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CROSS LAYER ROUTING DESIGN BASED ONRPL FOR MULTI-HOP COGNITIVE RADIO

NETWORKS

THESIS

Submitted in partial fulfilment of the requirementsfor the award of the Degree of Master of Technology

in Electronics and Communication Engineering(Advanced Communication and Information Systems)

of Mahatma Gandhi University, Kottayam

Submitted by

IRIN SAJAN

Department of Electronics and CommunicationEngineering

Rajiv Gandhi Institute of TechnologyKottayam 686 501

August 2014

CROSS LAYER ROUTING DESIGN BASED ONRPL FOR MULTI-HOP COGNITIVE RADIO

NETWORKS

THESIS

Submitted in partial fulfilment of the requirementsfor the award of the Degree of Master of Technology

in Electronics and Communication Engineering(Advanced Communication and Information Systems)

of Mahatma Gandhi University, Kottayam

Submitted by

IRIN SAJAN

Under the guidance of

Mr. EBIN M. MANUEL(Assistant Professor)


Rajiv Gandhi Institute of TechnologyKottayam 686 501

August 2014


Rajiv Gandhi Institute of TechnologyKottayam-686 501

Certificate

This is to certify that this thesis report entitled CROSS LAYERROUTING DESIGN BASED ON RPL FOR MULTI-HOP COG-NITIVE RADIO NETWORKS is a bonafide record of the works doneby IRIN SAJAN (20508), under our guidance towards partial fulfilmentof the requirements for the award of the degree of Master of Technologyin Electronics and Communication Engineering ( Advanced Com-munication and Information Systems), of Mahatma Gandhi Univer-sity, Kottayam, during the year 2012-2014 and that this work has not beensubmitted elsewhere for the award of any degree.

Guide PG Co-ordinator Head of Dept.

Mr. Ebin M. Manuel Dr. David Solomon George Dr. Leena MaryAssistant Professor Associate Professor ProfessorDept. of ECE Dept. of ECE Dept. of ECERIT RIT RITKottayam Kottayam Kottayam

Acknowledgement

The success accomplished in this thesis would not have been possiblewithout the timely help and guidance rendered by many people to whom Ifeel obliged and grateful.

First of all, I would like to express my sincere thanks to our belovedprincipal Dr. K P INDIRADEVI, for her support and encouragement.

I use this occasion to express my thanks to Prof. GEETHARANJIN P. R.,PG Dean and Dr. LEENA MARY, Head of Electronics and CommunicationDepartment, for their continuous encouragement to fulfil my thesis.

I am thankful to Dr. RENU JOSE, staff advisor and Dr. DAVIDSOLOMON GEORGE, PG Co-ordinator for their valuable suggestions, in-spiration and motivation to develop the thesis.

I sincerely extend my gratitude to Mr. EBIN M. MANUEL, my guide forhis cooperation, encouragement and guidance for completing and presentingthe thesis.

I am also thankful to all the teaching and non teaching staffs in Electronicsand Communication Department for their timely assistance.

I thank my parents and friends for their kind co-operation and suggestionswhich helped me very much for the accomplishment of my thesis.

Finally, I would like to express my sincere thanks to the ALMIGHTYGOD, who empowered me to fulfil this work, by showering his abundantgrace and mercy.

Rajiv Gandhi Institute of Technology Irin SajanAugust, 2014

i

Abstract

Cognitive Radio (CR) is viewed as a revolutionary potential radio technol-ogy capable of offering dynamic spectrum access. CR Networks (CRNs) withsuch spectrum aware devices is a hopeful solution to the spectrum scarcityissue faced in the wireless communication sector. In this work, an effectiverouting solution with a cross layer design is proposed for the multi-hop CRNs.Most of the existing work uses AODV (Ad-hoc On-demand Distance Vector)protocol as the routing protocol for CRNs. A new routing protocol namedRPL (Routing Protocol for Low power and lossy networks (LLNs)) is beingintroduced into the CRN scenario in this work. It is the primary candidatefor acting as the standard routing protocol for IP (Internet Protocol) smartobject networks. The CRs being smart, RPL can be effectively implementedin its network. Dynamic spectrum allocation is also done along with routingwith the help of RPL. Routing is accomplished through the formation of col-ored Destination Oriented Directed Acyclic Graphs (DODAGs) of which thelink frequencies are represented using colors. Hop count and adjacent linkinterference are counted as the routing metrics. The CRN scenario is vulner-able to link failures due to the appearance of Primary Users (PUs). So routerepairing using the Trickle algorithm offered by RPL is also implemented inthis work. To implement this algorithm, a traffic aware scheduling is used.Simulation results show that the routing design can perform efficiently withminimum overhead under different network conditions.

ii

Contents

Acknowledgement i

Abstract ii

List of Figures v

List of Tables vii

1 Introduction 1

2 Literature Survey 3

3 Routing Model 113.1 Network Model . . . . . . . . . . . . . . . . . . . . . . . . . . 113.2 Cross Layer Design . . . . . . . . . . . . . . . . . . . . . . . . 123.3 Routing Metrics . . . . . . . . . . . . . . . . . . . . . . . . . . 12

4 Overview of RPL 144.1 RPL Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 144.2 Features of RPL . . . . . . . . . . . . . . . . . . . . . . . . . . 154.3 RPL Control Messages . . . . . . . . . . . . . . . . . . . . . . 16

4.3.1 DODAG Information Object (DIO) . . . . . . . . . . . 164.3.2 DODAG Information Solicitation (DIS) . . . . . . . . . 20

4.4 DODAG Construction / Routing Algorithm . . . . . . . . . . 20

5 Route Repair Using Trickle Algorithm 245.1 Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255.2 Trickle Parameters and Variables . . . . . . . . . . . . . . . . 255.3 Repairing Algorithm . . . . . . . . . . . . . . . . . . . . . . . 26

6 Simulation Results and Analysis 296.1 Routing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

iii

6.2 Route Repairing . . . . . . . . . . . . . . . . . . . . . . . . . . 326.3 Performance Analysis . . . . . . . . . . . . . . . . . . . . . . . 36

7 Conclusion 38

Reference 39

List of Publications 41

iv

List of Figures

2.1 Spectrum utilisation. . . . . . . . . . . . . . . . . . . . . . . . 32.2 Dynamic spectrum access. . . . . . . . . . . . . . . . . . . . . 52.3 Cognitve Cycle. . . . . . . . . . . . . . . . . . . . . . . . . . . 62.4 CRN Architecture. . . . . . . . . . . . . . . . . . . . . . . . . 8

