Wireless Networked Sensors Routing Challenges

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Wireless Networked Sensors Routing Challenges. Mikhail Nesterenko. In this presentation I used the material from a presentation by David Culler, USB http://www.cs.berkeley.edu/~culler/talks/mobihoc.ppt, http://www.cs.berkeley.edu/~culler/cs294-f03/slides/awoo_oct_2nd_2003.ppt - PowerPoint PPT Presentation

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  • Wireless Networked Sensors Routing ChallengesMikhail NesterenkoIn this presentation I used the material from a presentation by David Culler, USB http://www.cs.berkeley.edu/~culler/talks/mobihoc.ppt, http://www.cs.berkeley.edu/~culler/cs294-f03/slides/awoo_oct_2nd_2003.ppt Kwong-Don Kang, SUNY, Binghamton www.cs.binghamton.edu/~kang/teaching/cs580s/taming-bvr.ppt

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    Reading ListDeepak Ganesan, Bhaskar Krishnamachari, Alec Woo, David Culler, Deborah Estrin and Stephen Wicker, Complex Behavior at Scale: An Experimental Study of Low-Power Wireless Sensor Networks , UCLA Computer Science Technical Report UCLA/CSD-TR 02-0013 A. Woo and D. Culler. Taming the Underlying Challenges of Reliable Multihop Routing in Sensor Networks. In Proc. of the 1st ACM Conf. on Embedded Networked Sensor Systems (SenSys), pp 14--27. Los Angeles, Nov 5-7 2003

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    Outlineempirical measurements of low-power radio performanceradio neighborhoodlink quality estimationissues with simple routingmintroutelink quality estimationneighborhood selectionrouting metricssimulation resultsexperimental results

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    Radio Neighborhoodradio neighborhood is not clearly defined reception is probabilisticnot isotropicreception rate is lowgood link drops 1 out of 4 packets (cf. ethernet drops 1 out of 10K)changes with time!

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    Link Qualitythree regions based on receptionnearly perfectunpredictablenearly noneone the fringes some links are asymmetricmore than 75% in one directionless than 25% in the otherwhat to do with them?detect and ignore?embrace?

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    Flood-Based Routing Issuessimple flood-based routing is imperfecthasstragglersbackward linksdense clusters

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    Other Issueslarge variation in affinityasymmetric linkslong, stable high quality linksshort bad onesvaries with traffic loadcollisionsdistant nodes raise noise floorreduce SNR for nearer onesmany poor neighborsgood ones mostly near, some far

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    Outlineempirical measurements of low-power radio performanceradio neighborhoodlink quality estimationissues with simple routingmintroutelink quality estimationneighborhood selectionrouting metricssimulation resultsexperimental results

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    Link EstimationIndividual nodes estimate link quality by observing packet success and loss eventsUse the estimated link quality as the cost metric for routingGood estimator should: React quickly to potentially large changes in link quality StableSmall memory footprint Simple, lightweight computation

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    WMEWMASnoopingTrack the sequence numbers of the packets from each source to infer lossesWindow mean with EWMAWMEWMA(t, a) = (#packets received in t) / max(#packets expected in t, packets received in t)t, a: tuning parameterst: #message opportunitiesTake average in a windowTake EWMA of the average

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    WMEWA (t =30, a =0.6)simulation of empirical trace in stable setting

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    Neighborhood ManagementNeighborhood tableRecord information about nodes from which it receives packetsMAC address, routing cost, parent address, child flag, reception (inbound) link quality, send (outbound) link quality, link estimator data structuresPropagate back to the neighbors as the outbound rather than inbound link quality is needed for cost-based routingThe receiving node may update its own table based on the received information possibly indicating topology changes Distance-vector based routing How does a node determine which nodes it should keep in the table?Keep a sufficient number of good neighbors in the tableSimilar to cache management

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    Management PoliciesInsertionHeard from a non-resident sourceAdaptive down-sampling techniqueProbability of insertion = N/T = neighbor table size / #distinct neighborsAt most N messages can be inserted for every T messagesEvictionFIFO, Least-Recently Heard, CLOCK, Frequency

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    #Good neighbors maintainable (table size 40)Frequency AlgorithmKeep a frequency count for each entry in the tableReinforce a node by incrementing its countA new node will be inserted if there is an entry with a zero countOtherwise, decrement the count of all entries and drop the new candidategood node 75% link accuracy

