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Ivan Stojmenovic1 Scalable localized routing in wireless sensor networks Ivan Stojmenovic [email protected] ivan Tutorial

Dec 31, 2015

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  • Scalable localized routing in wireless sensor networksIvan [email protected]/~ivanTutorial

    Ivan Stojmenovic

  • Sensors route reports to a fixed sink SinkEnd userhumidityInternet

    Ivan Stojmenovic

  • Multi-hop networks: RoutingUnit graphsradiusSensor networksPosition informationRouting: source destination

    Ivan Stojmenovic

  • Routing with/out position information ?Sensors can function efficiently only with position information GPS and location estimation advanced rapidly(cubic cm sensor with 7mm x 7mm x 2mm GPS)

    Sink can flood network with/out its own positionRoutes can be learn while flooding, orOnly position of sink is learned and used

    Ivan Stojmenovic

  • Proactive routing: ad hoc networksRouting table contains the first hop/neighbor toward each destinationBellman-Ford: Each node exchanges its routing tables with all its neighbors, andBest neighbors N for route from S to D is one that minimizes: cost of link S to N + cost N to D (from routing table in N)OLSR (Optimized Link State Routing): link changes are flooded + Dijkstras shortest pathMPR (MultiPoint Relay) to reduce flooding

    Ivan Stojmenovic

  • Reactive routing: ad hoc networksSource floods route discovery (short) messageDestination node replies back to source upon receiving discovery message(s) using memorized hops (AODV) or paths (DSR)Source sends full message using recorded pathMulti-paths for QoSRoute discovery message may contain accumulated delay, congestion, power, cost etc. along paths; best path selected at destinationLocal route maintenance; expanding ring search

    Ivan Stojmenovic

  • Route discovery by floodingEach sensor retransmits onceProblem: sink stable but sensors may sleepDSR, AODV in ad hoc networks, position info not needed =directed diffusion for sensors Intanagonwiawat, Govindan, Estrin 2000

    Ivan Stojmenovic

  • Directed diffusionMonitoring center broadcasts packet to all sensors in a regionSensors create links for reporting along reverse broadcast treeLink is toward sensor from which the first copy of packet is received

    Ivan Stojmenovic

  • Greedy position based localized routingLocalized protocol: S knows only position of itself, its neighbors and destination DS forwards to neighbor B closest to DFinn 1987

    Ivan Stojmenovic

  • Greedy: SABCD vs shortest path SECDSAECDLocalized vs. globalized protocolSP Overhead: messages to maintain global information at each node following mobility and/or sleep/active periods changesB

    Ivan Stojmenovic

  • Greedy is loop-freeAssume A1 closest to DA2 sends to A3 contradiction, A1 is closerDAnAn-1A3A2A1

    Ivan Stojmenovic

  • Progress based routing 84-86.ABCDEFSMFR: Choose closest projection on SD; minimize SA.SDA

    Ivan Stojmenovic

    Random progress (Nelson, Kleinrock): A, C or F

    NFP- nearest forward progress (Hou, Li): C

    MFR - most forward within radius

    (Takagi, Kleinrock): A

  • MFR is loop-freeA1 A2DAnAn-1A3A2A1Proof by Stojmenovic, Lin 1998

    Ivan Stojmenovic

    DAn.DA1 > DA2.DA1

    DAn.DA1>DA1.DA2>DA2.DA3>> DAn-1.DAn > DAn.DA1

  • Greedy vs. MFRDBAASBmay choose different node AD
  • DIRectional routing methodsSDABasagni, Chlamtac, Syrotiuk, Woodward MOBICOM98 (DREAM)Ko, Vaidya MOBICOM 98 (LAR)Kranakis, Singh, Urrutia CCCG99 (compass routing)Send to all neighbors within angular range from direction [BCSW,KV]location update schemes [BCSW, KV]Closest directionFlooding rate (# of messages vs SP) ??

    Ivan Stojmenovic

  • DIR is not loop-free !Transmission radiusDHGFEStojmenovic 1998Greedy and MFR are loop free

    Ivan Stojmenovic

  • Performance evaluationRandom unit graphs: Choose n nodes at random in [0,m]x[0,m]select average node degree d = 2,3,4,5,sort all (n-1)n/2 edges in increasing orderRadius R= nd/2-th edge in sorted order!Reject graph if disconnected

    Success rate = high for high degree, low for low degreehop count = successful Greedy/MFR close to SP, DIR >flooding rate (#messages vs SP) = close to SPIndependent variable is d, not R !!!

