure 21: End-to-end delay............................................................................... 52

    Figure 22: Packet delivery rate ............... ! .

    Figure 23: Residual Energry .............................................................................. 55

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 9

    LIST OF TABLES

    Table 1: IoT layers and characteristic ................................................................ 18

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 10

    LIST OF ABBREVIATIONS

    Abbreviation Phrase

    ACK Acknowledgement

    ADC Analog to Digital Converter

    CSMA Carrier Sense Multiple Access

    CSMA/CA Carrier Sense Multiple Access / Collision Avoidance

    DAG Directed Acyclic Graph

    DAO Destination Advertisement Object

    DIO DODAG Information Object

    DIS DODAG Information Solicitation

    DMR DAG-based multipath routing protocol

    DODAG DAG-based multipath routing protocol

    ELB Energy Load Balancing

    FLR Faster Local Repair

    GDP Gross Domestic Product

    GH GreenHouse

    IANA Internet Assigned Numbers Authority

    ICMP Internet Control Message Protol

    IEEE Institute of Electrical and Electronics Engineers

    IETF Internet Engineering Task Force

    IoT Internet of Things

    IP Internet Protocol

    IPV6 Internet Protocol version 6

    MAC Media Access Control

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 11

    MTU Maximum Transmission Unit

    OF Objective Function

    OSI Open Systems Interconnection

    PA Precision Agriculture

    PHY Physical Layer

    RAM Random Access Memory

    RDC Radio Duty Cycling

    RF Reduce-Function

    ROLL Routing over low-power and lossy network (IETF WG)

    RPL IPv6 Routing Protocol for Low-power and Lossy

    Networks

    TCP Transmission Control Protocol

    UDP User Datagram Protocol

    WSN Wireless Sensor Network

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 12

    PART I. PROBLEM STATEMENT AND SOLUTION ORIENTATION

    CHAPTER I. INTRODUCTION

    I. Precision Agriculture and Greenhouse model

    I.1. Precision Agriculture

    The concept of precision agriculture has been around for some time now.

    Blackmore et al., in 1994 [1] defined it as a comprehensive system designed to

    optimize agricultural production by carefully tailoring soil and crop management to

    correspond to the unique condition found in each field while maintaining

    environmental quality. Its acceptance in the United States of America has been

    formally recognised by the drafting of a bill on PA by the US Congress in 1997 [2].

    The early adopters during that time found precision agriculture to be unprofitable

    and the instances of implementation of precision agriculture were few and far

    between. Further, the high initial investment in the form of electronic equipment for

    sensing and communication meant that only large farms could afford it. The

    definiton of PA is: an integrated information- and production-based farming

    system that is designed to increase long term, site-specific and whole farm

    production efficiency, productivity and profitability while minimizing unintended

    impacts on wildlife and the environment [2].

    Precision Agriculture refers to a set of technologies that introduce the concept

    of local variation into the large-scale mechanization, which is essential to large

    fields [3]. With the determination of soil, air conditions and plant development,

    these technologies can lower the production cost by fine-tuning seeding, fertilizer,

    chemical and water use, and potentially increasing production and lowering costs.

    These can be achieved through the approach of agricultural control and

    management based on direct chemical, biological and environmental sensing. In

    order to increase crop yield, improve quality, regulate the growth period and

    improve the economic efficiency, the optimum condition of crop growth is realized

    when analyzing these factors obtained by this system. Environment control system

    is very complex and needs to execute different processes: automatic monitoring,

    information processing, real-time control and online optimization. The development

    of environment measurement and control system has made considerable progress in

    the developed countries, and reached the multi-factors comprehensive control level,

    but if we introduce the foreign existing systems, the price is very expensive and

    maintenance isnt convenient. WSN is a network of small sensing devices known as

    sensor nodes or motes, arranged in a distributed manner, which collaborate with

    each other to gather, process and communicate over wireless channel about some

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 13

    physical phenomena. The sensor motes are typically low-cost, low-power, small

    devices equipped with limited sensing, data processing and wireless communication

    capabilities with power supply. WSN can form an useful part of the automation

    system architecture in modern control system. Wireless communication can be used

    to collect the measurements and to communicate between the centralized control

    and the actuators located to the different parts of this system. Wireless Sensor

    Networks (WSN) plays a major role in this approach.

    The Precision farming system has the following parts:

    Sensing agricultural parameters.

    Identification of sensing location and data gathering.

    Transferring data from crop field to control station for decision making.

    Actuation and Control decision based on sensed data.

    I.2. WSN technology

    Wireless Sensor network, or Low power and lossy network, is a network of

    small sensing devices known as sensor nodes or motes, arranged in a distributed

    manner , which collaborate with each other to gather, process and communicate

    over wireless channel about some physical phenomena. Their structure and

    characteristics depend on their electronic, mechanical and communication

    limitations but also on the requirements of the specific application. One of the most

    important network limitations is energy conservation. Wireless sensors operate on

    limited power sources therefore, their main focus is on power conservation through

    appropriate optimization of communication and operation management. Several

    analyses of energy efficiency of sensor networks have been realized and several

    algorithms that lead to optimal topologies for power conservation have been

    proposed. Inside WSN, the sensor motes are typically low-cost, low-power, small

    devices equipped with limited sensing, data processing and wireless

    communication capabilities with power supply. WSN provides a bridge between

    the real physical and virtual worlds. Furthermore, using WSN, people are allowed

    he ability to observe the previously unobservable at a fine resolution over large

    spatio-temporal scales. WSN can be used for many different applications range,

    from military implementations in the battlefield, to environmental monitoring [4], in

    health sectors[5], as well as emergency responses and various surveillances[5].

    WSN is consisted of numbers of elements, called sensor node. The main duty

    of each sensor node is monitor parameters are temperature, humidity, pressure,

    power-line voltage, and vital body functions etc. Each of them contains a

    transducer, microcomputer, transceiver and power source, as shown in Figure 1.

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 14

    ADC PROTOCOLS

    MICRO PROCESSOR

    MEMORY

    SENSOR UNIT

    TRANSCEIVER

    POWER UNIT

    SENSING COMPUTING COMMUNICATION

    Figure 1: Basic construction of sensor node

    There are 4 main components, they are:

    The transducer generates electrical signals based on sensed physical

    effects and phenomena.

    The microcomputer processes and stores the sensor output.

    The transceiver transmits and receives radio signals, and power source

    provides electricity to these devices.

    The size of these devices is usually very small and powered by either

    battery, energy scavenging like solar cells or mains powered.

    The significant impact of the WSN is to make prominent concept of IoT real

    life. The collaboration of two provide better environmental monitoring, energy

    savings, smart grids, more efficient factories, better logistics, better healthcare.

    Figure 2: Wireless sensor network

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 15

    I.3. Greenhouse model

    One of applications deployment of PA in particular is Greenhouse (GH) model.

