Taming the Underlying Challenges of Reliable Multihop Routing in Sensor Networks.
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Transcript of Taming the Underlying Challenges of Reliable Multihop Routing in Sensor Networks.
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Taming the Underlying Taming the Underlying Challenges of Reliable Challenges of Reliable Multihop Routing in Multihop Routing in
Sensor NetworksSensor Networks
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Key ObservationsKey Observations Many wireless links are lossyMany wireless links are lossy Loss rate may change dynamicallyLoss rate may change dynamically
EEnvironmental factorsnvironmental factors HHighly correlated behavior of an applicationighly correlated behavior of an application
Routing should consider these Routing should consider these underlying factorsunderlying factors A lot of existing work on routing are based A lot of existing work on routing are based
on abstract MAC & physical layer modelon abstract MAC & physical layer model Simply assume 802.11 takes care of MAC Simply assume 802.11 takes care of MAC
layer issueslayer issues
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ContributionsContributions
Empirical link quality observation Empirical link quality observation Connectivity analysisConnectivity analysis
LLikelihood of the success of a communicationikelihood of the success of a communication Distance, residual energy, congestion, Distance, residual energy, congestion,
channel contention,channel contention,…… Link quality estimationLink quality estimation
Neighborhood managementNeighborhood management Routing for periodic data collection Routing for periodic data collection
applicationsapplications
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Empirical Observation of Empirical Observation of Link CharacteristicsLink Characteristics
Measure loss rates between many Measure loss rates between many different pairs of nodes at different different pairs of nodes at different distancesdistances A sequence of linearly arranged sensor A sequence of linearly arranged sensor
nodes with a spacing of 2 feetnodes with a spacing of 2 feet One transmitter sends packets 200 One transmitter sends packets 200
packets at the rate of 8 packets/secpackets at the rate of 8 packets/sec Remaining nodes counts the number of Remaining nodes counts the number of
successfully received packets successfully received packets
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Empirical ResultsEmpirical Results
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A simple probabilistic means can be A simple probabilistic means can be used to capture the link behavior in used to capture the link behavior in simulationssimulations Connected regionConnected region Transitional region: link probability Transitional region: link probability
with mean & variance from the with mean & variance from the empirical data empirical data
Disconnected regionDisconnected region
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SphericalSpherical radio range radio range assumptionassumption in current in current researchresearch Localization, Sensing Coverage, Topology ControlLocalization, Sensing Coverage, Topology Control
Radio IrregularityRadio Irregularity Deepak Ganesan, etc., Deepak Ganesan, etc., “Complex Behavior at Scale: An “Complex Behavior at Scale: An
Experimental Study of Low-Power Wireless Sensor Networks” , Experimental Study of Low-Power Wireless Sensor Networks” , UCLA/CSD-TR 02-0013, 2002UCLA/CSD-TR 02-0013, 2002
Alberto Cerpa, etc.,Alberto Cerpa, etc., “SCALE: A Tool for Simple Connectivity “SCALE: A Tool for Simple Connectivity Assessment in Lossy Environments”, Assessment in Lossy Environments”, CENS-TR 03-0021, 2003CENS-TR 03-0021, 2003
Jerry Y. Zhao, etc.,Jerry Y. Zhao, etc., “Understanding Packet Delivery “Understanding Packet Delivery Performance in Dense Wireless Sensor Network”, Performance in Dense Wireless Sensor Network”, ACM SenSys, ACM SenSys, 20032003
Alec Woo, etc.,Alec Woo, etc., “Taming the Underlying Challenges of Reliable “Taming the Underlying Challenges of Reliable Multihop Routing in Sensor Networks”, Multihop Routing in Sensor Networks”, ACM SenSys, 2003ACM SenSys, 2003
DOI Concept DOI Concept Tian He, etc., Tian He, etc., “Range-Free Localization Schemes in Large Scale “Range-Free Localization Schemes in Large Scale
Sensor Networks”, Sensor Networks”, MobiCom, 2003MobiCom, 2003
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Link EstimationLink Estimation
Individual nodes estimate link quality by Individual nodes estimate link quality by observing packet success and loss eventsobserving packet success and loss events
Use the estimated link quality as the cost Use the estimated link quality as the cost metric for routingmetric for routing
Good estimator should: Good estimator should: React quickly to potentially large changes in React quickly to potentially large changes in
link quality link quality StableStable Small memory footprint Small memory footprint Simple, lightweight computationSimple, lightweight computation
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WMEWMAWMEWMA
SnoopingSnooping Track the sequence numbers of the packets Track the sequence numbers of the packets
from each source to infer lossesfrom each source to infer losses Window mean with EWMAWindow mean with EWMA
WMEWMA(t, a) = (#packets received in t) / WMEWMA(t, a) = (#packets received in t) / max(#packets expected in t, packets received max(#packets expected in t, packets received in t)in t)
t, a: tuning parameterst, a: tuning parameters t: #message opportunitiest: #message opportunities
Take average in a windowTake average in a window Take EWMA of the averageTake EWMA of the average
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WMEWA (t =30, a =0.6)WMEWA (t =30, a =0.6)