    Ivan Stojmenovic

  • Is hop count the best metric ?Power consumptionReluctance (avoiding nodes with low energy)Power_reluctanceDelayExpected hop count (realistic physical layer)COST - selected metric

    Ivan Stojmenovic

  • Cost to progress ratio frameworkProgress: measures advance toward destinationProgress = |SD|-|AD|=d-aSelect neighbor A that minimizes cost(SA)/progress(A)Hop count: cost=1Maximize advance

    SDAdraStojmenovic IEEE Network 2006

    Ivan Stojmenovic

  • Parameterless behaviorCost-to-progress ratio framework has no added parameters such as thresholdsThreshold based approach: eliminate bad links, drop packet if there is no good neighborWhat if a solid path has just one weak bridge?Experiments so far indicate that threshold based approaches are inferior for all threshold values - either high failure rate or suboptimal since there is no notion of best neighbor

    Ivan Stojmenovic

  • Constant power minimize hop countpower =u(d)= d + c minimize total powerMany articles assume c=0; in practice c>0 since power is needed to run hardware at each node, and correct reception requires minimal transmission power (no energy free transmission at zero distance)reluctance f(A) to forward packets ==1/g(A) g(A) in [0,1] lifetime minimize total costPower_reluctance = f(A)u(d) Power saving localized routing model by Rodoplu, Meng 1999

    Ivan Stojmenovic

  • Ideal and localized power aware routing# of hops n d(a( -1)/c)1/ minimal power: v(d)= dc(a(-1)/c)1/ + da(a( -1)/c)(1-)/ = O(d)

    A = minimizes u(r)+ v(s) among neighbors of SStojmenovic, Lin 1998

    Ivan Stojmenovic

  • Localized power aware routing

    Kuruvila, Nayak, Stojmenovic 2004Power progress: minimize (r+c)/(d-a)Iterative power progress: select B if power(SB)+power(BA) < power(SA)(Iterative) Projection power progress

    Ivan Stojmenovic

  • Reluctance routing algorithmAf(A)= reluctance =1/g(A) g(A) in [0,1] lifetimeA = neighbors of S that minimizes f(A) + f(S)*s/R( cost of A + average cost around S * ideal number of hops from A to D)If D is neighbor of S then deliver to D else forward to AReluctance/progress: minimize f(A)/(|SD|-|SA|)Kuruvila, Nayak, Stojmenovic 2004 (no added parameters)Stojmenovic, Lin 1998Rediscovered by: Yu, Govindan, Estrin: GEAR, TR-01-0023, Aug. 2001.

    Ivan Stojmenovic

  • Power_reluctance routingA = neighbors of S that minimizes u(r) + v(s)If D is neighbor of S and u(d) < min [u(r) + v(s)] then deliver to D else {A = neighbor of S that minimizes f(A)u(r) + v(s)f(S); forward to A }Power*reluctance/progress: minimize f(A)power(SA)/(|SD|-|SA|)Kuruvila, Nayak, Stojmenovic 2004 (no added parameters)

    Stojmenovic, Lin 1998

    Ivan Stojmenovic

  • Physical layer impactExpected hop count (counting all transmissions and possibly acknowledgements) F(SA)= expected hop count from S to AMinimize F(SA)/(d-a)Kuruvila, Nayak, Stojmenovic 2004Delay QoS routing Bitrate

    Ivan Stojmenovic

  • Physical layer impact =4p(R)=0.5Packet reception probabilityRUnit graph model:Prp(x)=1, xRPrp(x)=0, x>RLognormal shadowing modelDistance between nodesWhat is the transmission radius ? Who are neighbors?

    Ivan Stojmenovic

  • Simulation dilemmaHome-made simulator or one used by others (NS-2, Qualnet, J-sim,)?Greedy routing uses hop count as measureNS-2 applies realistic physical layer, which mostly penalizes long hops Why to use simulator that defeats the model, hides physical models and parameters which impact the data, impact comparison, and provide no explanation?Solution: build protocols and simulators in parallel, so that results can be explained and protocols improved Network layer protocol need to be designed with more realistic physical layer, not with unit disk graph model

    Ivan Stojmenovic

  • How to simulate ?Study one variable at a time, explain it fullyIdeal MAC, no congestion, for initial studiesIf one routing A is on average better than one routing B, it should cause less congestion, thus show even more advantage at the transport layerSimulation to match ideal assumptionsStable graphs first; localized design takes care of dynamicsIndependent variable is one that matters e.g. density (average number of neighbors per node), not transmission radiusCompare against the best (e.g. shortest path), not against worst (e.g. flooding)

    Ivan Stojmenovic

  • Approximate packet reception probabilityp(x) 1-(x/R)q/2 for x < R (2-x/R)q/2 for 2R x Rq depends on L, packet length, 2 6Signal strength is a random variable, and deviation cannot be predicted in advance (but some articles use it to select best neighbors)Transmission power is assumed fixed and same q=1 for L=1; q2 for L=120.Exact formula complex, time consuming and unreliableeach bit is received or not independently (no coding) packet received correctly iff all bits received

    Ivan Stojmenovic

  • Reactive routing with physical layerIn route discovery phase, forward the sum of Expected Hop Counts along partial route, orWait retransmission proportional to EHC on linkProblems:A single retransmission by a given node may not reach the best forwarding neighbor; tradeoff # of retransmissions and gains madeReal traffic may not use routes created by control traffic different packet lengths, or low packet reception probability

    Ivan Stojmenovic

  • Hello messages with physical layerfixed hello protocolSend hello messages fixed number of times, to increase the probability of reception by neighborsvariable hello protocolSen

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