    Greenhouse is a kind of place which can change plant growth environment, create

    the best conditions for plant growth, and avoid influence on plant growth due

    to outside changing seasons and severe weather[6] [7]. In a GH, there may be a

    different structure of the crop in different stages of its growth. As per the actual

    conditions of the green house and the requirements of the crop at a different

    location in Green House, the application is expected to control acuter like pump,

    valve, carton slider and fans etc. For greenhouse measurement and control

    system, in order to increase crop yield, improve quality, regulate the growth

    period and improve the economic efficiency, the optimum condition of crop growth

    is obtained on the basis of taking full use of natural resources by changing

    greenhouse environment factors such as temperature, humidity, light, CO2

    concentration. Greenhouse measurement and control system is a complex system, it

    needs to various parameters in greenhouse automatic monitoring, information

    processing, realtime control and online optimization. The development of

    greenhouse measurement and control system has made considerable progress

    in the developed countries, and reached the multi-factors comprehensive

    control level, but if we introduce the foreign existing systems, the price is very

    expensive and maintenance isnt convenient.

    Figure 3: Typical Greenhouse and remote control

    Crop growth is mainly influenced by the surrounding environmental

    climatic variables, the amount of water and the fertilizers supplied by irrigation.

    Greenhouse is ideal for cultivation of proper crop, in which climatic and

    fertilization variables can be controlled to allow an optimal growth and

    development of the crop.

    As the climate and fertilization are independent issues, they have different

    control problems. The exact need of nutrients and amount water for different

    crop species can be very well controlled, by automated machine which works on

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 16

    collected data. The amount of water and fertilizers require to the plant is a

    function of climate environmental conditions on which growth of the crop is

    depended. So that greenhouse crop production is a complex issue[8].

    Figure 4: Environment control system for Greenhouse model

    The Climatic Control Variables are the dynamic behaviour of the greenhouse.

    Microclimate is a combination of physical processes involving energy transfer

    (which includes radiation and heat) and mass balance (which includes water

    vapour fluxes and CO2 concentration). This system depends on the outlet

    environmental conditions, architecture of the greenhouse, performance of the

    control actuators and variety of crop. Proper ventilation and heating are the

    main way of controlling green house climate.

    From the paricular needs, the general design and operation of GH must satisfies

    these requirements:

    Continuously work for long time.

    Auto repair when error occurs.

    High sustainability: System must work in harsh condition.

    High performance: The packet delivery rate need to be as high as

    possible.

    Energy constraint.

    Flexible for various requirements.

    Low cost, easy to maintain, expand.

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 17

    II. The concept

    II.1. Internet of Things

    The internet, from small local network in small university, has growth into

    universe, ubiquitous network used regularly and now approaching up to 3 billion

    users worldwide[9]. With internet, individual and groups were allowed to connect

    and communicate with each other. Over years, many of new services, protocols

    were added and internet are becoming more complete. As the Internet of routers,

    servers and personal computers has been maturing, another revolution has been

    going on The Internet of Things (IoT). The term IoT had been in discussion since

    1991, but it is not until 1999 when Kevin Ashton proposed[10], in the fields of

    industrial system. The Internet of Things represents a vision in which the Internet

    extends into the real world embracing everyday objects. Physical items are no

    longer disconnected from the virtual world, but can be controlled remotely and can

    act as physical access points to Internet services. An Internet of Things makes

    computing truly ubiquitous a concept initially put forward by Mark Weiser in the

    early 1990s[11]. This development is opening up huge opportunities for both the

    economy and individuals. However, it also involves risks and undoubtedly

    represents an immense technical and social challenge.

    The Internet of Things vision is grounded in the belief that the steady advances

    in microelectronics, communications and information technology we have

    witnessed in recent years will continue into the foreseeable future. In fact due to

    their diminishing size, constantly falling price and declining energy consumption

    processors, communications modules and other electronic components are being

    increasingly integrated into everyday objects today.

    The scale of IoT is already estimated to be immense, with potential of trillions

    of devices becoming IP-enabled. As a result, it mandates for every devices to be

    IPv6-ready, which offers an extremely large space address that can assign to every

    devices in contrast with IPv4. And, it also need a new set of ICMPv6 and

    mechanism to send those packaged in order to construct and make WSN works.

    In our system, we proposed a communication stack based on ContikiOS. This

    design is widely used in WSN systems:

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 18

    OSI Layer IoT Layer IoT Technology Testing system

    Application Application CoAP, CoAPs Client - Server

    Transport Transport UDP UDP

    Network

    Net layer

    ICMP

    IPv6

    RPL, IPsec

    IPv6

    RPL

    Adaption

    layer

    6LoWPAN

    [12][13] 6LoWPAN

    Data link MAC layer 802.15.4 MAC

    Un-beacon mode

    CSMA

    RDC layer (none) ContikiMAC [14]

    Physical PHY layer 802.15.4 PHY Framer802.15.4

    cc2420 driver

    Table 1: IoT layers and characteristic

    II.1.1. Physical layer

    We use IEEE 802.15.4 frame format. With the simulated hardware of choice is

    cc2420. The CC2420 is a true single-chip 2.4 GHz IEEE 802.15.4 compliant RF

    transceiver designed for low power and low voltage wireless applications. CC2420

    includes a digital direct sequence spread spectrum baseband modem providing a

    spreading gain of 9 dB and an effective data rate of 250 kbps. Key features:

    250kbps 2.4GHz IEEE 802.15.4 Chipcon Wireless Transceiver

    8MHz Texas Instruments MSP430 microcontroller (10k RAM, 48k Flash)

    Integrated ADC, DAC, Supply Voltage Supervisor, and DMA Controller

    Integrated onboard antenna with 50m range indoors / 125m range outdoors

    Integrated Humidity, Temperature, and Light sensors

    Ultra low current consumption

    Fast wakeup from sleep (

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 19

    amount of time to do its work and then go back to sleep to save energy. Such thing

    can be done by implementing a Radio Duty Cycling design ContikiMAC in this

    case. ContikiMAC uses only asynchronous mechanisms, no additional signaling

    messages, nor package headers. ContikiMAC packages are link layer frame.

    ContikiMAC has a significantly more power-efficient wake-up mechanism that

    previous one. This is achieved by precise timing through a set of timing constraints.

    ContikiMAC use periodical wake-ups to listen for packet transmission. If a

    possible signal is picked, a node will stay a little longer trying to decode the signal.

    Unicast is done by having the sender continuously send out message until an

    acknowledgement response. In case of broadcast, the process is identical to unicast,

    but instead of stop when ack received, the sender keeps sending out message the

    whole wake-up time.

    II.1.3. Mac layer

    This layer is responsible for dertemining who is allowed to access the media at

    any time. For wired devices, a CSMA with collision detection is used since it is

    very easy to detect collision before hand in a wired network. However, it is nearly

    impossible to do that with wireless devices, a CSMA with Collision advoidance

    (CSMA/CA) is used instead. The typical CSMA mode used in IoT is un-beacon

    mode.

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 20

    Figure 5:Un-beacon CSMA

    II.1.4. Network layer

    As we mentioned before, there would be billion of devices connected to the

    internet in the near future. And the world is already run out of addresses for Ipv4.

    Therefore, adapting to a new Internet Protocol (Ipv6) is an absolute requirement for

    systems in future. However, while there is no problem in using Ipv6 with a PC or

    smartphones, it is much more difficult to fully utilize Ipv6 in case of embedded

    NB = 0,

    BE = macMinBE

    Delay for

    random(2BE - 1) unit

    backoff periods

    Perform CCA

    Channel idle?