3.1 Network Model. . . . . . . . . . . . . . . . . . . . . . . . . . . 12

4.1 Colored DODAG. . . . . . . . . . . . . . . . . . . . . . . . . . 154.2 RPL Control Message Format. . . . . . . . . . . . . . . . . . . 174.3 DIO Base Object Format. . . . . . . . . . . . . . . . . . . . . 174.4 Local RPLInstanceID. . . . . . . . . . . . . . . . . . . . . . . 184.5 DIO Options Field. . . . . . . . . . . . . . . . . . . . . . . . . 184.6 DAG Metric Container Object Format. . . . . . . . . . . . . . 194.7 Hopcount Object Body Format. . . . . . . . . . . . . . . . . . 194.8 Link Color Object Body Format. . . . . . . . . . . . . . . . . 194.9 Type-I sub-object. . . . . . . . . . . . . . . . . . . . . . . . . 204.10 Type-II sub-object. . . . . . . . . . . . . . . . . . . . . . . . . 204.11 DIS Base Object Format. . . . . . . . . . . . . . . . . . . . . . 204.12 Operation of a Router During Routing . . . . . . . . . . . . . 22

5.1 Operation of a Router During Route Repairing . . . . . . . . . 28

6.1 Network Topology. . . . . . . . . . . . . . . . . . . . . . . . . 296.2 Topology Showing Multiple Paths. . . . . . . . . . . . . . . . 316.3 Topology Showing Default Route. . . . . . . . . . . . . . . . . 316.4 DODAG Formed. . . . . . . . . . . . . . . . . . . . . . . . . . 326.5 Locally Repaired Route with Alternate Channel . . . . . . . . 326.6 Locally Repaired Route with Alternate Path. . . . . . . . . . . 336.7 Locally Repaired Route with Alternate Channel. . . . . . . . . 336.8 New Topology. . . . . . . . . . . . . . . . . . . . . . . . . . . 346.9 Topology Showing Multiple Paths After Global Repair. . . . . 346.10 New Route After the Global Repair. . . . . . . . . . . . . . . 35

v

6.11 New DODAG Formed. . . . . . . . . . . . . . . . . . . . . . . 356.12 Data and Control Packet Flow Comparison. . . . . . . . . . . 366.13 Control Packet Overhead Under Different Routing Conditions. 37

vi

List of Tables

2.1 Spectrum Allocation in India . . . . . . . . . . . . . . . . . . 4

6.1 Topology and Spectrum Availability . . . . . . . . . . . . . . . 30

vii

Chapter 1

Introduction

Todays wireless networks face the issue of spectral congestion problemdue to the fixed spectrum allocation policy. Cognitive Radio (CR), proposedby Joseph Mitola III[1], is an emerging wireless communication paradigmthat can significantly improve the spectrum usage efficiency by offering dy-namic spectrum access. CR is an intelligent radio that can change its trans-mitter parameters based on the interaction with the radio environment inwhich it operates[2]. CR Networks (CRNs) with such spectrum aware de-vices is the obvious eminent future of todays wireless networks.

In multi-hop CRNs, routing is the most significant problem to be ad-dressed as it determines the performance of the network. Development of aspectrum agile routing solution for CRNs is a major challenge[5]. CR de-vices become aware of their radio environment through its spectrum sensingfunctionality. Several spectrum sensing algorithms are available in the lit-erature with the energy detector, the cyclostationary feature detector, andthe matched filter detector being the mostly discussed among them[2]. Ina network, the spectrum opportunities of each CR device will be locationdependent. In such a scenario, an effective routing solution is a cross layerdesign where dynamic spectrum allocation is done along with routing[5].Considering this, a cross layer routing solution is proposed in this work.

Routing protocol being used in most of the existing work is the Ad-hoc On-demand Distance Vector (AODV) protocol and its variations[5]. InAODV, the Route Request (RREQ) messages, which are sent via broadcast-ing, contain locally obtained network state and deliver this detailed informa-tion to the destination, where they are processed to compute paths[4]. Andthe routing decisions being adopted at the destination are then forwardedin the reverse path using the Route Reply (RREP) messages. Here comes

1

Cross Layer Routing Design Based on RPL for Multi-hop Cognitive RadioNetworks

the need for a protocol in CRN that can perform the routing as the con-trol packet moves from one point to another. Such a routing protocol is theRPL (Routing Protocol for Low power and lossy networks (LLNs)). Oncethe control packet reaches the end node, the routing is completed and datatransmission can be initiated in the next instant. This work proposes to useRPL as a routing protocol in a CRN routing scenario.

RPL is actually a routing protocol developed for the LLNs. It is the maincandidate for acting as a standard routing protocol for IP (Internet Protocol)smart object networks[6]. CRs being smart, it can be effectively implementedas a promising routing solution for a CRN. As the name suggests, it can proveworthy for those networks with frequent link outages and CRN is one amongthem. RPL is based on the topological concept of Directed Acyclic Graphs(DAGs). In a CRN scenario, routing is performed through the constructionof a colored Destination Oriented DAGs (DODAGs) with destination as theroot and source(s) as the leaf node(s). Link frequencies are represented usingdifferent colors which make the DODAG a colored one.

For any routing algorithm, routing metric is of paramount importance asit determines the quality of the resulting route. It determines the best routefrom a source to destination. This RPL based algorithm chooses the pathwith the minimum hop count and the minimum adjacent link interferenceas the best path. Also, two nodes will communicate in a CRN only if thereexists a common channel between them.

Unpredictable link failures due to the appearance of primary users (PUs)are common in a CRN. Unquestionably, a repairing algorithm is essential tobe defined when a routing algorithm is proposed. It should allow a reroutingin terms of channels and/or nodes. This routing design uses Trickle algo-rithm for route repair which is actually a part of RPL[6]. Trickle algorithmoptimizes the control plane overhead based on network conditions[9].

This report is structured as follows. Chapter 2 gives a brief accountof the literature survey behind this work. Chapter 3 depicts the routingmodel being used in this work which introduces the network model, the crosslayer design and the routing metrics. Chapter 4 gives an overview of theRPL and Chapter 5 describes the implementation of route repair using theTrickle algorithm in CRNs. Chapter 6 presents the simulation results andthe analysis. Finally, Chapter 7 provides the concluding remarks.

