reliability in wireless sensor networks

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Sri Lanka Institute of Information Technology

Project Proposal Report

Reliable , Low Power Consumption , IPv6 Compatible AndSecured Ad-Hoc Network Routing Protocol

Comprehensive Design/Analysis Projects

February 21, 2012

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Declaration

I declare that the this project report or part of it was not a copy of a doc-ument done by any organization, university any other institute or a previous

student project group at SLIIT and was not copied from the Internet or othersources.

Group Member :

Reg. No Name SignatureIT 09 0609 82 A.A.M Chathuranga

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Contents

1 INTRODUCTION 5

1.1 Wireless Sensor Networks . . . . . . . . . . . . . . . . . . . . . . 5

1.2 Reliability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51.3 Low-Power Consumption . . . . . . . . . . . . . . . . . . . . . . 51.4 Internet Protocol Version 6 . . . . . . . . . . . . . . . . . . . . . 51.5 Security . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2 Objectives 7

2.1 The Primary Ob jective . . . . . . . . . . . . . . . . . . . . . . . . 72.2 Secondary Ob jectives . . . . . . . . . . . . . . . . . . . . . . . . . 7

3 Methodology 8

3.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83.1.1 Wireless Sensor Networks . . . . . . . . . . . . . . . . . . 83.1.2 Uses of Wireless Sensor Networks . . . . . . . . . . . . . . 8

3.1.3 Mote Hardware . . . . . . . . . . . . . . . . . . . . . . . . 103.1.4 The Contiki Operating System . . . . . . . . . . . . . . . 103.1.5 Application simulator . . . . . . . . . . . . . . . . . . . . 123.1.6 Design overview . . . . . . . . . . . . . . . . . . . . . . . 133.1.7 Routing in Wireless Sensor Networks . . . . . . . . . . . . 14

3.2 Reliability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143.2.1 Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143.2.2 Solution Development . . . . . . . . . . . . . . . . . . . . 15

4 Project Gantt Chart 19

5 Description of Personal and Facilities 20

List of Tables

1 Personal Description . . . . . . . . . . . . . . . . . . . . . . . . . 20

List of Figures

1 Device drivers on a hardware vs. simulation platform . . . . . . . 122 The simulation loop . . . . . . . . . . . . . . . . . . . . . . . . . 133 A simulated sensor node . . . . . . . . . . . . . . . . . . . . . . . 134 S1 is using erasure code, S2 is using thick path and S3 is using

alternative hop . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

5 Erasure Code Mechanism . . . . . . . . . . . . . . . . . . . . . . 176 Gantt Chart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

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Abstract

A mobile ad-hoc network (MANET) is a self-configuring network where nodes,connected by wireless links, can move freely and thus the topology of the net-work changes constantly. Wireless mobile ad-hoc networks are characterized asnetworks without any physical connections. In these networks there is no fixedtopology due to the mobility of nodes, interference, multipath propagation andpath loss. A great body of knowledge about MANETs has been produced andmany researchers in the field are now trying to apply this knowledge to thefield of wireless sensor networks (WSN). The reasoning is that both MANETsand WSNs are auto-configurable networks of nodes connected by wireless links,where resources are scarce, and where traditional protocols and networking al-gorithms are inadequate. Many applications in Wireless Sensor Networks, in-cluding structure monitoring, require collecting all data without loss from nodes.End-to-end retransmission, which is used in the Internet for reliable transport,becomes very inefficient in Wireless Sensor Networks, since wireless commu-

nication, and constrained resources pose new challenges. There are numerousapplicable protocols for ad hoc networks, but one confusing problem is the vastnumber of separate protocols. Each of these protocols is designed to performits task as well as it is possible according to its design criteria. The protocol tobe developed must cover all states of a specified network and never is allowedto consume too much network resources by protocol overhead traffic.

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1 INTRODUCTION

1.1 Wireless Sensor Networks

A Wireless Sensor Network (WSN) consists of sensor nodes and a few controlnodes also known as base stations. Every sensor node has one or more com-ponents to sense the conditions of its immediate surroundings, which could betemperature, pressure, humidity etc. and processing and communication com-ponents to do minor computations on the collected data and communicate withits immediate neighbor node which could be a base station or another sensornode through wireless links. WSNs have recently emerged as an important fieldmeans study with the physical world. Sensor nodes usually scatter randomlyaround the field and will form a sensor network after the deployment in an adhoc manner to fulfill certain tasks. After deployment these sensor nodes arequickly self-organized to gather information in an ad hoc network.