    NB = NB+1,

    BE = min(BE+1, aMaxBE)

    NB>

    macMaxCSMABackoffs

    ?

    Failure Success

    Un-slotted CSMA

    Y

    Y

    N

    N

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 21

    small devices. The problems lie in these devices' low-powered, memory-limited

    characteristic as Ipv6 requires much more memory space compared to Ipv4.

    According to the IEEE 802.15.4, the standard MTU size is 128 bytes, that is

    without the security. If security is turned on, there would be only 80 bytes left for

    MAC payload. A UDP/IPV6 header already occupy 48 bytes at least, which left us

    with only 32 bytes for our data. The 6LoWPAN comes to the rescue here as an

    adaption layer. The new standard proposed by 6LoWPAN helps carry Ipv6

    packages over 802.15.4 link. It defines a Mesh Addressing header to support sub-IP

    forwarding, a fragmentation header to support IPv6 minimum MTU necessary,

    which is 1280 bytes. And by using link-local address, it reduces a significant

    amount of length.

    II.1.5. Transport layer

    In a WSN, which is also typically a Lossy and Low-Powered Networks (LLNs),

    saving energy is the most important task. And also take into consideration that there

    is not a clear proposal for reliable transport, the use of User Datagram Protocol

    (UDP) and retransmission control mechanism at application layer propose a good

    trade-off between enery cost and reliability. In contrast to TCP, UDP uses a simple

    connectionless transmission model with a minimum of protocol mechanism. It has

    no handshaking dialogues, and thus exposes any unreliability of the underlying

    network protocol to the user's program. There is no guarantee of delivery, ordering,

    or duplicate protection. UDP provides checksums for data integrity, and port

    numbers for addressing different functions at the source and destination of the

    datagram.

    II.1.6. Application layer

    This system implements a simple Client-Server program, in which the Client

    send data about surrounding environment to Server. The Client will be sensor

    modules periodically sensing and forward data to base station (Server). The Server

    is an appilcation installed on base station (DODAG root), it is reponsible for

    initilization and maintainence of DODAG root. The server will always listen to

    Client in a predefined port and store the collected data.

    II.2. IPv6 Routing Protocol for Low-power and Lossy Network

    RPL [9][10] is a de-facto standard routing protocol entirely defined for IPv6

    WSNs. It is a proactive, distance vector routing protocol, currently under

    specification by the ROLL working group of the IETF. RPL is designed to be a very

    flexible protocol in the sense of providing a standard of few basic mechanisms,

    which form the smallest common denominator or of functionality on different WSN

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 22

    applications can agree. Variety of extensions has been provided to tailor RPL

    framework to the particular requirements. In this chapter, the RPL is briefly

    explained with assumption of only one physical network and one root with no

    downward routing provided.

    RPL constructs and maintain network as a directed acyclic graph (DAG), which

    can be divided into several destination-oriented DAG (DODAG). And, this

    DODAG can be considered as a logical routing topology over physical network. An

    objective function (OF) [15]defines how routing metrics, optimization objectives,

    and functions to calculate rank as well as compare neighbor with aspect of rank.

    The rank of a node is relative distance of this node toward the base station. It may

    be built on node-quality (hop-count, residual energy, etc) or link-quality (expected

    transmission number, delay transmission time, etc).

    The RPL routing protocol specifies a set of new ICMPv6 [16]control messages

    to construct DODAG and to aid communication between root and source node. A

    RPL Control Message is identified by a code, and composed of a base that depends

    on the code, and a series of options. Most RPL Control Message has the scope of a

    link. The only exception is for the DAO/DAO-ACK messages in non-storing mode,

    which are exchanged using a unicast address over multiple hops and thus uses

    global or unique-local addresses for both the source and destination addresses. For

    all other RPL Control messages, the source address is a link-local address, and the

    destination address is either the all-RPL-nodes multicast address or a link-local

    unicast address of the destination. The all-RPL-nodes multicast address is a new

    address with a requested value of FF02::1A (to be confirmed by IANA)

    In accordance with [16], the RPL Control Message consists of an ICMPv6

    header followed by a message body. The RPL Control message is an ICMPv6

    information message with a requested Type of 155 (to be confirmed by IANA).

    Within scope of this paper, we do not consider downward routing, hence, only

    two kinds of message are involved, they are:

    DODAG Information Solicitation (DIS) - code field is 0x00 (to be

    confirmed by IANA) - is used to solicit DIO message from neighbor, it

    acts as an initial strobe for a nearby DODAG.

    DODAG Information Object (DIO) - code field is 0x01 (to be confirmed

    by IANA) - is issued by DODAG root, in order to construct a DODAG.

    DIO message contains: DODAG information (InstanceID, Version,

    DODAGID immutable, only root node can modify) and nodes rank.

    RPL Terminology

    The terminology is used within the scope of RPL, and is excerpted from [17]:

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 23

    DAG (Directed Acyclic Graph): a directed graph having the property that all

    edges are oriented in such a way that no cycles exist. All edges are contained

    in paths oriented toward and terminating at one or more root nodes.

    DAG root: a node within the DAG that has no outgoing edge. Because the

    graph is acyclic, by definition all DAGs must have at least one DAG root and

    all paths terminate at a DAG root.

    Destination Oriented DAG (DODAG): a DAG rooted at a single destination,

    i.e. at a single DAG root (the DODAG root) with no outgoing edges.

    DODAG root: the DAG root of a DODAG. The DODAG root may act as a

    border router for the DODAG, and in particular it may aggregate routes in

    the DODAG, and may redistribute DODAG routes into other routing

    protocols.

    Rank: a node's Rank defines the node's individual position relative to other

    nodes with respect to a DODAG root. Rank strictly increases in the Down

    direction and strictly decreases in the Up direction. The exact way Rank is

    computed depends on the DAG's Objective Function (OF). The Rank may

    analogously track a simple topological distance, may be calculated as a

    function of link metrics, and may consider other properties such as

    constraints.

    Objective Function (OF): defines how routing metrics, optimization

    objectives, and related functions are used to compute Rank. Furthermore, the

    OF dictates how parents in the DODAG are selected and thus the DODAG

    formation.

    DODAGID: the identifier of a DODAG root.

    DODAG Version: a specific iteration ("Version") of a DODAG with a given

    DODAGID.

    Version: a sequential counter that is incremented by the root to form a new

    Version of a DODAG. A DODAG Version is identified uniquely by the

    (InstanceID, DODAGID, Version) tuple.

    DODAG parent: a parent of a node within a DODAG is one of the

    immediate successors of the node on a path towards the DODAG root. A

    DODAG parent's Rank is lower than the node's.

    DIO: DODAG Information Object

    DIS: DODAG Information Solicitation

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 24

    II.3. Multi Path

    RPL routing algorithm has been proven its efficiency as a lightweight rounting

    algorithm in Wireless Sensor Network. However, there are still much to consider as

    well as room for improvements. Let us take a look at some properties of RPL and

    WSN to make it more efficient:

    Load balancing: RPL normally doesn't consider about nodes' energy level.

    RPL determines its route mostly by hop count and/or rank quality. This

    would easily leads to unbalanced route: a node will be chosen as a parent too

    much that its energy ran out quickly. Where as the second best route, even

    only a liitle worse than the best route here, is never chosen unless the best

    route is broken.