Dept. of ECE, RIT Kottayam 2

Chapter 2

Literature Survey

According to [1], current wireless networks are characterized by a staticspectrum allocation policy, where governmental agencies assign wireless spec-trum to license holders on a long-term basis for large geographical regions.Recently, because of the increase in spectrum demand, this policy faces spec-trum scarcity in particular spectrum bands.

Table 2.1 shows the spectrum allocations in India. According to the re-port published by the Federal Communications Commission (FCC), a largeportion of the assigned spectrum is used sporadically, leading to underuti-lization of a significant amount of spectrum. Figure 2.1 clearly shows this.Hence, dynamic spectrum access techniques were recently proposed to solvethese spectrum inefficiency problems.

Figure 2.1: Spectrum utilisation.

3


Table 2.1: Spectrum Allocation in India

Frequency Band (MHz) Services0-87.5 Mobile, aeronautical navigation, Cordless phones87.5 -108 FM Radio Broadcast109- 173, 230-450 Broadcast vans, aeronautical navigation585-698 TV Broadcast806-960 GSM, CDMA mobile services960-1710 Aeronautical and Space Communication1710-1930 GSM mobile services1930-2010 Used by Defence forces2025-2110, 2170- 2300 Satellite and Space2400-2483.5 Wi-Fi, Bluetooth2483.5-3300 Space communication3600-10000 Space research, radio navigation10000 onwards Satellite broadcasts, DTH services

The key enabling technology of dynamic spectrum access techniques isCognitive Radio (CR) technology, which provides the capability to sharethe wireless channel with licensed users in an opportunistic manner. Theterm was coined by Joseph Mitola III in his doctoral dissertation[2]. It wasgiven a communication perspective by Simon Haykins[2]. Cognitive radio isan intelligent wireless communication system that is aware of its surround-ing environment (i.e., outside CRNs with such spectrum agile CR devicesare envisioned to provide high bandwidth to mobile users via heterogeneouswireless architectures and dynamic spectrum access techniques. Figure 2.2shows this dynamic spectrum access. This goal can be realized only throughdynamic and efficient spectrum management techniques.

The term, cognitive radio, can formally be defined as follows[1]: Cogni-tive radio is an intelligent wireless communication system that is aware ofits surrounding environment (i.e., outsideworld), and uses the methodologyof understanding-by-building to learn from the environment and adapt itsinternal states to statistical variations in the incoming RF stimuli by makingcorresponding changes in certain operating parameters (e.g., transmit-power,carrier-frequency, and modulation strategy) in real-time, with two primaryobjectives in mind:

highly reliable communications whenever and wherever needed;



Figure 2.2: Dynamic spectrum access.

efficient utilization of the radio spectrum.From this definition, two main characteristics of the cognitive radio can bedefined[3]:

Cognitive capability: Cognitive capability refers to the ability of theradio technology to capture or sense the information from its radio en-vironment. This capability cannot simply be realized by monitoringthe power in some frequency band of interest but more sophisticatedtechniques are required in order to capture the temporal and spatialvariations in the radio environment and avoid interference to otherusers. Through this capability, the portions of the spectrum that areunused at a specific time or location can be identified. Consequently,the best spectrum and appropriate operating parameters can be se-lected. The tasks required for adaptive operation in open spectrum areshown in Fig. 2.3 which is referred to as the cognitive cycle. It involvesspectrum sensing, spectrum analysis and spectrum decision.

Reconfigurability: The cognitive capability provides spectrum aware-ness whereas reconfigurability enables the radio to be dynamically pro-grammed according to the radio environment. More specifically, thecognitive radio can be programmed to transmit and receive on a vari-ety of frequencies and to use different transmission access technologiessupported by its hardware design.



Figure 2.3: Cognitve Cycle.

CR networks, however, impose unique challenges due to the high fluctua-tion in the available spectrum, as well as the diverse quality of service (QoS)requirements of various applications. In order to address these challenges,each CR user in the CR network must perform the following functions[3]:

Determine which portions of the spectrum are available (Spectrum Op-portunities) - Spectrum sensing

Select the best available channel - Spectrum management Coordinate access to this channel with other users - Spectrum sharing Vacate the channel when a licensed user is detected - Spectrum mobility

[3] gives a clear description of the Cognitve Radio Network (CRN) ar-chitecture which is essential to understand the performance of the routingdesign. The components of the CRN architecture, as shown in Fig. 2.4, canbe classified in two groups as the primary network and the CRN. The basicelements of the primary and the CRN are defined as follows:

Primary network: An existing network infrastructure is generally re-ferred to as the primary network, which has an exclusive right to acertain spectrum band. Examples include the common cellular andTV broadcast networks. The components of the primary network areas follows:



Primary user: Primary user (or licensed user) has a license tooperate in a certain spectrum band. This access can only be con-trolled by the primary base-station and should not be affected bythe operations of any other unlicensed users. Primary users donot need any modification or additional functions for coexistencewith CR base-stations and CR users.

Primary base-station: Primary base-station (or licensed base-station)is a fixed infrastructure network component which has a spectrumlicense such as base-station transceiver system (BTS) in a cellularsystem. In principle, the primary base-station does not have anycognitive capability for sharing spectrum with CR users.

CRN: CRN does not have license to operate in a desired band. Hence,the spectrum access is allowed only in an opportunistic manner. CRNscan be deployed both as an infrastructure network and an ad hoc net-work. The components of the CRN are as follows:

CR user: CR user (or unlicensed user, secondary user) has nospectrum license. Hence, additional functionalities are requiredto share the licensed spectrum band.

CR base-station: CR base-station (or unlicensed base-station, sec-ondary base-station) is a fixed infrastructure component with cog-nitive capabilities. CR base-station provides single hop connectionto CR users without spectrum access license. Through this con-nection, a CR user can access other networks.

Spectrum broker: Spectrum broker (or scheduling server) is a cen-tral network entity that plays a role in sharing the spectrum re-sources among different CRNs. Spectrum broker can be connectedto each network and can serve as a spectrum information managerto enable coexistence of multiple CRNs.