1.2 ReliabilityChallenges to achieving reliability on Wireless Sensor Networks can be dividedto three main categories. First problems are related to the wireless communica-tion. The asymmetries of links makes link quality estimation hard and invalidatemany assumptions made in other environments. Correlated losses due to obsta-cles, interference, can lead to consecutive losses, decreasing the effectiveness oferasure code. Weak correlation between quality and distance, hidden terminalproblems, and dynamic change of connectivity complicates the situation further.

1.3 Low-Power Consumption

Normally nodes in the wireless sensor networks are battery powered. So they

are expecting to work for many years, in order to work long period of time theymust have some kind of an algorithm to save power that they are consuming.so the best practice is to implement a good routing protocol for wireless sensornetwork. In order to do that we need what are the existing technologies that arealready used at the past few years for lower the power consumption in wirelesssensor networks.

1.4 Internet Protocol Version 6

Internet Protocol Version 6 (IPv6) is the designated successor of IPv4 as thenetwork protocol for the Internet. To overcome the increase in networked deviceswhich will outnumber the conventional computer hosts Ipv6 was introduced asit expands the address space from 32 bits to 128 bits. The most widely used

link technologies evenly split the IPv6 address space into a subnet prefix thatuniquely identify the subnet within the internet and an interface identifier thatuniquely identify an interface within the subnet. Here in this project proposalas our research topic stands, we are trying to overcome the current issues inwireless sensor networks; concentrating on its Reliability, Power management,Security and Ipv6 Compatibility.

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1.5 Security

Wireless networks are vulnerable to security attacks due to the broadcast na-ture of the transmission medium. Furthermore, wireless sensor networks have

an additional vulnerability because nodes are often placed in a hostile or dan-gerous environment where they are not physically safe. In many applications,the data obtained by the sensing nodes needs to be kept confidential and it hasto be authentic. In the absence of security a false or malicious node could inter-cept private information, or could send false messages to nodes in the network.The major attacks are: Eavesdropping, Spoof Attack, Denial of Service (DOS),Worm hole attack, Sinkhole attack, Sybil attack, Selective Forwarding attack,Passive information gathering, Node capturing, False or malicious node, Helloflood attack etc. In this project the focus on providing security by prevent-ing DoS Attacks, eavesdropping and Spoofing with the use of Asymmetric KeyCryptography.

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2 Objectives

2.1 The Primary Objective

Implement reliable,low power consumption,IPV6 compatible and securedAd-hoc routing protocol for MANET.

2.2 Secondary Objectives

Developing a protocol which is reliable and low power consuming.

Make the protocol IPV6 compatible and secured.

Research on wireless sensor networks and Ad-hoc routing protocols.

Research on mobile Ad-hoc Networks.

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3 Methodology

3.1 Background

3.1.1 Wireless Sensor Networks

Wireless sensor networks are comprised of a large number of small sensor de-vices which are commonly known as motes. These devices range in size fromabout the size of a matchbox to the size of a pen tip. The motes have a lowclock rate processor on board as well as a small amount of memory. They alsohave some form of sensor attached to them in order to monitor some physicalproperty. Collectively these motes are able to form themselves into autonomousad-hoc networks using a variety of communication mediums. The most commonmedium used is radio frequency communication. In addition to being able toform networks autonomously protocols exist to allow sensor networks to recon-figure dynamically around moving nodes. These networks of motes are able tocollect, process and store data from sensors. They are capable of sharing data

with each other and of transmitting data through the network back to a basestation.

3.1.2 Uses of Wireless Sensor Networks

Wireless sensor networks are extremely versatile and can be deployed in manydifferent situations. The individual motes that make up a sensor network arerelatively inexpensive and it is estimated that motes will soon cost as little as200/= each. They also require no maintenance once deployed as they automat-ically form a wireless ad-hoc network which is completely autonomous. Someareas in which sensor network technology could be used are discussed below.

Military Applications

The Smart Dust project [1]at the University of California Berkeley wassponsored by DARPA (Defense Advanced Research Projects Agency), theAmerican Department of Defense central research and development orga-nization. Because of this a lot of the research at UC Berkeley has beenfocused on the military applications of wireless sensor network technology.