    Maintainace energy usage: RPL itself provides a mechanism to quickly

    repair itself in case of broken link by the use of ICMPv6. This, even with

    flexible trickler timer algorithm, still cost a lot in term of package count. And

    of course this will also cost nodes' power.

    Three enchanted methods have been proposed: Energy Load Balancing (ELB),

    Faster Local Repair (FLR) and a combination of both (ELB-FLR) to be integrated

    into RPL. As the name suggest, ELB take into consideration not only rank quality /

    hop count but also energy level of the node. Therefore, the route path taken will be

    distributed evenly. FLR, on the other hand, designed to solve the problems of

    having to send ICMPv6 everytime we need to update a node's parent list. The nodes

    will now consider other nodes with the same rank, called sibling nodes, in addition

    to only parent nodes (nodes with higher rank). We will go into details of each

    enchantment in the next chapter.

    III. Problem statement

    Over the past few years, many scenarios of Precision Agriculture have been

    research, and many models of Greenhouse with environment monitoring system

    were designed. However, these designs has various open issues:

    The pratical problem: The Greenhouse monitoring system has to specify

    which environment variables needed to control and how frequently the

    system has to control; which kind of fields and plants will be growth.

    Studies must specify how much can environment variables affect the plants.

    The performance of Greenhouse monitoring system: Since the data collected

    from wireless sensor network needed to be as much as possible. Usually, a

    WSN has package loss based on its size, the larger the system, the higher

    package loss. We see a package loss ratio of up to 15% in our set up. The

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 25

    package delivery rate can still be improved by applying enchanment

    methods to the original RPL.

    Energy and system's lifetime: WSN in Greenhouse does not require a strictly

    energy requirement, that is, usually the sensors node is constantly powered

    and will not die easily. However, an energy saving and balancing solution

    still needed to improve the overall performance and nodes' lifetime.

    From the background concept and problems above, my thesis will focus on

    design greenhouse models suitable for Vietnam environment

    andapplyingRPL-based multi-path protocol for improving Greenhouse

    environment monitoring performance of WSN based on Internet of Things

    For more details, the thesis will considers these terms:

    Studies about plants, especially flower in Hanoi and Dalat, which focus

    on their characteristic which depends on environment parameters.

    Studies about the environment parameters, how they can affect the

    plants.

    Studies about the Greenhouse model, design the Wireless Sensor

    Network for Greenhouse which satisfy the real lifes requirements.

    Apply the multi-path solution into existing RPL-routing algorithm to

    improve the performance of the system.

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 26

    PART II. RESEARCH RESULT

    CHAPTER I. THE DESIGN OF MULTIPATH RPL

    I. Faster Local Repair

    Originally, when there's a route failure in RPL, a node needs to send DIS

    message and wait for DIO message. This phase took a lot of time. Moreover, if the

    packet queue is not empty, DIO message will be delayed to be sent on later time.

    Another problem is that this local repair consumes a lot of energy. The more local

    repair triggered by a node, the faster it runs out of energy. FLR overcomes this

    problem by considering sibling nodes, which are neighboor nodes having the same

    rank. A node should store those sibling nodes in its routing table as back-up nodes.

    In case of broken route, these back up nodes will be used, thus reduce the cost of

    having a local or even worse, a global repair.

    I.1. DODAG construction

    In the beginning, all sensor nodes are awake and have their transceiver in listen

    mode in order to receive the network construction message (DIO).

    Step 0: This stage is triggered only when the base station (BS) constructs

    DODAG information, which is a unique tuple (InstanceID, Version,

    DODAGID) plus its rank.

    Step 1: BS initializes DODAG information (InstanceID, Version,

    DODAGID) and its self-rank. It encapsulated this information in DIO

    message and multicast the message toward all its neighbors.

    Step 2: Upon reception of DIO, sensor node determines whether or not the

    DIO message should be processed, and records the newest DODAG

    information (InstanceID, Version, DODAGID), considers rank of the

    neighbor to put in parent list if possible, and modifies its rank if needed.

    Step 3: If the rank is equal to self-rank, put neighbor into siblings-list.

    Step 4: It changes the rank field of original DIO message, and multicasts to

    its own neighbor

    Step 5: Whenever a sensor node receives a DIO message, it repeats step 2

    and step 3.

    Step 6: After a pre-defined interval, if sensor node has not received any DIO

    message, it fires DIS message in order to solicit DIO message from its

    neighbor.

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 27

    At the end of this stage, each node has a parent list, and the best rank parent is

    selected as preferred parent.

    I.2. Fast Local Repair mechanism

    The steps of FLR will be as follow:

    It considers the sibling list, and only triggers FLR when this list is not empty.

    Otherwise, trigger a normal local repair or costly global repair.

    It promotes all its siblings to become its parents in parents-list.

    Clear the siblings-list.

    Self increase its rank by RPL minimum hop rank increment.

    Figure 6: FLR data forwarding

    By following these rules, a node having broken path can quickly having a new

    parent nodes without the needs of multicasting DIS and waiting for DIO. This

    should greatly reduce end-to-end delay as well as energy usage.

    Moreover, by self-increase its rank, that node becomes the child of all its

    sibling node. Only then, the receiver should know that the broken route node is no

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 28

    longer a candidate for either its parent or sibling nodes, and remove routing

    information of that broken node from its routing table.

    Figure 7: FLR package reception

    II. Energy Load Balancing:

    The main idea is to use an energy-awareness Objective Function, and energy-

    awareness parent switching to make the next-hop determination more precise, light-

    weight load-balancing solution. We will next go the details of ELB.

    II.1. DODAG construction:

    Step 0: This stage is triggered only when the base station (BS) constructs

    DODAG information, which is a unique tuple (InstanceID, Version,

    DODAGID) plus its rank.

    Step 1: BS initializes DODAG information (InstanceID, Version,

    DODAGID) and its self-rank. It encapsulated this information in DIO

    message and multicast the message toward all its neighbors.

    Step 2: Upon reception of DIO, sensor node determines whether or not the

    DIO message should be processed, and records the newest DODAG

    information (InstanceID, Version, DODAGID), considers rank of the

    neighbor to put in parent list if possible, and modifies its rank if needed.

    Step 3: It changes the rank field of original DIO message, and multicasts to

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 29

    its own neighbor

    Step 4: Whenever a sensor node receives a DIO message, it repeats step 2

    and step 3.

    Step 5: After a pre-defined interval, if sensor node has not received any DIO

    message, it fires DIS message in order to solicit DIO message from its

    neighbor.

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 30

    Figure 8: ELB DIO processing

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 31

    At the end of this stage, each node has a parent list, and the best rank parent is

    selected as preferred parent.

    II.2. Energy-awareness objective function

    Normally, a node will select a preferred parent nodes based on hop count / rank

    quality. Therefore, there is a high chance that a node will be used too much and

    quickly ran out of energy. To solve this problem, ELB use an objective function that

    not only taken hop-count but also the residual energy-level of the nodes. The

    detailed formula of this objective function is as follow:

    1. We consider 1 hop has a valued of 100. Denoted RankInc = 100.

    2. The rank of root is equal to RankInc.

    3. Each node has its own energy level calculated as:

    EnergyLevel(node) = ResidualEnergy (node )

    MaxmimumEnergy (node) * 100

    4. The hop count (minimum number of hop needed to forward a package

    to the DODAG root) is calculated as:

    Hop(node) = Rank (node)

    RankInc

    5. Finally, the rank of a node is calculated as:

    Figure 9: ELB data forwarding diagram.