The reference network architecture is shown in Fig. 2.4, which consistsof different types of networks: a primary network, an infrastructure basedCR network, and an ad-hoc CR network[3]. CRNs are operated under themixed spectrum environment that consists of both licensed and unlicensedbands. Also, CR users can either communicate with each other in a multihopmanner or access the base-station. Thus, in CRNs, there are three differentaccess types:

CR network access: CR users can access their own CR base-stationboth on licensed and unlicensed spectrum bands.



CR ad hoc access: CR users can communicate with other CR usersthrough ad hoc connection on both licensed and unlicensed spectrumbands.

Primary network access: The CR users can also access the primarybase-station through the licensed band.

Figure 2.4: CRN Architecture.

According to [5], effective routing solutions for multi-hop CRNs are re-quired fully unleash the potentials of the cognitive networking paradigm. Ina nutshell, the main challenges for routing information throughout multi-hopCRNs include[5]:

Challenge 1: the spectrum-awareness; designing efficient routing solu-tions for multi-hop CRNs requires a tight coupling between the routingmodule(s) and the spectrum management functionalities such that therouting module(s) can be continuously aware of the surrounding phys-ical environment to take more accurate decisions.



Challenge 2: the set up of qualityroutes in dynamic variable environ-ment; the very same concept of route qualityis to be re-defined underCRN scenario. Indeed, the actual topology of multi-hop CRNs is highlyinfluenced by PUs behaviour, and classical ways of measuring/ assess-ing the quality of end-to-end routes (nominal bandwidth, throughput,delay, energy efficiency and fairness) should be coupled with novel mea-sures on path stability, spectrum availability/PU presence. As an ex-ample, if the PU activity is moderate- to-low, the topology of the sec-ondary usersa network is almost static, and classical routing metricsadopted for wireless mesh networks could be leveraged.

Challenge 3: the route maintenance/reparation; the sudden appear-ance of a PU in a given location may render a given channel unusablein a given area, thus resulting in unpredictable route failures, whichmay require frequent path rerouting either in terms of nodes or usedchannels. In this scenario, effective signalling procedures are requiredto restore broken paths with minimal effect on the perceived quality.

Also according to [5], routing protocol being used in most of the existingwork is the Ad-hoc On-demand Distance Vector (AODV) protocol or itsvariation. In AODV, the Route Request (RREQ) messages, which are sentvia broadcasting, contain locally obtained network state and deliver thisdetailed information to the destination, where they are processed to computepaths[5]. And the routing decisions being adopted at the destination are thenforwarded in the reverse path using the Route Reply (RREP) messages. Herecomes the need for a protocol in CRN that can perform the routing as thecontrol packet moves from one point to another. According to [7], sucha routing protocol is the RPL (Routing Protocol for Low power and lossynetworks (LLNs)). Once the control packet reaches the end node, the routingis completed and data transmission can be initiated in the next instant.

This paper proposes to use RPL as a routing protocol in a CRN routingscenario. RPL is actually a routing protocol developed for the LLNs. It is themain candidate for acting as a standard routing protocol for IP smart objectnetworks. CRs being smart, it can be effectively implemented as a promisingrouting solution for a CRN. It is based on the topological concept of DirectedAcyclic Graphs (DAGs). In a CRN scenario, routing is performed throughthe construction of a colored Destination Oriented DAGs (DODAGs) withdestination as the root and source(s) as the leaf node(s). Link frequencies arerepresented using different colors which make the DODAG a colored one[6].As the name suggests, it can prove worthy for those networks with frequent



link outages and CRN is one among them. This paper uses Trickle algorithmfor route repair which is actually a part of RPL. Trickle algorithm optimizesthe control plane overhead based on network conditions[10].

As found in [8], RPL can achieve the three design challenges mentionedin [5] and hence it is suggested and analysed in this work.


Chapter 3

Routing Model

Effective routing solutions for multi-hop CRNs are required fully unleashthe potentials of the cognitive networking paradigm.

3.1 Network Model

In this routing design, the CRN is assumed to be deployed as an infras-tructure network. It consists of CR users (CRUs) (referred also as nodes inthis work) and CR base station (CBS). Each user has a single-hop connec-tion to its base station. It co-exists with the primary network with PUs andprimary base station (PBS). The PUs access the PBS through the licensedspectrum bands. CRUs can access the PBS in the band licensed to PUswithout interfering them. The reference network model used in this designis shown in Fig. 3.1.

Typically the PUs are assumed to be static while the CRUs may vary theirposition, but CRU mobility is only partially considered in this design. Thisrouting design is applied to a slowly varying spectrum environment. Also thechannel frequencies available in the area are represented using colors in thisdesign[5]. Always two CRUs can communicate only if they hold a commonchannel in their spectral map. The transmission range of all the CRUs, isconsidered to be the same in the process of neighbor discovery. Also, a kind ofscheduling is assumed in this design to implement the repairing algorithm[10].

The network management information flows through the Common Con-trol Channel (CCC) available in the network. A reliable CCC is importantfor this design performance. It is another research challenge in CRN sce-nario which yet to be addressed seriously. UWB based design of CCC can

11


be assumed to be used in this design as it offers large bandwidth[4].

Figure 3.1: Network Model.

3.2 Cross Layer Design

Several spectrum bands (1, . . . , M) may exist in the area and theCRUs may have different views of the available spectrum bands[5]. So it isnecessary that each CRU in the network to be spectrum agile. The CRUsbecome aware of the spectrum opportunities at every instant through theirspectrum sensing functionality. The CRUs communicate with each otherin a multi-hop fashion which requires an effective spectrum aware routingdesign. The problem of routing in multi-hop CRNs targets the creation andthe maintenance of wireless multi-hop paths among CRUs by deciding boththe relay nodes and the spectrum to be used on each link of the path[5]. Sucha routing solution, typically known as a cross layer design, is proposed in thispaper. This design is also defined to deal with the simultaneous transmissionsof PUs which dynamically change the spectrum availability.

3.3 Routing Metrics

In a routing algorithm, the routing metrics play the role of the criteriabased on which the best route for forwarding packets from source to destina-tion is found. This routing design makes use two simple metrics to calculatethe route:

Hop count: It is defined as the total number of hops between two nodes.According to this design, that route with the minimum hop count fromsource to destination is chosen as the best route.



Adjacent link interference: It is obvious that if two adjacent links usethe same frequency channel for communication, they will interfere witheach other. According to this design, that route in which adjacent linksdo not use the same frequency is chosen as the best route.

