The document discusses the implementation of the Byzantine Fault Tolerant algorithm in wireless sensor networks, detailing the goals, constraints, and procedures for its execution on both mesh and multi-hop network configurations. It covers the technologies used, including simulations and practical demonstrations, as well as comparisons between different algorithms. Future improvements and a cloud computing extension for the simulator are also suggested.

1. IMPLEMENTING BYZANTINE ALGORITHM ON WIRELESS SENSOR NETWORKSGuided By:- Prof. GaurangRavalPresented By:Shatadru Chattopadhyay(07BIT005)Herat Gandhi(07BIT012)ShashankJuyal(07BIT017)

2. AGENDAIntroductionGoals and ObjectivesConstraintsTools and Technologies usedConceptsByzantine Failure Byzantine fault tolerant AlgorithmDeliverablesByzantine Implementation on Mesh NetworksByzantine Implementation on multi-hop networksByzantine implementation on multi-hop networks using power based routingComparison between algorithmsPractical DemonstrationFuture Scope

3. INTRODUCTIONGoals and ObjectivesImplementation of Byzantine Fault Tolerance AlgorithmSimulation of algorithm using TOSSIMDeployment over hardware motesMeasuring time required by each mote and optimizing itEfficient utilization of resources on Hardware motesPower Efficient Algorithms

4. IntroductionconstraintsInterference along the 2.4 GHz ISM band since most wireless devices tend to use this band for communication.Noise Level across links should be known.TOSSIM cannot simulate for heterogeneous networks.Because it is developed in TinyOS 2.1.1 it is backward incompatible.

5. IntroductionfunctionalitiesDetecting and Isolating faulty motes and keeping the network robust enough to communicateMaintaining power efficiencyA power efficient routing protocolA client server simulator for analysts to analyze their networks and topologiesGraphical Analysis and Report Generation

6. Introductiontools and technologiesNetBeans6.9.1TinyOSPowerTOSSIM-ZTOSSIMPython

7. Conceptsbyzantine faultThe term Byzantine was first used for the type of failure where faulty motes may exhibit completely unconstrained behavior.Derived from some traitorous generals of the Greek Byzantium EmpireThe Byzantine Problem assumes that the network is an n-mote connected undirected graphEach mote starts with an input from a fixed value set V .The goal is for the motes to eventually output decisions from the set V, with the possibility that a limited number (at most f) of motes might fail.

8. Conceptsbyzantine fault tolerant algorithmIn order to broadcast (m, i, r) at round r, mote i sends a message (“init', m, i, r) to all motes at round r. If mote j receives an ("init", m, i, r) message from mote i at round r, it sends ("echo", m, i, r) to all motes at round r + 1.If, before any round r > r + 2, mote j has received ("echo", m, i, r) messages from at least f + 1 motes, then j sends an ("echo", m, i, r) message at round r (if it has not already done so).If, by the end of any round r > r + l, mote j has received ("echo", m, i, r) messages from at least n - f motes, then j accepts the communication at round r(if it has not already done so).

10. conceptsCollection tree protocol(CTP)A collection protocol builds and maintains minimum cost trees to nodes that advertise themselves as tree roots.Two methods The first is data path validation using data packets to dynamically probe and validate the consistency of its routing topology.The second is adaptive beaconing, which extends the Trickle code propagation algorithm so it can be applied to routing control traffic.CTP uses expected transmissions (ETX) as its routing gradient.A root has an ETX of 0. The ETX of a node is the ETX of its parent plus the ETX of its link to its parent.

11. ConceptsdisseminationMajor Dissemination Protocols are DRIP-Each data item is independently advertised and disseminated. Metadata is not shared among data itemsDIP-It is a modification of the Drip protocol. Advertisement messages are used for a fixed data set meaning all nodes must agree on a fixed set of data item identifiers before dissemination. DHV-Advertisement messages are used for a fixed data set meaning all nodes must agree on a fixed set of data item identifiers before dissemination.

12. Deliverablesimplementation on mesh networksStage 1: All stations send HELO packet to the base stationStage 2: Base Stations sends ‘n’-the number of motes in the network, to all stationsStage 3: A node sends an INIT packet to all other motesStage 4: If having received INIT packet, motes send ECHO packet to all other motesStage 5: If a mote has received ‘n-f’ ECHO packets, f being the number of faulty motes, then communication is successfully established

13. Implementation on mesh networksPacket structuresHELO Packet-16 bit packetContains mote ID of the mote sending itINIT Packet-32 bit packetSent only once by a moteConsists sender`s mote IDECHO Packet-32 bit packetSent in reply to receiving an INITConsists of the mote ID of sender

14. Implementation over mesh networksresultsProbability vs. Number of Motes(n)

15. Implementation over mesh networksresultsEnergy(mJ) vs. Time(msecs)

16. Implementation over mesh networksresultsEnergy(mJ) vs. Probability

17. deliverablesImplementation over multi-hop networksFirst stage: All motes send HELO packet to base station using CTP and base station finds total number of motes in network.Second stage: Base station sends “n (number of motes)” to all motes using Dissemination.Third stage:In this stage one node will be randomly selected and will disseminate INIT packet using the Drip algorithm in the network.Fourth stage: After receiving INIT packet, motes send ECHO packet. Motes keep counter of ECHO packets.Fifth stage: If any mote has received n-f ECHO packets in previous round then it establishes successful communication.