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 32

    Rank(node)=(Hop(parent)+1)*RankInc EnergyLevel(node)

    II.3. Energy-awareness parent switching

    An energy-awareness load balancing is provided for the whole network by

    switching a node's prefered parent on every transmisstion turn. That is, a node's

    parents having the same hop count and energy level should be evenly chosen so that

    no parent node is exploited. The least recently used parent node is always

    prioritized to be selected.

    II.4. Summary

    ELB aims to provide an energy-awareness load balancing in a wireless sensor

    network. It is ensured that all of the parent nodes of a sensor will in turn be chosen

    as preferred parent by take into consideration a node's residual energy. Therefore, it

    results in a load balancing in term of energy. Also, the lifetime of the whole

    network should be improved as well, since every best-rank parents are switched turn

    by turn.

    III. ELB-FLR

    This methods aim to take advantages from both of previous enchanment. ELB

    defined the term "rank" a little different than FLR. In ELB, rank is calculated by

    hop-count and energy level. Therefore when FLR take places, these nodes having

    the same hop-count but different energy level is not considered as siblings. Thus,

    the number of sibling nodes to be used as back-up is greatly reduced. The term

    sibling nodes need to be redefined as follow:

    Siblings = neighbor with the same hop count

    With this definition of sibling nodes, FLR can still work perfectly when it

    comes to dealing with broken route. The sibling nodes can still be promoted to

    parent nodes. Only then, ELB can take place and choose a suitable parent node

    based on energy-level. This will not only helps reducing end-to-end delay but also

    prolonging network's life.

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 33

    Figure 10: ELB-FLR data forwarding

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 34

    Figure 11: ELB-FLR package reception

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 35

    CHAPTER II. GREENHOUSE DESGIN AND DATA

    ACQUISITION REQUIREMENTS

    I. Flowers and advantages of environment control system

    Vietnam, as known as a agriculture country, owns a large farming industry

    which contributed about 74% of 2014s GDP[18]. Within agriculture, the

    cultivation area holds major density. However, the changes of global climate from

    nearly years caused significant impact in cultivation.

    The bonsai and flowers farming industry, from the past few years, raised from

    small and individual area into a large, high profit area. There are about 15 thousans

    herta used to grow flowers, distributed in area around Red river, Cuu Long river,

    Dalat and Hanois suburban [19].

    Figure 12: Idea temperature range of some flowers

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 36

    Figure 13: Idea humidity range of some flowers

    Figure 14: Photophilic characteristic (surveyed from 40 kind of flowers)

    Unlike paddy, corn, and other food plants, flowers can only growth under given

    conditions, depending on what kind the flower is. Furthermore, only high

    quality flowers can give high value. Since the quality of products depends

    much on the environments effect, the used of environment monitoring system

    is necessary to ensure the quality and productivity.

    0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

    Carnation

    Gerberas

    Gerberas (2)

    chrysanthemums

    gladiolus

    lilies

    Rose

    Phalaenopsis orchids

    Bell flowers

    Lyly

    Humidity (percentage)

    Flo

    wer

    s

    Weak light, 10%

    Normal light, 40%

    Strong light, 35%

    Very Strong light, 10%

    Unknown, 5%

    Weak light Normal light Strong light Very Strong light Unknown

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 37

    II. Greenhouse design

    Greenhouse models for Precision Agriculture have already been developed in a

    lot of countries. These greenhouse usually comes with different size and design to

    meet particular requirements. In Vietnam, Precision Agriculture and Greenhouse

    model was deployed few years ago, and primarily placed in Dalat, where farmer

    growth high quality and high value flowers.

    Figure 15: One of typical Greenhouse deployment

    These system focus on the automation farming method: auto open/close roof,

    auto irrigation system, etc... but hasnt focus on the environment control system yet.

    From the section above, we known that the flowers depend a lot on the environment

    parameters, so the desgin of Greenhouse in this thesis will mention on the

    implementation of the environment control system: how many sensors should we

    need, how we populate these nodes.

    By careful observation of greenhouses in Vietnam as well as taking Vietnam's

    economic circumstances, we propose 3 types of Greenhouse: small size, medium

    size and large size.

    II.1. Small field

    With the size that smaller than 20x20m, small field usually suitable for the use

    of home. It offers a low cost, easy to maintainence solution for home business. The

    figure 16 below captured the typical small size field, which place on rooftop of

    apartment. The GH model for this kind of field is actually simple too. Farmers only

    need to use one sensor node if the range of this node is large, or two nodes in case

    of smaller cover range sensor, and one node for base station. We also do not need to

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 38

    implement WSN and RPL in this situation due to the simply structure of the system.

    The figure 17 describe the design for this size of field.

    Figure 16: typical of small field

    Figure 17: design for small size field

    II.2. Medium field

    Medium field is the field with size about 50m width and 20m height. This type

    of greenhouse is most suitable for medium business and can be deployed in urban

    area. The number of sensors needed in this set up is up to 10 sensors depends on the

    coverage range of each sensor. WSN and RPL is applicable for this design,

    however, with this kind of greenhouse, the performance is very high and does not

    require any more enchantment (100% package delivery rate).

    Figure 18: design for normal size field

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 39

    II.3. Large field

    The most common field size in Vietnam is about 150x50m. Most of family

    agriculture cooperations in this city have this large size. In this case, we devide this

    flat into 24 grids, each has a size of 13.2mx13.2m. Each grid is populated by 3

    sensor and The sensors are placed at about 6m from each other. The base station is

    placed at the shorter edge. The number of sensor is calculated as follow:

    Ns = Nc 2 + [(fw 1) + ((Nc fw) (1 / fw) 1) + ((Nc fw) (1 1 / fw)

    2)] [20]

    where: Ns is the number of sensors, Nc is the number of grid and fw is the

    length of the garden.

    Figure 19: design for large size field

    In this setup, the technology of IoT and RPL are put to the test. They already

    show a reasonable performance (up to 85% package delivery rate) but there still

    room to improve. We will discuss the improvement in the enchanted RPL compares

    to original RPL in the next chapter.

    III. Data acquisition requirements

    III.1. Effect of natural parameters into plants

    From the above section, we can conclude that, by controlling these natural

    parameters, we can guarantee and improve the quality of plants. To control these

    stuffs, first we need to measure and collect the data from nodes, but how often

    should we need to collect the data ? This situation should be carefully consider

    because choosing the suitable degree of measurement could enhance the

    performance of the whole system and reduce the power consumption of each

    sensors.

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 40

    To find the suitable answer for this question, we study on how frequent that

    these conditions change their value, and the mechanism that plant use to react with

    the changes.

    III.1.1. Temperature

    Temperature has the massive effect on plants. Suitable air temperature can

    enhance the speed of photosynthesis, nutrition absorption and nutrition exchange

    inside plants. Plants can growth within wide range of temperature, and each one has

    the lowest bound and highest bound of temperature, where this plant can stop all the

    inside process if the environment temperature exceed these bounds.