RPL allows to use routing metrics and constraints[8]. Hop count is takenas the routing metric. Link color/frequency choice is constrained by adjacentlink interference so it forms the link color constraint.


Chapter 4

Overview of RPL

RPL is the acronym for Routing Protocol for Low power and lossy net-works (LLNs). The key feature of RPL is that it is designed for networkswith lossy links, which are those exposed to high Packet Error Rate (PER)and link outages[7]. It has been developed by Internet Engineering TaskForce (IETF) Routing Over Low Power and Lossy (ROLL) group. It is stillan RFC (Request For Comments), a draft published to seek improvementthrough the comments of experts. It is the main candidate for acting as thestandard routing protocol for IP smart object networks. RPL is a distancevector routing protocol for LLNs that specifies how to build a DestinationOriented Directed Acyclic Graph (DODAG) using an objective function anda set of metrics/constraints[8]. DAG is a directed graph with no cycles andwith all edges oriented towards one or more root nodes. DODAG is a DAGrooted at a single root node. A DAG root is a node within the DAG that hasno outgoing edge and all paths terminate at it. RPL constructs DODAGswith destination as the root node and the source(s) as the leaf node(s). Inter-mediate nodes in a route are the routers. Once the DODAG is constructedrouting is completed and the parent of each node is a potential next hop tothe root node. In the CRN scenario, a colored DODAG is constructed wherethe links are represented in different colors representiong different channelfrequencies[6]. An example of the coloured DODAG is shown in Fig. 4.1.

4.1 RPL Terminology

Some new terms in RPL protocol are,

Rank of a Node in DODAG: A nodes Rank is defined as the nodesindividual position relative to other nodes with respect to a DODAGroot. It strictly increases in the downstream direction of the DAG. The

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Figure 4.1: Colored DODAG.

routing algorithm begins at the root whose rank is zero always. Theexact way it is computed depends on the DAGs Objective Function.

Objective Function: It dictates how nodes select parents and thus theDODAG formation itself. It is responsible for rank computation basedon specific routing metrics and constraints. The design of efficientObjective Functions is still an open research issue[8]. It is not formallydefined in this design.

RPL Instance: A network may consist of one or several DODAGs,which form together an RPL instance. All the DODAGs in an RPLInstance use the same objective function. A network may run multipleRPL instances concurrently; but these instances are logically indepen-dent. A node may join multiple RPL instances, but must only belongto one DODAG within each instance. There are two types of RPL In-stances: local and global. Local RPL Instances always have only a sin-gle DODAG with a single root node; for on-demand discovery of routesto specific destinations. Global instance consists of many DODAGs.

DODAG Version: A specific iteration (Version) of a DODAG. When-ever a global repair which results in complete rerouting occurs, the rootnode upgrades the DODAG version.

4.2 Features of RPL

The features of RPL are[7],

Auto-configuration: Supports dynamic discovery of network paths anddestinations. This feature is guaranteed by the use of the NeighborDiscovery mechanisms.



Self-healing: RPL proves its ability to adapt to logical network topol-ogy changes and node/link failures. RPL implements mechanisms thatchoose more than one parent per node in the DAG to eliminate/ de-crease the risks of failure. RPL triggers recovery mechanisms (globaland local repair) when failures occur.

Loop avoidance and detection: A DAG is acyclic by nature as a nodein a DAG must have a higher rank than all of its parents. RPL includesreactive mechanisms in order to detect loops in case of topology change.

Independence and Transparency: As in the IP architecture, RPL isdesigned to operate over multiple link layers. RPL is able to oper-ate in constrained networks, or in conjunction with highly constraineddevices. Thus, RPL is then independent from data-link layer technolo-gies.

Multiple edge routers: It is possible to construct multiple DAGs inan RPL network and each DAG has a root. A node may belong tomultiple instances, and may act different roles in each instance. Thus,the network will benefit from high availability and load balancing.

4.3 RPL Control Messages

RPL uses several control messages to perform routing. In this routingdesign, only two RPL control messages are considered, DODAG InformationObject (DIO) and DODAG Information Solicitation (DIS)[8]. A typical RPLcontrol message has the format as shown in Fig. 4.2. It consists of a headerwith three fields namely, type, code, and checksum and a message bodywith a message base, and a number of options. RPL is an IPv6 protocol,so type is set as 155 (by Internet Assigned Numbering Authority (IANA)).Code determines the type of the control message. Checksum helps in errorchecking.

4.3.1 DODAG Information Object (DIO)

Type is 0x01 (by IANA). The DIO carries information that allows anode to discover a RPL Instance, learn its configuration parameters, selecta DODAG parent set, and maintain the DODAG[]. It is the root that startsissuing the DIO which passes through the network via multicast to form theDODAG. DIO base object format is shown in Fig. 4.3. The fields in DIOcan be explained as, (i) RPLInstanceID: It is a unique identifier. DODAGs



Figure 4.2: RPL Control Message Format.

with the same RPLInstanceID share the same Objective Function. A localRPLInstanceID has the format as shown in Fig. 4.4. D Flag is set to 0 toindicate that the DODAG ID is the source address. (ii) DODAGVersion-Number: It is the identifier of a DODAG Version. (iii) Rank: Indicates therank of the node sending the DIO. (iv) G Flag: Set to 1 if a DODAG isexpected to satisfy a specific goal; grounded DODAG. (v) MOP: Defines themode of a operation of an RPL instance. It is set to 000 if only upwardroutes are supported. (iv) Prf: Preference level of the current DODAG root;veries from 0x01 to 0x07. (v) DTSN: Destination Advertisement Trigger Se-quence Number: Used to maintain downward routes. (vi) DODAGID: It isthe source address; unique within the scope of an RPL instance.

Finally DIO contains the options field whose format is given in Fig. 4.5.The main fields in it include, (a) Type: Different Option Types are availableaccording to the requirement. When type = 2, it becomes a DAG metriccontainer object. (b) Length gives the length of the options field data. (c)Data is the variable length field that contains data specific to the option.

Figure 4.3: DIO Base Object Format.



Figure 4.4: Local RPLInstanceID.

Figure 4.5: DIO Options Field.