Smart Buildings

There are many potential applications for sensor networks that are de-ployed within buildings. Example applications include structural integritychecking, energy management and climate control.

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Habitat Monitoring of Seabird Colonies

Sensor networks have also been used to monitor the habitat of seabirdcolonies. On Great Duck Island in Maine a sensor network is being used

to monitor the microclimates in and around the nesting burrows of theLeachs Storm Petrel [2]. The project is collaboration between the IntelResearch laboratory at Berkeley, the College of the Atlantic in Bar Harborand the University of California Berkeley. The goal of the project is to de-velop a habitat monitoring kit to enable non-intrusive and non-disruptivemonitoring of wildlife.

Virtual Input Devices

By equipping motes with accelerometers and attaching them to an ob jectit is possible to build a sensor network capable of monitoring the move-ment of an object. Each mote in the network would take samples fromits on board accelerometer and pass it back to a computer via a wire-less network. The computer would then interpret the data received fromthe motes to determine the movement of the object. This data could beinterpreted in many different ways. Some potential applications includea virtual keyboard, a wearable mouse, sculpting of virtual clay, virtualmusical instruments, gesture and sign language recognition and computergame controllers.

Forest Fire Tracking

Forest fire tracking is another application area for which sensor networksare being developed and deployed. The FireBug project [3] has used asensor network to monitor the controlled burning of a forest in Califor-

nia. The project is collaboration between the department of Civil andEnvironmental Engineering, the department of Landscape Architectureand Environmental Planning, the department of Earth and Planetary Sci-ences, and the department of Electrical Engineering and Computer Scienceat UC Berkeley.

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3.1.3 Mote Hardware

Over the last few years many different versions of motes have been designed andbuilt by various companies and institutions. The size of these motes varies from

roughly the size of a matchbox to the size of a pen tip. MEMS (Micro Elec-tromechanical Systems) technology has been used to miniaturize componentswith an aim of implementing a mote on a single chip that fits into a volume ofno more than a cubic millimeter. These motes have been nicknamed SmartDust.There are different types of motes available, considering different applications.Such as;

Radio Frequency (RF) Mote

Mini Mote

weC Mote

Mica Mote

Mica2 Mote

3.1.4 The Contiki Operating System

Contiki is an operating system designed for memory constrained environments,such as the nodes used in WSN. It is built around an event-driven kernel, andfeatures include dynamic loading and unloading of individual programs and ser-vices, and optional preprocess pre-emptive multi-threading. It also supports afull TCP/IP stack via the uIP library, as well as the programming abstractionProtothreads. Contiki is implemented in the C language and has been designed

to be easily portable to new platforms. It has been ported to more than 20different platforms since its release 2003 [4].

1. Event-based kernel

In a purely event-based system, a process is implemented as an eventhandler, letting different blocks of code execute depending on which eventis given. These blocks are always allowed to run to completion once called.Since a single code block will never be interrupted, these blocks can bedesigned so that they may all share the same stack. Compared to a multi-threaded model this requires less memory and computation overhead whenhaving several concurrent processes. In Contiki, a process consists of anevent handler and an optional poll handler function. The Contiki kernelholds the event scheduler that dispatches events to processes and peri-odically polls processes that registered a poll handler function. It uses asingle stack for all processes, which is rewound between each invocationof an event handler [5].

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2. uIP

uIP (micro IP) is a small TCP/IP implementation suitable for sensornodes and other resource limited devices. It is designed to have only the

absolute minimum of required features for a full TCP/IP stack, and doesnot implement UDP but focuses on the TCP, ICMP and IP protocols [6].

3. Java Native Interface

Java Native Interface (JNI) is built into the Java virtual machine (VM)and provides a way to locate and invoke native methods on a platform.This way code running inside the JVM can interoperate with applicationswritten in other programming languages such as C or Assembly. Reasonsfor using JNI may be to reuse libraries and APIs not implemented in Java,or to speed up calculations by using Assembly code.