    Figure 20Effect of temperature on major physiological processes of plants [21] [22]

    The direct impact of temperature into plants happens when plants live outside

    their temperatures range:

    Cold damage: With in low temperature, the leaf could be sere, or shed. The

    tree try to minimize its metabolism, then there is no chance for flower to

    bloomed.

    Hot damage: When the temperature is too high, leaf could be burned, and

    tree will dead as result. However, a little bit higher temperature can

    stimulate the plant growing faster.

    Beside the direct impact, temperature also has indirect impact on plants.

    Photosynthesis process contains light reaction (day time) and dark reaction (night

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 41

    time). While the light reaction totally depend on light, the dark reaction almost

    controlled by temperature. When the temperature decrease to low point, the

    enzymes can not work well.

    Knowing about the impact of temperature into plants, we not only optimize the

    living condition, but also control the productivity, time and quality of plants,

    especially flowers.

    Control the blooming time of flower: As describled above, low temperature

    slow down the blooming time of flower, and vice versa. Another word, we

    can adjust the time of blooming event. This ability is very useful because

    flower is more valueable if bloom in the right time (cenemory, annivesary,

    holiday,..)

    Control the quality of flower: Some flowers (orchid, dahlia, ...) different

    color of flower within different temperature, and soil condition. Therefore,

    we have right to decide the most valuable production by adjust the

    temperature of Greenhouse.

    III.1.2. Air humidity

    All plants inhale carbon dioxide through their leaves. This gas is used in

    photosynthesis. As the plant opens its leaf pores to take in carbon dioxide, some of

    the moisture in the leaf can escape. Thus the plants sweat water vapor into the air

    whenever they breath.

    Dry air causes plants to transpire moisture much more rapidly than does humid

    air. Waterin the leaves evaporates very quickly into air, causing the plant to lose

    moisture at a rapid rate. When leaves begin to lose water faster than the roots can

    absorb it - disaster strikes. It is an evil the plant inflicts on itself, in self defense. In

    order not to lose more water to the air, the plant will almost completely close its leaf

    pores. This slows down the flow of moisture from the plant effectively, but

    unfortunately it also reduces the intake of carbon dioxide. Without supplies of

    carbon dioxide, the cells begin to die and the plant looks tired and ill.

    The important point to remember is that dry air pulls water out of the leaves

    faster than theroots can supply the leaves. Under these conditions, it doesn't matter

    how much you water such a plant it doesn't help. Over watering only reduces the

    amount of air in the soil and invites root rot.

    When plants have the right humidity they thrive, because they open their pores

    completely and so breath deeply without threat of excessive water loss. When the

    air is moist, there is little water lost from the leaf. Damping down the benches and

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 42

    surrounds, also misting leaves will keep the air moist. Rapid temperature rises

    damage orchids too. It means thatthe plant's leaves become warm and

    physiologically active, while the root system in it's solid rooting medium, is still

    cold and consequently Physiologically dormant. The active leaves are demanding

    large quantities of water and nutrients which the root system cannot possibly

    supply.

    Under these conditions, photosynthesis, transpiration and the other vital plant

    processes, are severely restricted and as a result, developing flower growth and new

    growth are damaged. Rapid rises in temperature on sunny days can be avoided by

    opening vents or doors early in the morning - and letting the greenhouse warm

    gradually.

    III.1.3. Soil humidity

    Soil humidity directly affect the process of water exchange, as well as the

    development of harmed insects and disease. In general, humidity in Vietnam is

    high, but different regions do not have the same value.

    In particular, many kind of flowers living in Vietnam came from non-tropical

    region (eg, tulip...), which only growth in low humidity. Therefore, these flowers

    need to live under the humidity that continuously controlled.

    Like temperature, each plant has its own ideal range of humidity. Too low or

    too high value of humidity can harm the plant:

    High humidity can prevent the water exchange, thus the plant is very hard to

    analyse the nutrion. As the result, the flower usually has the bad quality, or

    even dead. Harmful insects and diseases can also growth fast in this

    condition.

    Low humidity cause the water leak, therefore, plant does not growth well.

    III.1.4. Light

    Light has three principal characteristics that affect plant growth: quantity,

    quality, and duration.

    Light quantity refers to the intensity or concentration of sunlight and varies

    with the season of the year. The maximum is present in the summer and the

    minimum in winter. The more sunlight a plant receives (up to a point), the better

    capacity it has to produce plant food through photosynthesis. As the sunlight

    quantity decreases the photosynthetic process decreases. Light quantity can be

    decreased in a garden or greenhouse by using shade-cloth or shading paint above

    the plants. It can be increased by surrounding plants with white or reflective

    material or supplemental lights.

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 43

    Light quality refers to the color or wavelength reaching the plant surface.

    Sunlight can be broken up by a prism into respective colors of red, orange, yellow,

    green, blue, indigo, and violet. On a rainy day, raindrops act as tiny prisms and

    break the sunlight into these colors producing a rainbow. Red and blue light have

    the greatest effect on plant growth. Green light is least effective to plants as most

    plants reflect green light and absorb very little. It is this reflected light that makes

    them appear green. Blue light is primarily responsible for vegetative growth or leaf

    growth. Red light when combined with blue light, encourages flowering in plants.

    Fluorescent or cool-white light is high in the blue range of light quality and is used

    to encourage leafy growth. These lights are excellent for starting seedlings.

    Incandescent light is high in the red or orange range but generally produces too

    much heat to be a valuable light source. Fluorescent "grow" lights have a mixture of

    red and blue colors that attempts to imitate sunlight as closely as possible. They are

    costly and generally not of any greater value than regular fluorescent lights.

    Light duration or photoperiod refers to the amount of time that a plant is

    exposed to sunlight. When the concept of photoperiod was first recognized it was

    thought that the length of periods of light triggered flowering. The various

    categories of response were named according to the light length (i.e., short-day and

    long-day). It was then discovered that it is not the length of the light period but the

    length of uninterrupted dark periods that is critical to floral development. The

    ability of many plants to flower is controlled by photoperiod.

    There is two groups of plants: light-like plants and shade-like plants. While the

    first group needs direct and high intensity of light to well growth, the other one only

    growth under shade. Like temperature and humidity, high and low intensity of light

    could impact the plants:

    Weak light sometimes is not enough for photosynthesis process, which lead

    to low quality of production.

    Strong light, on the other hand, can burn the leaf and destroy the

    chlorophyll. By the other word, too strong light can kill the plant.

    III.2. Data acquisition requirement

    From the above section, we can conclude that, by controlling these natural

    parameters, we can guarantee and improve the quality of plants. To control these

    stuffs, first we need to measure and collect the data from nodes, but how often

    should we need to collect the data ? This situation should be carefully consider

    because choosing the suitable degree of measurement could enhance the

    performance of the whole system and reduce the power consumption of each

    sensors.

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 44

    To find the suitable answer for this question, we study on how frequent that

    these conditions change their value, and the mechanism that plant use to react with

    the changes.

    III.2.1. Light and temperature data

    In theory, light must be control continously because tree depends too much on

    light and temperature. However, start from the particular situation, the value of

    them can be measured periodically, because of these reasons:

    High intensity of light or high temperature could instantly kill the tree, but it

    is almost impossible under greenhouse, and the climate of Vietnam.