DAG Metric Container Object

It holds the metrics and constraints used for routing using the RPL[9]. Itis contained in the DIO options fields which is propagated through the net-work to accomplish routing. The format of a DAG metric container objectis shown in Fig. 4.6. The main fields are, (i) Type: Indiactes the specificobject (routing metric/constraint)as confirmed by IANA. (ii) Length givesthe length of the object body. (iii) Object body can carry one or more sub-objects. (iv) P flag: Set as 0/1 implies whether all the metrics are recordedalong the path/one or more are not recorded. (v) C flag: Set as 0/1 if theobject is a routing metric/constraint. (vi) O flag: Set as 0/1 if the rout-ing constraint is mandatory/optional; considered only when C = 1. (vii) Rflag: Set as 0/1 if the metrics are recorded along the path/not recorded butaggregated. (viii) A Flag represents whether metric is additive (0x00), mul-tiplicative(0x01), reports a maximum(0x02) or minimum(0x03). (ix) Precindicates precedence of the Routing Metric/Constraint object. Flags field isreserved. The object body varies with the type of objects. The used objectsare of two types,

Hopcount Object: Used to report the number of nodes traversed alongthe path. Type value is 3. It is used as a metric. The object bodyformat is shown in Fig. 4.7. Each visited node simply increments thehopcount field. It helps in finding the shortest path and it determinesthe rank of a node.

Link Color Object: It is used as a metric (can only be recorded) and aconstraint. Type value is 8. Its format is shown in Fig. 4.8. When used



Figure 4.6: DAG Metric Container Object Format.

Figure 4.7: Hopcount Object Body Format.

as a metric it cannot be called as routing metric. It is just a metricthat helps to implement RPL in the CRN scenario. When a node isvisited, the channels available at the node are recorded in the objectbody as different Type-I sub-objects. This helps to find out whetherthere exists a common channel between two neighboring nodes so thata connectivity can be established. The format of Type-I sub-objectis as shown in Fig. 4.9. The fields are, (i) Link color: Holds thechannel/color. (ii) Counter: Set as 0/1 if the color is absent/presentat the node. When used as a constraint, the object body containsType-II sub-objects of the format as shown in Fig. 4.10. It is a routingconstraint which helps to reduce adjacent link interference. The fieldsare, (i) Link color: Holds the channel/color used by the sending nodeto communicate with its parent. (ii) I flag: Set to 0/1 to indicatewhether the color specified must be included/excluded while forming acommunication link with the sending node. In this design, it is set to1. It is used as an optional constraint here.

Figure 4.8: Link Color Object Body Format.



Figure 4.9: Type-I sub-object.

Figure 4.10: Type-II sub-object.

4.3.2 DODAG Information Solicitation (DIS)

Type is 0x00. It is used by a node to retrieve DIO from another neigh-boring node. DIS base object format is shown in Fig. 4.11.

Figure 4.11: DIS Base Object Format.

4.4 DODAG Construction / Routing Algo-

rithm

DODAG construction starts at the destination. The source node sendsa beacon to the CR base-station with the request of data transmission toa particular destination node. The CR base-station can be considered asthe Virtual DODAG Root that has control over every actions in its rangeof control. It intimates the destination about the request and conveys the



source address to it through a beacon. To initiate the construction the root,which is the destination node, broadcasts the DIO control message to allits neighboring nodes. The nodes receiving it will either act as a router ora leaf node. A router will process the DIO and rebroacast it with sufficientmodifications. DODAG construction ends upon reaching the leaf node, whichis the source node, so is the routing. In the DODAG formed, each node willhave a parent list, but the potential next hop to the root for each nodewill be the most prefered parent from it. And the most preferred parent isthat one which mandatorily obeys the link color constraint. When a DIOis being multicasted many neighboring nodes receive it. But different nodesact differently to the received DIO.

When a node that is not yet associated with any DODAG receives theDIO, it will accept the DIO and proceed further only if there exists a commonchannel to communicate with the sender node. If passed in this criteria, itwill (i)add the DIO sender address to its parent list, (ii) compute its rankby adding one to the sender nodes rank, (iii) allocate a channel for the linkwith the sender node, and (iv) forward the DIO message with the updatedrank information.

When a node that is associated with a DODAG receives the DIO, it willaccept the DIO and proceed further only if the DIO has the same RPLIn-stanceID, VersionNumber, and DODAGID as the DIO it previously received.Once it also passes the common channel check, DIO is processed. Here itwill compute its rank according the received DIO and compare it with itsown rank. If own rank is greater than the newly computed one, the senderis discarded and the location in DODAG is maintained. If own rank is equalto the newly computed one, the sender is added to the parent list but thelocation in DODAG is maintained. If own rank is less than the newly com-puted one, the sender is added to the parent list, the existing list is discardedand the node moves to an improved location in DODAG and finally allocatesa channel for the link with the sender node based on the constraint. Theoperation of a router can be summarized in a flow chart as shown in Fig.4.12. and also as an algorithm as shown in Algorithm 1.



Receive DIO

Receive DIOthe 1st time

Satisfy thecriteria

Discardthe packet

Any commonchannel?

Discardthe packet

Add senderto parent list

Computethe rank

Allocatea channel

based on theconstraint

Forward DIOto others inmulticast

Any commonchannel?

Rank < OwnRank

Improveits locationand get thelower rank

Discard theparents withhigher rank

Allocatea channel

based on theconstraint

Rank = OwnRank

Maintain thelocation in

the DODAG

no

yes

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yes

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no no

Figure 4.12: Operation of a Router During Routing



Algorithm 1 Operation of a Router in Routing1: Receive a DIO2: if Receive a DIO the first time then3: if A common channel exists then4: Add sender to the parent list5: Compute the rank6: Allocate a channel based on the constraint7: Forward DIO to others in multicast8: else9: Discard the packet

10: end if11: else if Satisfy required criteria then12: if A common channel exists then13: if Rank < Own Rank then14: Improve its location and get the lower rank15: Discard the parents with higher rank16: Do steps 6-717: else if Rank = Own Rank then18: Do steps 4-719: else20: Maintain the location in the DODAG21: Forward DIO to others in multicast22: end if23: else24: Discard the packet25: end if26: else27: Discard the packet28: end if


Chapter 5

Route Repair Using TrickleAlgorithm

Route repair is an eminent feature required whenever a routing protocolis defined. It refers to the capability of repairing a defined route when alink/node failure occurs. In a CRN scenario, link outages are so commondue to channel unavailability upon the appearance of PUs in their licensedbands when they are being used by the CR users. Link failures are onlyconsidered in this design. RPL offers two types of repair mechanisms[8]which are made possible through the trickle algorithm[10],

Local repair: Triggered by a node when it detects a link failure. Thisdesign offers two types of local repair mechanisms upon the failureof the link with its default parent, (i) find another available commonchannel/color to be used in the link, (ii) find an alternate parent withan available channel/color from the parent list. Performance of boththe mechanisms depend on the efficiency of the CR users spectrumsensing functionality.