18. Implementation over multi-hop networksPacket structuresHELO Packet-16 bit packetContains mote ID of the mote sending itINIT Value-Is a value disseminated over the networkValue disseminated using DRIPIf a value of 0 is received it is interpreted as INIT valueECHO Value-Is a value disseminated over the networkValue disseminated using DRIPIf a value other than 0 is received it is interpreted as ECHO

19. Implementation over multi-hop networksresultsEnergy vs. Number of Motes(n)

20. Implementation over multi-hop networksresultsTime vs. Number of Motes(n)

21. Deliverablesimplementation using power based routingFirst stage: All motes send HELO packet to base station using CTP and base station finds total number of motes in network. Second stage: Base station sends “n (number of motes)” to all motes using Dissemination.Third stage: Each mote sends HELO packet to its neighbor. Fourth stage: After receiving HELO packet from neighbor mote sends ACK packet to sender mote. After receiving ACK packet mote measures its RSSI value and stores all necessary information. Each mote also stores which mote can be selected as its parent. Continued……..

22. continuedFifth stage: Information collected from the previous stage is sent to base station using FRNDS packet and base station processes this information and creates routing table.Sixth stage: Base station sends pruned routing table to all motes. Seventh stage: In this stage one node will be randomly selected and will disseminate INIT packet using pruned routing table. Eighth stage: After receiving INIT packet, motes send ECHO packet. Motes keep counter of ECHO packets. Ninth stage: If any mote has received n-f ECHO packets in previous round then it establishes successful communication.

23. implementation using power based routingPacket structuresHELO Packet-16 bit packetContains mote ID of the mote sending itINIT Value-Is a value disseminated over the networkValue disseminated using DRIPIf a value of 0 is received it is interpreted as INIT valueECHO Value-Is a value disseminated over the networkValue disseminated using DRIPIf a value other than 0 is received it is interpreted as ECHOFRNDS Packet-Contains neighbor information and power required to transmit to them

24. implementation using power based routingresultsEnergy vs. Number of motes

25. implementation using power based routingresultsTime vs. Number of motes

26. Comparison between algorithms

27. SimulatorA client server based simulatorIt is aimed at network analysts to analyze topologiesCan work for particular or a randomly generated topologyProvides graphical analysis as well as reports for the topology and its energy consumptionWorks over the internet and TOSSIM needs to be installed only in the server hence saves from installing TinyOS.

28. simulatorreports-power analysis

29. simulatorreports-network graph

30. simulatorreports-power graph

31. Practical Demonstration

32. Future scopeSome improvements in the Algorithm can be done by using the routing table generated by the Base Station using power based routing in the implementation of Byzantine algorithm to make it more efficient and feasible over large network.This simulator performs all processing part on server and client can view result by communicating with server. This architecture can be extended to use cloud computing.

33. bibliographyD Gay, P Levis, ‘The NesC language: A holistic approach to network embedded systems’, ACM 2003Nancy Lynch, ‘Distributed Algorithms’, Morgan Kaufmann Inc. 1997\Philip Levis, ‘TOSSIM: Accurate and Scalable simulation of entire TinyOS applications’.Enrico Perla, Art O Cathain, ‘PowerTOSSIM z: Realistic Energy Modeling for Wireless Sensor Network Environments’Jessica Staddon, Dirk Balfanz and Glenn Durfee, ‘Efficient Tracing of Failed Nodes in Sensor Networks’, Palo Alto reasearch Center, October 1 2002. Thomas Clouqueur, ‘Fault Tolerance in Collaborative Sensor Networks for Target Detection, IEEE Conference, March 2004.Carolos Livadas and Nancy A. Lynch, ‘A Reliable Broadcast Scheme for Sensor Networks’.H.A. Ali, ‘An efficient relative broadcast algorithm in Adhoc networks based on Self-Pruning’, Egypt.

34. referenceshttp://docs.tinyos.nethttp://netbeans.org/kb/docs/ide/overview-screencast.htmlhttp://www.millennium.berkeley.eduhttp://www.eecs.harvard.edu/~mainland/tinyoshttp://www.cs.berkeley.edu/~pal/research/tossim.htmlhttp://deneb.cs.kent.eduhttp://vimeo.com/channels/tinyoshttp://cs.acadiau.ca/~shussain/wsn/apps/tos2/index.html

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