    The tree itself has the mechanism to protect and react with the change of

    them in short time.

    In certain season, we can predict the value of light and temperature in

    specific time, with small errors.

    In artifact light condition, we can exaclty determine the value of light and

    maintain the value of temperature.

    III.2.2. Air and soil humidity data

    High air humidity in long time is the the main reason for most of disease and

    insect.

    Low air humidity can instantly prevent the photosynthesis, low air moisture

    in long time can prevent plant rejecting Carbon Dixide, which very harmful

    to plant itself.

    High soil humidity (after baste or under flooded condition) may kill the root

    in couple of minutes.

    III.3. Data measurement frequencies

    From the above studies, we can see that different data requires a different

    sensing period. We propose the following environment parameter measurement

    period:

    Light sensing: Once every 30 seconds.

    Air temperature sensing: Once every 10 seconds.

    Air humidity sensing: Once every 5 seconds.

    Soil sensing (pH and humidity): Once every 2 seconds.

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 45

    IV. Types of sensors and controlling parameters in greenhouse

    IV.1. Air temperature control

    Growth of Plants depends on the photosynthesis process which is a

    measure of photosynthetically active radiation. It is observed that proper

    temperature level influences the speed of sugar production by photosynthesis

    radiation. Temperature has to be control properly since higher radiation level

    may give a higher temperature. Hence, in the diurnal state, it is necessary to adjust

    the temperature at an optimal level for the photosynthesis process. In nocturnal

    conditions, plants are not active therefore; it is not necessary to maintain such a high

    temperature. For this reason, two temperature set-points are usually considered are

    diurnal and nocturnal [23].

    In favourable weather conditions of temperature during the daytime the

    energy required to reach the optimal temperature is provided by the sun. In fact,

    the usual diurnal temperature control problem is the refrigeration of the greenhouse

    using natural ventilation to achieve the optimal diurnal temperature. On the other

    hand, heating of the greenhouse up to required temperature is the case of

    nocturnal temperature control. Some cases forced-air heaters are commonly

    used as heating systems.

    IV.2. Humidity control

    Water vapour inside the greenhouse is one of the most significant variables

    affecting the crop growth. High humidity may increase the probability of diseases

    and decrease transpiration. Low humidity may cause hydria stress, closing the

    stomata and thus it may lower down the process of photosynthesis which depends

    on the CO2 assimilation. The humidity control is complex because if

    temperature changes then relative humidity changes inversely. Temperature and

    humidity are controlled by the same actuators. The main priority is for

    temperature control because it is the primary factor in the crop growth. Based

    on the inside relative humidity value the temperature set-point can be adjusted

    to control the humidity within a determined range. Hence to control the required

    humidity is very complex task. For proper control of humidity internal air can be

    exchange with outside air by properly controlling ventilations of the green house

    [24].

    IV.3. Soil control

    Soil water also affects the crop growth. Therefore, the monitor & control of soil

    condition has a specific interest, because good condition of a soil may

    produce the proper yield. The proper irrigations and fertilizations of the crops

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 46

    are varies as per the type, age, phase and climate. The pH value, moisture

    contains, electric conductivity and the temp of a soil are some key parameters. The

    pH valves and other parameters will help to monitor the soil condition. The

    temperature and the moisture can be controlled by the irrigation techniques like

    drift and sprinkles system in a greenhouse. The temperature of the soil and

    the inside temperature of the green house are interrelated parameters, which can

    be, control by proper setting of ventilation. Since the temperature control is

    depends on direct sun radiation and the screen material used, the proper set point

    can adjust to control soil temperature. The temperature set-point value

    depends on actual temperature of the inside and outside of the greenhouse

    [25].

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 47

    CHAPTER III. SYSTEM SIMULATION

    I. OMNeT++

    OMNeT++ is an object-oriented modular discrete event network simulation

    framework. It has a generic architecture, so it can be (and has been) used in various

    problem domains:

    Modeling of wired and wireless communication networks

    Protocol modeling

    Modeling of queueing networks

    Modeling of multiprocessors and other distributed hardware systems

    Validating of hardware architectures

    Evaluating performance aspects of complex software systems

    In general, modeling and simulation of any system where the discrete event

    approach is suitable, and can be conveniently mapped into entities communicating

    by exchanging messages.

    OMNeT++ simulations can be run under various user interfaces. Graphical,

    animating user interfaces are highly useful for demonstration and debugging

    purposes, and command-line user interfaces are best for batch execution

    II. System simulation

    We implemented the whole IoT stacks using Omnet++. The overview of our

    implementation is as follow:

    Application layer demonstrate the process of sensing environment data and

    send them to base station

    UDP in transport layer

    IPV6 with RPL and 6LoWPAN in network layer.

    CSMA-CA for MAC layer.

    ContikiMac for RDC layer.

    Specifcation of 802.15.4 250kbps 2.4GHz Chipcon CC2420 for physic layer.

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 48

    III. OMNet++ project structure

    Folder simulations includes system configuration (omnetpp.ini, WSN.ned)

    and testing result folder (result)

    o File simulations/omnetpp.ini: contains network configurations.

    o File simulations/WSN.ned contains communication stack definition

    of each module (sensors node, statistics and world manager)

    Folder src: contains source code.

    o Folder src/package has 5 sub-folders (data, segment, packet, frame,

    signal and strobe) which defines packet format at each layer

    o Folder src/util contains 3 modules: statistics model, world manager

    and signal manager.

    o Folder src/apps contains code for Client-Server applications.

    o Folder src/core contains code for each layer driver and utilities.

    The energest module is one that use capsule algorithm to estimate time

    operation of cc2420 and then calculate the energy consumption of each sensor node.

    o Folder src/mote contains client.ned and server.ned which describe

    the sensor nodes and base stations components and create connection

    among them.

    OMNeT++ simulations can be run under various user interfaces. Graphical,

    animating user interfaces are highly useful for demonstration and debugging

    purposes, and command-line user interfaces are best for batch execution.

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 49

    CHAPTER IV. PERFORMANCE EVALUATION

    I. Network setup

    We set up the sensors accordingly to our design mentioned in chapter 2. We

    have 3 scenario for 3 sizes of greenhouse: small-sized, medium-sized and large-

    sized. The nodes are configurated to have a range of 47m, charged with 2AA

    batteries with the total capacity of 2000 mAh and operation voltage of 1.5V. The

    residual energy is set at 0.3%.

    The sensors will periodically sense data according to our result from previous

    parts:

    Light sensing: Once every 30 seconds.

    Air temperature sensing: Once every 10 seconds.

    Air humidity sensing: Once every 5 seconds.

    Soil sensing (pH and humidity): Once every 2 seconds.

    Each sensors then try to send these data back to the base station.

    For small-sized and medium-sized, the perfomance was superb with almost

    100% Package Delivery Rate using only simple RPL routing. For that reason, we

    will not discuss the improvement of Multipath routing in these two scenario, we

    will mainly focus on our result in large-sized field. The 3 following methods will be

    used to measure the improvement of our multipath RPL:

    Packet delivery rate: this is the ratio of number of package received in

    the base station to number of package sent from nodes.

    End-to-end delay: this is calculated by divide the total delay to the total

    number of package has been received by application layer in Server. It

    represent time difference between data sent at each nodes and received

    at the base station.