4. Process memory structures

A regular process memory consists of several different memory areas, ormemory sections. Each section is a range of addresses without gaps andall data in a section is treated the same. Which sections exist varies be-tween platforms but simplied there are at least three sections, these arethe text, data and bss section. The text section holds the pro-gram code and constants, and is usually unalterable when the programis executing. The data section holds initialized variables and is alterable.The bss section is similar to the data section but holds uninitialized vari-ables. The reason for having a bss section is to save space in compiledbinaries. Since all of the data in the section is zeroed when the programis started, only the length of the section has to be saved in the binary, not

all the zeroes.

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3.1.5 Application simulator

T he COOJA Simulator is a Contiki OS application simulator as opposed toa sensor node emulator. When a user creates a new node type, the resulting

Contiki system is compiled for the simulation platform, in the regular Contikienvironment. While the drivers of a hardware platform operate on hardware, thedrivers of the simulation platform work against the Java part of the simulator.But since the simulation platform supports the same devices as any hardwareplatform, there is no difference between them from an application viewpoint.The same application code compiles and executes on both platforms. So thehardware peripherals of a platform are not emulated, they are replaced by othersimulated devices. An alternative would be to emulate all hardware of a sensornode, which could give more precise results but also would limit the simulator toone or a couple of supported hardware platforms. By using the above method,different hardware platforms can be supported simply by puzzling together allwanted drivers. Figure 1.0 shows a comparison of device drivers on a hardwareplatform and in the simulator. The left part illustrates how an application usesa driver to interact with hardware, whereas in the right part the driver pretendsto be hardware but instead communicates with the simulator.

Figure 1: Device drivers on a hardware vs. simulation platform

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3.1.6 Design overview

Simplified, a COOJA simulation consists of a number of nodes being simu-lated. Each node is connected to a node type, of of a node type. When the

simulation is running, all of the nodes get to act in turn. And when all nodeshave acted once the simulation time is updated and then the process is repeated

Figure 2: The simulation loop

More specially, each node also has its own node memory and a number ofnode interfaces. The memory consists of one or several memory segments, eachwith a start address and data. Together the memory segments must define allinteresting and needed parts of an entire simulated Contiki OS.The interfaces act on the memory and simulate node devices such as a clock or aradio transmitter. For example, when the time changes a clock interface shouldupdate some specic time variable. An that variable resides in the node memoryof that node. The node type is the bridge between the node explained above, anda loaded Contiki OS executing node specific code. This is from where the simu-

lated Contiki OS (the core) is initialized, and the initial memory is created.And all nodes of the same type is linked to the same loaded Contiki OS. Thenode type also performs variable name to address mapping. This implies that ifthe above clock interface wants to change the core time variable timevar, thenode type is asked what address that variable is at. When a node gets to act,the node type is responsible for linking the node to its corresponding Contiki OS.

Figure 3: A simulated sensor node

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3.1.7 Routing in Wireless Sensor Networks

There are several factors which limit what routing protocols can be used inwireless sensor networks. The individual motes within the sensor network have

limited resources. These resources include battery power, processing powerand memory. The latter two factors mean that any protocols employed withinthe network must not take up too much processor resources and should use aslittle memory as possible. In order to allow each mote to function for as longas possible the routing protocols employed must also be energy efficient. Thetopology of a sensor network may also influence protocol choice. This includesthe number of nodes and the node density as well as the data movement withinthe network. For example, networks with a fixed base station receiving data fromremote nodes require different protocols from networks where nodes send datato a mobile base station such as in the Pursuit-Evasion Game demonstration.

3.2 Reliability

3.2.1 Problem

Challenges to achieving reliability on Wireless Sensor Networks can be dividedto three main categories. First problems are related to the wireless communica-tion. The asymmetries of links makes link quality estimation hard and invalidatemany assumptions made in other environments. Correlated losses due to obsta-cles, interference, can lead to consecutive losses, decreasing the effectiveness oferasure code. Weak correlation between quality and distance, hidden terminalproblems, and dynamic change of connectivity complicates the situation further.

The second sort of problems comes from the constrained resources of Wire-less Sensor Networks motes. Mote has small computational power and memoryspace. Furthermore, its communication bandwidth is narrow. Therefore we cantrun a complicated algorithm to achieve reliability: the algorithms run on motesshould not send too much overhead traffic, and should not be computationallyor storage intensive. Finally, from a software engineering standpoint, diverserouting layers add more challenges. Since motes are resource constrained, ap-plications tend to make heavy use of customization and cross-layer optimizations[7]. Therefore, there are different routing layers customized for specific purpose:even if we can use a general purpose, point-to-point routing for disseminationof information or collection of data, this approach is very inefficient for somespecific cases.

