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Taming the Underlying Challenges of Reliable Routing in Sensor Networks

Taming the Underlying Challenges of Reliable Routing in Sensor Networks. Alec Woo, Terence Tong, and David Culler UC Berkeley and Intel Research Berkeley. A Cross-Layer Perspective of Routing. How to get from A to B?. Select Good Routes. Underlying question: what are the ways to get

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Taming the Underlying Challenges of Reliable Routing in Sensor Networks

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  1. Taming the Underlying Challenges of Reliable Routing in Sensor Networks Alec Woo, Terence Tong, and David Culler UC Berkeley and Intel Research Berkeley

  2. A Cross-Layer Perspective of Routing How to get from A to B? Select Good Routes • Underlying question: • what are the ways to get • from A to B? • not given • vary over time • Neighbor management • keep the good ones Discover & characterize connectivity Each layer is a distributed, local process. • Study and understand global properties • End-to-end success rate • Routing topology over time • Stability Combine SenSys 2003

  3. Underlying Connectivity in Reality • 3 regions and transitional region is large • Deployment: • Communication range = effective region • Nodes: • Discover connectivity = link estimation • Hear many nodes in transitional region • How to define a “neighbor”? Transitional Region Effective Region many Clear Region SenSys 2003

  4. Roadmap • Underlying process • Link Quality Estimation • Neighborhood Management • Cross-layer routing study • Tree-based Routing SenSys 2003

  5. A Good Link Estimator • Accurate • Agile yet stable • Small memory footprint • Simple SenSys 2003

  6. Passive Estimation • Link sequence number snooping • Estimate inbound reception quality • Key issue • Cannot infer losses until next packet reception • Solution • With a minimum data rate, infer losses based on time • Asymmetric links • Require outbound transmission quality estimation • Exchange reception quality over local broadcast SenSys 2003

  7. Link Estimator Study • Study 7 estimators • by tuning to yield the same error bound • Results • WMEWMA(T, ) Estimator • Stable, simple, constant memory footprint • Compute success rate over non-overlapping window (T) • Average over an EWMA() • Key: • 10% |error| requires at least 100 packets to settle • Limits rate of adaptation SenSys 2003

  8. Neighbors in Transitional Region • Hear • Many potential neighbors • Few good nodes (blue) • Potential neighbors > available table-size • Cannot tell which neighbor is good Get in Get out Neighbor Table • General solution: • down-sample to suppress • gray nodes • maintain frequent nodes SenSys 2003

  9. Management Techniques • Cache Replacement Policy • FIFO, LRU (LRH), Clock • Database • Frequency estimation of data streams • FREQUENCY (Manku et al.) SenSys 2003

  10. Details • Insert (when) • Down-sample rate adapt to # of neighbors • Rate = Table Size / Neighbors • Reinforce if in table • Cache hit (FIFO, LRH, Clock) • Node’s Counter++ (Frequency) • Evict (which) • Counter--, zero entries are replaceable (Freq) • If all Counter > 0, drop insertion • Cache policies • evict for each insertion SenSys 2003

  11. Freq always maintains 50% or more good neighbors in table Key Results • Fixed-size table as cell density increases # Good neighbors > Table size 2nd 3rd 1st 40 Number of Potential Neighbors SenSys 2003

  12. Roadmap • Underlying process • Link Quality Estimation • Neighborhood Management • Cross-layer routing study • Tree-based Routing SenSys 2003

  13. Distributed Tree Building • Distributed distance-vector protocols • Operate over link estimator and neighbor management • Send periodic route messages • Carry “cost” to tree root • Piggyback link estimations • Hear neighbor’s “cost” and store in table • Select minimum cost neighbor for routing • Route damping • What should be the cost metric? SenSys 2003

  14. Hop-Count • Shortest hop with no estimation (SP) • Shortest hop with threshold SP(%) • Hard threshold Hop-Count? Neighbor? Link Quality? SenSys 2003

  15. Link estimator provides Non-threshold based Cost Metrics • Path Reliability • Product of link quality along the entire path • Minimum Transmission (MT) • Cost is based on link quality • Cost = E[total number of trans.] SenSys 2003

  16. Evaluation Roadmap • Key observations: • Hop distribution, end-to-end success, stability • Graph analysis • 80x80 grid • SP, SP(%), MT • Rule out SP because of poor reliability • Packet-level simulation • 10x10 grid, (max 2 retrans./hop) • Broadcast and DSDV (periodic route selection) • Neighbor table management (Freq -> MTTM) • Empirical (Mica Motes) • 5x10 grid and 30-node random placement • SP(%), MT with large enough table • max 2 retrans./hop, deliberate congestion High Level Large Low Level Small SenSys 2003

  17. Graph Analysis Key Results • Hop-Distribution and Reliability to BS SenSys 2003

  18. Simulation Key Results Hop-Count Distribution End-to-end Success vs. Distance Stability SenSys 2003

  19. Empirical Study • Restudy connectivity vs. distance • Put nodes at end of effective region (~ worst case) • 8 feet • Study SP(70%), SP(40%), MT • Key observations: • SP(70%) fails • SP(40%) fails • Hard threshold fails under congestion Link quality drops under traffic SenSys 2003

  20. End-to-end Success vs. Distance Hop-Count Distribution Empirical Key Results Different from simulations! Effective Region is 8 feet SenSys 2003

  21. Average Hop-Count Contour Plot SenSys 2003

  22. Congestion and Stability 30-node network Topology Stability # Route Changes Per 5 Route Messages Link Estimation % Time (s) SenSys 2003

  23. Conclusion • Connectivity: 3 regions (need to measure) • Deployment: node spacing • Routing as 3 on-line processes • Discover/maintain varying connectivity (WMEWMA) • Settling time limits adaptation rate • Maintain a set of good neighbors regardless of cell density (Frequency) • Hard thresholds are problematic • MT (No predefine threshold) • Interactions among these processes • Hop distribution, end-to-end success, stability SenSys 2003

  24. Backup Slides

  25. Routing Architecture Timer Send originated data message Application Send route update message Run parent selection and send route message periodically Parent Selection • Cycle detected • choose other parent Originating Queue Forward Queue Cycle Detection Estimator Neighbor Table Table Management Forwarding message Data message • All message • sniff and • estimate • Route message • save information Filter All Messages • discard non data packet • discard duplicate packet SenSys 2003

  26. Routing Cost: Actual vs. Est. SenSys 2003

  27. Channel Utilization Contour SenSys 2003

  28. MT Topology Movie SenSys 2003

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