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    Background Link-State and Distance-Vector RoutingLink state routing algorithm (ex: DSDV)assume knowledge of the network topology and all link costsapply Dijkstras algorithm to find the shortest path from one source to all the other nodesImplemented via link state broadcast memory intensive, has issues with information update

    Distance vector routing (ex: AODV)each node propagates cumulative distance estimator (ex: min # hops) to all neighborsneighbors update their metric and propagate furtherhas counting to infinity problemcountered by poisoned reverse or split horizon

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    Cost-based routingKey ideasMinimize the cost that is abstract measure of distanceCould be #hops, #retransmissions, etc.Minimize # retransmissions: A longer path with fewer #retransmission could be better than a shorter path with more retransmissions!Distance-vector based approach implemented by the parent selection componentPeriodically run parent selection to identify one of the neighbors for routingMay also locally broadcast a route message including parent address, estimated routing cost to the sink, and a list of reception link estimations of neighborsA receiving node may update the neighbor table based on the received info or drop itFlag a child in the table to avoid a cycleWhen a cycle is detected trigger parent selection without the current parent

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    Routing Framework

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    Underlying IssuesParent selectionIf connectivity to the current parent is lost, a node disjoins from the tree, and sets its routing cost to infinity Reselect a parentRate of parent changePeriodic: Parent selection for every route update msg from neighbors incurs a domino effect of route changesParent snoopingFor example, quickly learn routing infoCyclesMonitor forwarding traffic and snoop on the parent address in each neighbors msg -> Identify child nodes and dont consider them as potential parents

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    Underlying IssuesDuplicate packet eliminationUse sender address & sequence numberQueue managementGive priority to originating traffic assuming originating data rate is lower than forwarding rateGeneral fair queuing is not considered in this paperRelation to link estimationLink failure detection based on a fixed number of consecutive xmission failures can be ineffective over semi-lossy links Link quality estimation can be a better judgment of link failureBidirectional link estimations can avoid routing over asymmetric linksStability and agility of link estimators can significantly affect routingFinal tuning must be done while observing its effect on routing performance

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    Cost metricMT (Minimum Transmission) metric: Expected number of transmissions along the pathFor each link, MT cost is estimated by 1/(Forward link quality) * 1/(Backward link quality)Inherently non-linearFor MT, a substantial noise margin should be used in parent select to enhance stabilityReliabilityAnother cost metricProduct of link qualities along the pathNot explored in this paper

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    Performance Evaluation: Tested Routing AlgorithmsMinimum Transmission (MT)Use the expected #transmissions as the cost metricUse a new path if the new cost is lesser by a noise marginMTTMAssume a neighbor table can maintain only 20 entries BroadcastRoot periodically floods the networkA node chooses a parent that forwards the flooded msg to itself first in each epochUse the reverse path to reach the root

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    Performance Evaluation: Tested Routing AlgorithmsShortest PathConventional distance-vector approachEach node picks a minimum hop-count neighbor as the parent and set its own hop-count to one greater than its parentTwo variations for performance analysisSP: A node is a neighbor if a packet is received from itSP(t): A node is a neighbor if its link quality exceeds the threshold tt = 70%: only consider the links in the effective regiont = 40%: also consider good links in the transitional region

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    Packet level simulationsBuilt a discrete time, event-driven simulator in MatlabNetwork of 400 nodes: 20 * 20 grid with 8 feet spacingSink is placed at a corner to maximize the network depth

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    Packet level simulationHop DistributionPath reliability over distance

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    Packet level simulation

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    Empirical study of a sensor fieldEvaluate SP(40%), SP(70%), MT50 Berkeley motes inside a building5 * 10 grid w/ 8 foot spacing90% link quality in 8 feet3 inches above the groundsink in the middle of short edge of the gridmeasurements at night to avoid pedestrian traffic

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    Link Quality of MTVary around 70%SP(70) may sufferHop DistributionSP(70) failed to construct a routing tree- MT congested: Triple the data origination and route update rate

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    E2E success rate

    Stability

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    Irregular Indoor Network30 nodes scattered around an indoor office of 1000ft2

    E2E Success RateLink Estimation of a nodeto its neighbors over time

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    ConclusionsLink quality estimation and neighborhood management are essential to reliable routingWMEWMA is a simple, memory efficient estimator that reacts quickly yet relatively stableMT (Minimum Transmissions) is an effective metric for cost-based routingThe combinations of these techniques can yield high end-to-end success rates

    Investigate local link estimators for determining link quality

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