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USC CSCI 599 - 14

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Adaptive Protocols for Information Dissemination in Wireless Sensor NetworksOutlineIntroductionIntroduction contd.Sensor Protocols for Information via Negotiation (SPIN)Implosion ProblemOverlap problemSPIN contd..SPIN Meta-DataSPIN MessagesSPIN-1 and SPIN-2Node B sends a REQ listing all of the data it would like to acquire.If node B had its own data, it could aggregate this with the data of node A and advertise.Nodes need not respond to every messageSPIN-2Other data dissemination algos.PowerPoint PresentationIdeal disseminationSlide 19Sensor Network SimulationsSimulation TestbedSPIN-1 ResultsData Acquired Over TimeEnergy Dissipated Over TimeSlide 25Unlimited Energy SimulationsLimited Energy SimulationsLimited Energy Simulations contd..Best-Case Convergence TimesTransmission time per data packet = 8s/d Since SPIN-1 has to process ADV, REQ, DATA so processing time = 3(d+r)Convergence Time – overlapping dataSlide 32ConclusionsStrengths and WeaknessesQuestions ?CS 599 Intelligent Embedded Systems 1Adaptive Protocols for Information Dissemination in Wireless Sensor NetworksW.R.Heinzelman, J.kulik, H.BalakrishnanCS 599 Intelligent Embedded Systems 2OutlineIntroductionSPINOther Data Dissemination AlgorithmsSensor Network SimulationsConclusionsStrengths and WeaknessesCS 599 Intelligent Embedded Systems 3IntroductionWide deployment of Wireless sensor networksWireless sensor networksCan aggregate sensor data to provide multi-dimensional viewImprove sensing accuracyFocus on critical events (e.g. intruder entering)Fault tolerant networkCan improve remote access to sensor data – sink nodesCS 599 Intelligent Embedded Systems 4Introduction contd.Limitations of Wireless sensor networksEnergyComputationCommunicationCS 599 Intelligent Embedded Systems 5Sensor Protocols for Information via Negotiation (SPIN)Classic flooding limitationsImplosionOverlapResource blindnessCS 599 Intelligent Embedded Systems 6Implosion ProblemCS 599 Intelligent Embedded Systems 7Overlap problemCS 599 Intelligent Embedded Systems 8SPIN contd..SPIN overcomes these deficienciesNegotiationResource-adaptationEach sensor node has resource managerKeeps track of resource consumptionApplications probe the manager before any activityCut down activity to save energyMotivated by principle of ALFCommon data naming (meta-data)CS 599 Intelligent Embedded Systems 9SPIN Meta-DataSensors use meta-data to describe the sensor data brieflyIf x is the meta-data descriptor for data Xsizeof (x) < sizeof (X)If x==ysensor-data-of (x) = sensor-data-of (y)If X==Ymeta-data-of (X) = meta-data-of (Y)Meta-data format is application specificCS 599 Intelligent Embedded Systems 10SPIN MessagesADV – new data advertisementREQ – request for dataDATA – data messageADV and REQ messages contain only meta-data so they are smaller in size.CS 599 Intelligent Embedded Systems 11SPIN-1 and SPIN-2SPIN-1Simple 3-stage handshake protocolData aggregation is possibleCan adapt to work in lossy or mobile networkCan run in a completely unconfigured networkCS 599 Intelligent Embedded Systems 12Node B sends a REQ listing all of the data it would like to acquire.CS 599 Intelligent Embedded Systems 13If node B had its own data, it could aggregate this with the data of node A and advertise.CS 599 Intelligent Embedded Systems 14Nodes need not respond to every messageCS 599 Intelligent Embedded Systems 15SPIN-2SPIN-1 with a Low-Energy ThresholdWhen energy below energy threshold – stop participating in the protocolCan just receive data avoiding ADV-REQ phaseCS 599 Intelligent Embedded Systems 16Other data dissemination algos.Classic FloodingConverges in O(d), d-diameter of the networkGossipingForward data to a random neighborAvoids implosionDisseminates at a slow rateFastest rate = 1 node/roundCS 599 Intelligent Embedded Systems 17CS 599 Intelligent Embedded Systems 18Ideal disseminationEvery node sends sensor data along shortest pathReceives each piece of distinct data only onceImplementationNetwork level multicast (source specific)To handle losses, reliable multicast has to be deployedSPIN is a form of application-level multicastCS 599 Intelligent Embedded Systems 19CS 599 Intelligent Embedded Systems 20Sensor Network SimulationsSimulated using ns simulatorExtended ns to create a Resource-Adaptive NodeCS 599 Intelligent Embedded Systems 21Simulation TestbedCS 599 Intelligent Embedded Systems 22SPIN-1 ResultsHigher throughput than gossipingSame throughput as floodingUses substantially less energy than other protocolsSPIN-2 delivers more data per unit energy than SPIN-1SPIN-2 performs closer to Ideal disseminationNodes with higher degree tend to dissipate more energy than nodes with lower degreeCS 599 Intelligent Embedded Systems 23Data Acquired Over TimeCS 599 Intelligent Embedded Systems 24Energy Dissipated Over TimeCS 599 Intelligent Embedded Systems 25Energy Dissipated Over TimeCS 599 Intelligent Embedded Systems 26Unlimited Energy SimulationsCS 599 Intelligent Embedded Systems 27Limited Energy SimulationsCS 599 Intelligent Embedded Systems 28Limited Energy Simulations contd..CS 599 Intelligent Embedded Systems 29Best-Case Convergence TimesFor overlapping sensor dataConvergence times for ideal and flooding are the sameFor non-overlapping sensor dataFlooding converges faster than SPIN-1To understand these results, we develop equations that predict convergence times of each of these protocols.CS 599 Intelligent Embedded Systems 30Transmission time per data packet = 8s/dSince SPIN-1 has to process ADV, REQ, DATA so processing time = 3(d+r))8)(3()83()8(,)8(1bsrdlCbsdlbsrdlCCbsdldSPINddFloodIdealdConvergence Time – no overlapCS 599 Intelligent Embedded Systems 31Convergence Time – overlapping data24)1()8()83()8)(3()83()8(,)8(1rbskdbskrdlbsdlbskrdlCbsdlbskrdlCCbsdllplplpSPINlplpFloodIdeallpCS 599 Intelligent Embedded Systems 32For the testbed network parametersSimulation resultsFlooding converges in 135msIdeal converges in 125msSPIN-1 converges in 215msConvergence times of flooding and ideal are closer to their upper bound unlike SPIN-1294.0133.0154.0,063.01SPINFloodIdealCCCCS 599


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USC CSCI 599 - 14

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