    Data error received at base station: During the experiment, I recorded the

    value of data sent from sensor nodes and base station. Then, the set of

    data will be synthesized to result the general error during the transmit

    time by comparing the data from choosen nodes and base station.

    Residual energy-level distribution: energy in each sensor nodes is

    divided into 100 equally level. In this method, the number of node in

    each level is counted.

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 50

    II. Result analysis

    After running time of 1800 seconds, there are 74232 packets sent over the

    network. These packets contains the information of light, temperature, soil humidity

    and air humidity. The ratio of numbers of each type is described in figure 21:

    Figure 21: Ratio of packets

    II.1. Package Delivery Rate

    After calculating the package delivery ratio by the percent of successfully

    transferred packages and total sent packages. The result is presented in the table 2:

    Delivered ratio (%) Total

    Light Air

    humidity

    Soil

    humidity

    temperature Send Received Ratio

    (%)

    RPL 73.05 88.62 87.00 85.21 74232 65208 87.84%

    ELB 78.07 92.04 90.21 89.12 74232 67552 91.00%

    FLR 75.95 91.67 89.92 87.71 74232 67455 90.87%

    ELB-

    FLR

    78.21 93.32 91.39 89.64 74232 68530 92.32%

    Table 2: Packet Delivery Rate in detail

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 51

    Figure 22: Overall Packet delivery rate

    ELB-FLR shown to have the best PDR (92.3%). ELB and FLR alone shown

    some improvement yet having roughly equal result: 91% and 90.8% respectively.

    RPL has the worst package delievery rate with only 87.8% package successfully

    deliveried. It can be explained that because RPL use more ICMPv6 message to

    maintain its route, there is higher chance of traffic congestion, and FLR tackle this

    issue by reduce the amount of these messages. Moreover, ELB provides a parent

    switching mechanism to prevent a few good parents from having much higher load

    than the rest and quickly ran out of power. ELB-FLR gives the best result since

    FLR provides a set of sibling nodes. These nodes can in turn act as parent nodes,

    giving ELB more choices when it comes to parent switching.

    II.2. End-to-end delay

    In this section, we measure the end-to-end delay of packets produced by

    different routing solutions: RPL, ELB, FLR, ELB-FLR. Packet delay is the amount

    of time that packet took to be transmitted successfully. The average packet delay is

    calculated by the following formula:

    Packet delay = total delay / number of packet received

    The detail packet delay of each measured parameters is presented seperatedly in

    table 3:

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 52

    Packet delay (ms)

    Light Air humidity Soil

    Humidity

    Temperature

    RPL 194.72 212.62 201.63 211.98

    ELB 301.3 334.44 316.42 332.97

    FLR 192.84 212.5 200 213.51

    ELB-FLR 248.77 266.1 251.27 270.34

    Table 3: Packet delay in detail

    Figure 23: Overall End-to-end delay

    FLR (202 msec) shown a little improvement compared to normal RPL (203

    msec). However ELB and ELB-FLR cause a significant higher delay (319 msec and

    253 msec respectively). It can be explained that FLR actually reduced the number

    of ICMPv6 message needed to maintain RPL route, therefore reduce the amount of

    time data payload needs to wait for those ICMPv6 in package queue. On the other

    hand, ELB and ELB-FLR tries to balance energy load by choosing different parent

    at any transmission. Under the circumstances of our network setup, 1 node may

    have many parent nodes, therefore the parent switching get really slow, thus

    increase the overall delay of package.

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 53

    However, these delay is in acceptable range, as a greenhouse monitoring

    system does not need pin-point accuracy on time constraint.

    II.3. Data error received at Base Station

    Figure 24: Temperature Error at BS

    Figure 25: Light Error at BS

    0

    0.5

    1

    1.5

    2

    0 500 1000 1500 2000 2500 3000

    Erro

    r (C

    elc

    iou

    s)

    Time

    Temperature error

    RPL ELB FLR FLR+ELB

    0

    20

    40

    60

    80

    100

    120

    140

    160

    0 500 1000 1500 2000 2500 3000

    Erro

    r (L

    ux)

    Time

    Light error

    RPL ELB FLR FLR+ELB

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 54

    Figure 26: Air humidity Error at BS

    Figure 27: Soil humidity Error at BS

    All above figures (from Fig.24 to Fig.27) represent the error between data

    received at the BS produced by RPL, ELB, FLR, ELB-FLR and the data sent at the

    sensors. Obviously, the high data error leads to the decreased monitoring quality.

    As shown in the previous figures, RPL routing protocol produces the highest data

    error, compared to ELB, FLR and ELB-FLR. The reason of this characteristic is

    that RPL achieves the worst packet delivery rate (as described in previous section).

    This low packet delivery rate leads to the data error produced at the BS. More

    concretely, pH level and light intensity varies slightly according to the time while

    temperature and humidity fluctuates more strongly. Thus, the data error received at

    0

    2

    4

    6

    8

    10

    12

    14

    16

    18

    0 500 1000 1500 2000 2500 3000

    Erro

    r (%

    )

    Time

    Air humidity error

    RPL ELB FLR FLR+ELB

    0

    2

    4

    6

    8

    10

    12

    14

    16

    18

    0 500 1000 1500 2000 2500 3000

    Erro

    r (%

    )

    Time

    Soil humidity error

    RPL ELB FLR FLR+ELB

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 55

    the BS of pH level and light intensity is smaller than error of temperature and

    humidity. In addition, among five above parameters (pH level, light intensity,

    humidity of the air and the soil, temperature), it is necessary to measure the

    humidity with the highest sampling rate. This high sampling rate leads to the more

    frequent humidity error produced at the BS. In conclusion, the implementation of

    multipath-based RPL protocols ELB, FLR, ELB-FLR can help to the performance

    increase of environment monitoring parameters.

    II.4. Residual Energy

    It can be seen that ELB, FLR and ELB-FLR provided more nodes with high

    residual energy level. Where ELB and FLR provided roughly the same result, ELB-

    FLR combined shows much promising sin0063e it both reduce the number of

    overhead package and maintain a balanced level of energy among nodes.

    Figure 28: Residual Energry

  • Thesis is performed by: Nguyen Khoi Nguyen - 20101949 ICT 55 56

    CHAPTER V. CONCLUSION AND FUTURE WORKS

    In this thesis, we have studied the concept of Precision Agriculture and the

    deployment of Greenhouse using Wireless Sensor Network over Internet of Things.

    We also studied the popular plants and flowers in Vietnam and their characteristic

    to determine how environment affects their growth. Using these information, we

    concluded how important certain environment parameters are and how often should

    we measure them to not only ensure plants' safety but also save energy. By careful

    observation of real world Greenhouse models and Vietnam's particular requirement,

    we came up with a design of Greenhouse suitable for Vietnamese farmers. We also

    studied the multipath solution based on RPL and apply it to improve the system's

    performance. Last, we set up a simulation and the out come result was very

    promising.

    However, these designs have only been implemented and tested in simulation

    environment. For real world applications, there are a lot of others' factor that can

    affect and degrade the system's performance. Another problems is that the multipath

    enchanment is still in theory and not yet implemented and tested on real devices.

    Overall, this research is aimed toward deploying a real world applicati