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For collecting data (convergence routing), each node only needs to keeptrack of which nodes are candidates for its parent. This reduces the burden ofkeeping additional information to support routing to any node. Dissemination ofinformation, such as code image distribution, is similar to multicast (divergence

routing). In this case, we can benefit from the broadcast nature of wirelesscommunication. By injecting one packet into channel, all neighboring nodescan hear the packet. Compared to sending packet to each single receiver, thiscan save a huge effort. So there are three main routing layers categories:

point-to point routing

convergence routing

divergence routing

One transport layer or one method may not work for all three cases well. Butit is not a good idea to keep three separate versions of reliable transfer either.At least it will be desirable to share some components if possible, whereverit might be located in network stack. Ultimately, we seek to find common re-liability primitives or principles that can be used even in different routing layers.

3.2.2 Solution Development

we examine diverse options for improving reliability over multiple-hops, focus-ing mainly on point-to-point routing. First of all, it is worthwhile looking atfundamental factors that determine reliability. Then we look at possible optionswhich improve each factor. Let us simplistically look at the following equation

number of packets received = Psuccess X number of packets sent

The goal is to increase number of packets received sufficiently so that we can getall data. Even though it is also important which packets are received. The basiclimitation is delivering a sufficient amount of packets. This in turn amounts toincreasing either number of packets sent or increasing the probability to getthrough Psuccess.

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Figure 4: S1 is using erasure code, S2 is using thick path and S3 is usingalternative hop

Increasing the number of packets sent can be interpreted as adding redun-dancy to information. One option is retransmission. End-to-end retransmissionis used in TCP on the Internet. Link-level retransmission is used in wirelesscommunication where loss rate of link is high. Adding redundant data is alsoan option. Sending an additional parity packet for some number of previouspackets is a good example. Erasure codes can be thought as a generalization ofparity code. Rather than sending one additional packet, erasure code can sendmultiple additional packets. In parity packet case, any M out of M+1 packetswill reconstruct original M data. Likewise, erasure code enables reconstruction

of M original data packets if any M out of M + R packets are received. In Figure2, S1 is sending data with erasure code. We can also exploit spatial redundancyalong the path. As S2 in Figure 2, thick path can be used as in [8]. Everynode within nearby area along the path will participate in transferring data.This method adds in-network data redundancy. Increasing the probability ofsuccessful delivery and changing the loss distribution can solve problems whichare hard to overcome by redundancy alone. Let us assume Psuccess is not ran-domly distributed. Erasure code can survive up to R losses. When consecutiveR+1 or more packets are lost, erasure code is unable to reconstruct the originaldata. This phenomenon happens in wireless communication. For example, aftera link failure, it takes time for the routing table to be updated. Until then, allpackets sent to that link will fail, introducing consecutive failures. In this situa-tion, we can quickly try an alternative next hop. This is shown as S3 in Figure 2.

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LINK-LEVEL RETRANSMISSION

The loss rate on wireless links is much higher than that of wired links,and this effect accumulates quickly as the number of hops increases. For

example, when loss rate is 10% per hop, after 15 hops loss rate becomes80%! If a message is lost at the n th hop, all previous n - 1 transfersbecome wasted effort. To deliver the packet to nth hop again, we needn 1 additional transfers, if all n - 1 transfers succeed. With link-level re-transmission, just one retransmission can bring packet to the same point.For efficient use of the wireless channel, link-level retransmission is a veryattractive choice. There are drawbacks in link-level retransmission, whenused in some specific contexts. When retransmission is implemented withlink-level acknowledgments, there is a decrease in channel utilization. Thisoverhead can, however, be mitigated in some contexts by using techniquessuch as passive acknowledgments, in which the next hop transmission isinterpreted as an acknowledgment. Another minor downside is that the

middle node needs to hold the packets in a buffer until it receives ac-knowledgement from the next hop. Lastly, the delivery time depends onthe number of retransmissions along the route, so the end-to-end roundtrip time (RTT) can vary significantly. This situation makes end-to-endretransmission inefficient. Since we do not clearly know the RTT, an (over-estimated) upper bound needs to be used. The sender holds its buffer fora longer time than necessary. Holding memory space for a long time isnot desirable in resource-constrained Wireless Sensor Networks.