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Neighborhood Neighborhood ManagementManagement
Neighborhood tableNeighborhood table Record information about nodes from which it Record information about nodes from which it
receives packetsreceives packets How does a node determine which nodes How does a node determine which nodes
it should keep in the table?it should keep in the table? Keep a sufficient number of good Keep a sufficient number of good
neighbors in the tableneighbors in the table Similar to cache managementSimilar to cache management
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Management PoliciesManagement Policies InsertionInsertion
Heard from a non-resident sourceHeard from a non-resident source Adaptive down-sampling techniqueAdaptive down-sampling technique Probability of insertion = N/T = neighbor table Probability of insertion = N/T = neighbor table
size / #distinct neighborssize / #distinct neighbors At most N messages can be inserted for every T At most N messages can be inserted for every T
messagesmessages
EvictionEviction FIFO, Least-Recently Heard, CLOCK, FIFO, Least-Recently Heard, CLOCK,
FrequencyFrequency
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#Good neighbors #Good neighbors maintainable (table size 40)maintainable (table size 40)
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Cost-based routingCost-based routing
MMinimize #retransmissionsinimize #retransmissions AA longer path w/ fewer longer path w/ fewer
#retransmission could be better #retransmission could be better than a shorter path w/ more than a shorter path w/ more #retransmissions! #retransmissions!
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Routing FrameworkRouting Framework
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Other Routing IssuesOther Routing Issues
Parent selectionParent selection Rate of parent changeRate of parent change PParent snoopingarent snooping CCyclesycles DDuplicate packet eliminationuplicate packet elimination QQueue managementueue management Relation to link estimationRelation to link estimation
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Cost metricCost metric
MT (Minimum Transmission) metric: MT (Minimum Transmission) metric: Expected number of transmissions along Expected number of transmissions along
the paththe path For each link, MT cost is estimated by For each link, MT cost is estimated by
1/(Forward link quality) * 1/(Backward 1/(Forward link quality) * 1/(Backward link quality).link quality).
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Performance Evaluation: Performance Evaluation: Tested Routing AlgorithmsTested Routing Algorithms
Shortest PathShortest Path SP: A node is a neighbor if a packet is SP: A node is a neighbor if a packet is
received from itreceived from it SP(t): A node is a neighbor if its link SP(t): A node is a neighbor if its link
quality exceeds the threshold tquality exceeds the threshold t tt = 70%: only consider the links in the = 70%: only consider the links in the
effective regioneffective region t = 40%: also consider good links in the t = 40%: also consider good links in the
transitional region transitional region
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Minimum Transmission (MT)Minimum Transmission (MT) Use the expected #transmissions as the cost metricUse the expected #transmissions as the cost metric
BroadcastBroadcast Periodic fPeriodic floodinglooding Choose a parent based on the source address of the 1Choose a parent based on the source address of the 1stst
flooding message in each epochflooding message in each epoch Destination Sequence Distance Vector (DSDV)Destination Sequence Distance Vector (DSDV)
Choose a parent based on the freshest sequence Choose a parent based on the freshest sequence number from the rootnumber from the root
Maintain a minimum hop count when possibleMaintain a minimum hop count when possible Ignore link quality Ignore link quality –– consider a node a neighbor once consider a node a neighbor once
heard from itheard from it Periodically reevaluatePeriodically reevaluate
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Packet level simulationsPacket level simulations
BBuilt a discrete time, event-driven uilt a discrete time, event-driven simulator in Matlabsimulator in Matlab
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Empirical study of a Empirical study of a sensor fieldsensor field
Evaluate SP(40%), SP(70%), MTEvaluate SP(40%), SP(70%), MT 50 Berkeley motes50 Berkeley motes 5 * 10 grid w/ 8 foot spacing5 * 10 grid w/ 8 foot spacing
90% link quality in 8 feet90% link quality in 8 feet 3 inches above the ground3 inches above the ground
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Link Quality of MTHop Distribution
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E2E success rateE2E success rate StabilityStability
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Irregular Indoor NetworkIrregular Indoor Network
30 nodes scattered around an indoor 30 nodes scattered around an indoor office of 1000ftoffice of 1000ft22
E2E Success Rate Link Estimation
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ConclusionsConclusions
Link quality estimation and neighborhood Link quality estimation and neighborhood management are essential to reliable management are essential to reliable routingrouting WMEWMA is a simple, memory efficient WMEWMA is a simple, memory efficient
estimator that reacts quickly yet relatively estimator that reacts quickly yet relatively stablestable
MT (Minimum Transmissions) is an MT (Minimum Transmissions) is an effective metric for cost-based routingeffective metric for cost-based routing
The combinations of these techniques can The combinations of these techniques can yield high E2E success rates yield high E2E success rates
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Questions?Questions?