Global repair: Triggered by the DODAG root if local repairs are notefficient for network recovery due to several inconsistencies. The wholeroute is repaired by initiating a new DODAG version for the globalrepair operation. Nodes in the new DODAG version can choose a newposition whose rank is neither constrained by nor dependent on theirprevious rank within the old DODAG version[].

These mechanisms are made possible through the Trickle algorithm. TheTrickle algorithm allows nodes in a lossy shared medium (e.g., LLNs) to ex-change information in a highly robust, energy efficient, simple, and scalable

24


manner[10]. Each node periodically generates DIO messages, the trickle mes-sages, triggered by the Trickle timer which helps in identifying the networkinconsistencies and hence trigger a repair operation. The message transmis-sion frequency is optimised based on network conditions. The frequency isincreased whenever an inconsistency is identified for faster recovery from thefailure, and decreased in the opposite condition. This helps in optimizing thecontrol plane overhead based on network conditions.

5.1 Scheduling

Some kind of scheduling is required in implementing the Trickle algorithm(in designing the Trickle parameters). It is the process of assigning a sched-ule for the transmission of data packets without collision. A traffic awarescheduling is considered here[11]. According to this scheduling, a route canbe even scheduled (all nodes with even rank transmit in even time slots) orodd scheduled (all nodes with even rank transmit in odd time slots). Thishelps to avoid collision. The nodes transmit and receive in alternate times-lots. Source sends the hop count and total estimated packet number to thebase station so that it can decide on the scheduling. If the rank of source iseven, the route is odd scheduled. The schedule length can be calculated as,

Ls = (2 Qs) + (Hopcount 2) (5.1)where Qs is the number of scheduled packets and Hopcount gives the numberof hops from source to destination. In this scheduling, the transmission timeof a packet can be calculated as,

Txn time = timeslotlength Hopcount (5.2)where timeslotlength gives the length of the time slot allocated per packet.

5.2 Trickle Parameters and Variables

There are certain parameters and variables based on which a Trickle timerperforms its fuction[11]. The timer runs for a defined interval and has threeconfiguration parameters,

The minimum interval size, Imin: Two or three times the transmissiontime for k data packets.

Imin = 2 Txn time k (5.3)



The maximum interval size, Imax, number of doublings of the Iminrequired to reach the maximum interval time:

Maximum interval time, I max = Imin 2Imax (5.4)

It is actually given by,I max = Ls/4 (5.5)

Imax = log2(I max/Imin) (5.6)

The redundancy constant, k, is a natural number: Atleast a consistentDIO from the default parent must arrive at a node in an interval, so k= 1.

The variables are,

I, the current interval size. t, a time within the current interval. c, a counter.Initially, the timer duration is set to Imin, which will be doubled Imax

times until it reaches the maximum value. For any detected change in theDODAG, the timer duration is reset to Imin to overcome the situation asfast as possible.

5.3 Repairing Algorithm

The Trickle algorithm starts execution with the data transmission. At thebeginning, interval size is set at I = Imin. At a particular scheduled time,t [I/2, I), the CR base-station intimates the DODAG root to transmit theDIO. The root then multicasts the DIO to all its neighbors after modifying itaccording to the results of channel sensing. Among the neighbors receivingit, only those involved in current data transmission and those with root asdefault parent will only accept the DIO. On accepting the DIO it will gofor the consistency check (whether the channel color used with the parent ispresent in the set of common colors between the nodes) using the spectrumsensing functionality.

If the color is found absent upon the consistency check, the node calls fora local repair. If an alternate common channel is found absent between thenodes, the node sends a DIS message to the alternate parents in its parent list



to find a credible path to the root. Now if in all ways the local repair is foundinsufficient, the algorithm calls for a global repair, which is intimated by thenode to the base-station. After global repair, data transmission is restartedfor the remaining number of packets to be delivered to the destination.

If the DIO found consistent, the node will just multicast its modified DIOto its neighbors, after incrementing its consistency counter (c) by one. Andthe next node in the route will perform the same steps as the previous nodeupon the receival of the new DIO. The interval ends at I and each node willsend its c value to its default parent which ultimately reaches the root. Thebase-station will check whether at any node c < k. If found so, it will resetthe trickle timer interval to Imin, else the interval time is doubled. If thenew I > I max, the I is set at the maximum interval time. The new intervalthen starts and the process repeats. The function of a router in the repairingis summarized as an algorithm in Algorithm 2 and a flow chart given in Fig.5.1.

Algorithm 2 Operation of a Router in Route Repairing1: c = 02: Receive a DIO3: if A node in route then4: if Received DIO consistent then5: c = 16: Multicast the modified DIO7: else if Alternate common channel exists then8: Local repair occurs9: c = 0

10: Multicast the modified DIO11: else if Valid alternate parent exists then12: Do steps 8-1013: else14: Global repair occurs15: end if16: else17: Discard the packet18: end if



Receivea DIO

Node inroute

Consistent

Discardthe packet

c=1

Multicastthe

modifiedDIO

Commoncolor

betweennodes

Localrepair

c=0

Validalternateparent

Globalrepair

no

yes

yes

no

yes

no

yes

no

Figure 5.1: Operation of a Router During Route Repairing


Chapter 6

Simulation Results andAnalysis

This section highlights the results obtained through a MATLAB sim-ulation. The topology and channel availability of each node used in thissimulation are as shown in Table 6.1. The topology obtained from simula-tion is shown in Fig. 6.1. Over an area of 200m x 200m, about 21 nodes(A, B, C,... U) are homogeneously distributed. Also six frequency channelsare allocated randomly over the area which are represented using the colorsred, green, blue, yellow, black and magenta. It is assumed that this channelavailability at each node is obtained through any efficient spectrum sensingalgorithm available in literature[2].