ERASURE CODE

Another important mechanism we hope to employ is erasure coding. It isa scheme with which we can reconstruct m original messages by receiving

any m out of n code words (n m).If n is sufficiently large compared to theloss rate, we can achieve high reliability without retransmission. Figure 3shows high level mechanism of erasure code.

Figure 5: Erasure Code Mechanism

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ALTERNATIVE ROUTE

Adding an alternative route in the case of the failure of a given link isyet another way to increase reliability. When a link between two nodes

fails, the messages sent through that link will successively be dropped,until the link estimation component is triggered and selects a new route.This process, if prevalent, can eliminate the benefits gained from erasurecoding, since many consecutive losses will very likely to be above the tol-erance of redundancy added by erasure code. In this case, it should beclear that link-level retransmissions are of no great help, unless used to aprohibitively long extent. A sensible strategy, then, is to detect the failureas soon as possible, and send the packet to an alternative route, if possible.

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4 Project Timeline

Figure 6: Gantt Chart for Project

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5 Description of Personal and Facilities

Registration No. Name Workload

IT09060982 A.A.M Chathuranga Research on Wireless sensor Networks regarding reliability.Define problems, issues regarding reliability of manets and

propose suitable solutions.

Familiarize with Contiki OS.

Familiarize with COOJA Simulator.

Develop mechanism to combine reliable solutions with the

protocol solution.

Track progress of project work.

IT09060050 B.P.R Perera Research on Wireless sensor Networks regarding reliability.

Define problems, issues regarding power consumption of

manets and propose suitable solutions.

Familiarize with Contiki OS.

Familiarize with COOJA Simulator.

Consider low power consuming protocol practices in developing

solution.

Share knowledge on programming concepts.

IT09164864 Sandeepana M Research on Wireless sensor Networks regarding compatibility

of IPV6.

Define problems, issues regarding compatibility of IPV6 of

manets and propose suitable solutions.

Define a methodology to work out IPV4 addresses when

connecting to internet.

Define methodology for developing a protocol.

Implement a IPV6 compatible protocol on top of uIPV6 stack.

Test on solution and gather results.

IT09080096 P.R Karunaweera Research on Wireless sensor Networks regarding security.

Define problems, issues regarding security of manets and

propose suitable solutions.Consider physical security threats in Manets.

Implement security stack for the protocol using COOJA

simulator.

Applying existing link security techniques.

Analyze results for interpretation.

Consider eavesdropping, spoofing and denial of service attacks.

Table 1: Personal Description

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References

[1] K.S.J.Pister, Smart Dust Project Home Page,Available http://robotics.eecs.berkeley.edu/~pister/SmartDust/index.html, Accessed February

17, 2012.

[2] Habitat Monitoring on Great Duck Island,Available http://www.greatduckisland.net,Accessed February 17, 2012.

[3] FireBugWildland fire monitoring system,Available http://firebug.sourceforge.net/,Accessed February 18, 2012.

[4] A. Dunkels. The contiki operating system (webpage),Available http://www.sics.se/~adam/contiki/, Accessed February 18, 2012.

[5] A. Dunkels, B. Grnvall, and T. Voigt,Contiki - a lightweight and exibleoperatingsystem for tiny networked sensors. In Proceedings of the FirstIEEE Workshop onEmbedded Networked Sensors, Tampa, Florida, USA,

Nov. 2004.

[6] A. Dunkels.Full TCP/IP for 8 Bit Architectures. In Proceedings of theFirstACM/Usenix International Conference on Mobile Systems, Applica-tions and Services(MobiSys), San Francisco, May 2003.

[7] P. Levis, S. Madden, D. Gay, J. Polastre, R. Szewczyk, A. Woo,E. Brewer,and D. Culler,The emergence of networking abstractionsand techniquesin tinyos, In Proceedings of the First USENIX/ACMSymposium on Net-worked Systems Design and Implementation (NSDI2004), 2004.

[8] M. Maroti,Directed flood-routing framework, ISIS, Vanderbuilt Univer-sity,Tech. Rep. ISIS-04-502, 2004.

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