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Table 6.1: Topology and Spectrum Availability

Node Position Channel AvailabilityA (48.5,10.6) red,yellow,green,blackB (2.8,52.3) magenta,blueC (6.4,29.7) magenta,blue,blackD (39.6,18.5) red,green,yellow,blackE (19.4,56.1) magenta,blueF (17.8,22.7) blue,blackG (53.3,12.8) red,yellowH (8.6,11.2) blue,magenta,blackI (11.8,18.4) magenta,blue,blackJ (45.1,52.4) red,greenK (8.7,58.3) magenta,blueL (49.0,41.3) red,greenM (2.3,13.5) magenta,blue,blackN (41.7,41.3) red,greenO (52.1,47.9) red,green,yellowP (25.0,40.0) red,blueQ (33.3,48.5) red,blueR (35.0,33.3) red,greenS (15.0,45.0) magenta,blueT (29.1,25.8) red,blackU (19.5,34.2) red,blue,black

6.1 Routing

Among the nodes, assume the source node to be M and the destinationnode to be J. Fig. 6.2. shows all the possible paths from M to J formedusing the routing metrics mentioned in Chapter 3. Fig. 6.3. shows the defaultroute (that route which mandatorily obeys the link color constraint) used fortraffic flow chosen from the possible paths. It can be observed from the figurethat adjacent links do not use the same color leading to a minimum adjacentlink interference. Fig. 6.4. shows the corresponding DODAG formed. Thedefault route is only highlighted using different colors in the DODAG. It canbe seen that destination is the root node and source is a leaf node.



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Figure 6.2: Topology Showing Multiple Paths.

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Figure 6.3: Topology Showing Default Route.



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Figure 6.4: DODAG Formed.

6.2 Route Repairing

It is presumed in the simulation that a single packet is sent in a timeslot. Accordingly, all the trickle parameters are estimated before the exe-cution starts. To understand route repairing, first assume that the channelmagenta becomes unavailable during the data transmission. Channel ma-genta forms the route between the nodes, M and H. It gets repalced byanother channel black which is common between these nodes through localrepair. It is shown in Fig. 6.5.

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Figure 6.5: Locally Repaired Route with Alternate Channel



Then assume that the channel black becomes unavailable during the datatransmission. Channel black forms the route between the nodes, F andT. Local repair takes place here by choosing an existing alternate path asthe default route which is shown in Fig. 6.6.

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Figure 6.6: Locally Repaired Route with Alternate Path.

Now assume that the channel red becomes unavailable during the datatransmission. Channel red forms the route between the nodes, T andR and N and J. Between J and N, an alternate channel, green isfound through sensing to continue the transmission as shown in Fig. 6.7.

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Figure 6.7: Locally Repaired Route with Alternate Channel.



But between T and R, local repair cannot find a channel or an alternatepath to continue transmission. In such a case, global rapir occurs. Whenthe global rapair occurs, it is assumed that the topology changes as the CRusers are mobile and complete rerouting occurs with an upgraded version ofDIO. It is also assumed that the topology changes randomly when this repairoccurs. The new topology is shown in Fig. 6.8. Fig. 6.9. shows the multiplepaths formed. And the route formed after global repair is shown in Fig. 6.10.and Fig. 6.11. shows the corresponding DODAG formed.

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Figure 6.8: New Topology.

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Figure 6.9: Topology Showing Multiple Paths After Global Repair.



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Figure 6.10: New Route After the Global Repair.

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Figure 6.11: New DODAG Formed.



6.3 Performance Analysis

In this design, routing is performed through the transmission of a numberof control packets. The control plane overhead is an important routing char-acteristic in RPL. It is imperative to bound the control plane overhead[12].And it is made possible by the use of trickle timers by eliminating the redun-dant messages. Fig 6.12. shows the data and control packet comparison foreach in the topology in normal routing and data transmission condition withzero link outage. The x axis indicates the node ID in the network and the yaxis indicates the number of packets through each node. It is clear from theresult that the control packet overhead is negligible when compared to thedata packtes being transmitted through the nodes.

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Figure 6.12: Data and Control Packet Flow Comparison.

Several conditions may occur in the network during transmission. Fig.6.13. shows the comparison of control plane overhead under different con-ditions. The x axis indicates the node ID in the network and the y axisindicates the number of packets through each node. It is clear from the fig-ure that the control plane overhead is the maximum through the networkwhen the global repair occurs. When a local repair occurs by finding the al-ternate path, there is an increase in control plane overhead due to the extra



flow of DIS messages to retrieve DIO from nodes in alternate path.

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Figure 6.13: Control Packet Overhead Under Different Routing Conditions.


Chapter 7

Conclusion

In this work, a new routing protocol based on RPL is being introducedinto the CRN scenario. It is found that CRs being smart, RPL could beeffectively implemented in a CRN. It also supports the cross layer designwhich is widely accepted as an effective CRN routing solution. An efficientroute repairing algorithm has also been implemented. Route repairing isalways a relevant part of routing algorithms in a CRN scenario. Simulationresults show that the proposed routing design works efficiently in the CRNscenario with minimum control packet overhead. Overall, RPL is found tobe a suitable routing protocol that can be carried out into the real CRNscenario.

This work implements RPL using very simple routing metrics and con-straints. RPL is flexible enough to allow the designer to use any metric basedon the network requirement. Future work of this thesis work lies in develop-ing efficient routing metrics and constraints suitable for both RPL and CRNscenario.

38

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List of Publications

[1] Irin Sajan, Ebin M. Manuel, Cooperative Jarque-Bera Statistic BasedSpectrum Sensing Using MIMO Decision Fusion, in Proceedings ofFourth International Conference on Advances in Computing and Com-munications (ICACC), 27-29 Aug., 2014, pp.274-277.

[2] Irin Sajan, Ebin M. Manuel, Cross Layer Routing Design Based on RPLfor Multi-hop Cognitive Radio Networks, in International Conference onContemporary Computing and Informatics,November, 2014.[Accepted]

[3] Irin Sajan, Ebin M. Manuel, Cross Layer Routing Design Based on RPLfor Multi-hop Cognitive Radio Networks, in IEEE International Con-ference on Signal Processing, Informatics, Communication and EnergySystems (IEEE SPICES), February, 2015.[Communicated]

[4] Irin Sajan, Ebin M. Manuel, Cross Layer Routing Algorithm Based onRPL for Multi-hop Cognitive Radio Networks, in International Journalof Networking and Communication (IJNC), December, 2014.[Communi-cated]

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Documents

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