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Sift: A MAC Protocol for Event-Driven Wireless Sensor Networks

Sift: A MAC Protocol for Event-Driven Wireless Sensor Networks. Kyle Jamieson † , Hari Balakrishnan † , Y.C. Tay ‡. † MIT Computer Science and Artificial Intelligence Laboratory ‡ Dept. of Computer Science, National University of Singapore. Periodic traffic Animal habitat monitoring

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Sift: A MAC Protocol for Event-Driven Wireless Sensor Networks

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  1. Sift: A MAC Protocol for Event-Driven Wireless Sensor Networks Kyle Jamieson†, Hari Balakrishnan†, Y.C. Tay‡ † MIT Computer Science and Artificial Intelligence Laboratory ‡ Dept. of Computer Science, National University of Singapore

  2. Periodic traffic Animal habitat monitoring Indoor environment Temperature Room occupancy Medical monitoring Patient vital signs Event-driven traffic Failure of mechanical structures Water pipes Airplane wings Medical emergencies Vehicle tracking Types of Traffic in Sensor Networks

  3. Airplane Wing Example For critical systems, low latency is important!

  4. Sift • Focus of our work • Designing MAC protocol to handle event-driven workload • Challenges • Low-latency • Good throughput • Good fairness

  5. Problems for Traditional MAC • Spatially-correlated contention: correlation between geographical neighbors’ traffic. • Bursty traffic: the number of senders can quickly change. • Suppression (counter-intuitively) Suppression: often, not all sensing nodes need to report an event.

  6. The Status Quo: CSMA • Basis of existing sensornet MAC layers • B-MAC, S-MAC • Timeslot: opportunity for a node to begin transmitting • Process repeats after each packet Busy Medium Time MAC Goal: only one node transmit at a time

  7. The Status Quo: CSMA Time • Pick a timeslot chosen uniformly in [0, CW] • Listen up to chosen slot • Transmit if nobody else started transmitting • Wait if somebody else started transmitting

  8. Slot choice (slot #4) Slot choice (slot #8) Example: A Successful Transmission • A and B happened to choose different slots • Node A chooses slot 4, hears nothing, transmits • Node B chooses slot 8, hears Node A, waits Node A: Node B: Time Success: exactly one node in first non-vacant slot

  9. Slot choice (slot #4) Slot choice (slot #4) Example: A Collision • A and B happened to choose slot 4 • Both listen and hear nothing • Both transmit simultaneously Node A: Node B: Time Collision: ≥ 2 nodes in first non-vacant slot

  10. Numericalsimulation High Contention Causes Collisions in CSMA Unacceptable collision rate above ~15 transmitting sensors Uniform distribution “fills up,” quickly

  11. Solving the Problem of Collisions in CSMA • Create more slots • Conventional approach • Called “binary exponential backoff” (BEB) • Change the way we pick slots • Sift takes this approach

  12. Create More Slots:Binary Exponential Backoff (BEB) • The basis for Ethernet, B-MAC, S-MAC, 802.11, MACAW, many other MAC layers Acknowledgement? Yes No Reduce CW Double CW and resend

  13. Problems with BEB • Takes time for every node to increase CW • Especially if traffic is spatially-correlated and bursty • Waste backoff slots if collisions cause CW to increase • Especially with suppression BEB causes performance to suffer

  14. Our Proposal: Sift • Sift is a MAC protocol for sensor networks • Event-driven traffic • Low-latency requirements • Sift’s Properties • Extremely simple • Offers up to 7-fold lower latency • Maintains good channel utilization (throughput)

  15. Sift: Changing the Distribution • Keep number of slots the same (simple) • Use an increasing non-uniform slot selection probability distribution • Make collisions unlikely for large range of N • Reduce the chance of collisions • Penalty: one packet- or RTS-time (ms) • Reduce wastage of backoff slots • Penalty: one slot time (μs)

  16. Balls and Bins Analogy • Bin represents a backoff slot in the contention window • Bin height represents probability of picking that slot • Ball represents a single node’s slot choice A Bins represent backoff slots →

  17. Why an Increasing Slot-Selection Function? Nodes choosing each slot → Bins represent backoff slots →

  18. Sift’s Slot Selection Distribution

  19. Numericalsimulation Optimal Non-Persistent CSMA Performance With knowledge of number of nodes (IEEE J-SAC ’04)

  20. Numericalsimulation Sift Approaches Optimal Sift keeps success rate above this unacceptable range Sift needs no knowledge of the number of nodes

  21. Experimental Setup • Simulation-based results (ns-2) • Compare 802.11 (BEB), Sift, and 802.11/copy • 802.11/copy: send CW in each packet, copy overheard CW

  22. Event-driven Traffic Pattern • Event-based traffic pattern • Single-hop to one base station • N nodes sense and report an event • R ≤ N reports are required • If a node hears≥ R reports then it suppresses its own event report E.g. N=4, R=3 Base Station

  23. Experimental evaluation: R=1,16 Sift Outperforms When N is Large R=16 R=1

  24. Experimental evaluation: N=128 Sift Outperforms as R Increases

  25. Experimental evaluation Exploring Sift’s Performance Space

  26. Separate 128 sensors into mutually-hidden clusters Nodes in one cluster cannot hear nodes in another All nodes send to the base station Result: hidden terminal collisions at the base station Base Station Hidden Terminal Experiment Setup

  27. Experimental evaluation: N=128, R=1 Sift Performs Well with Hidden Terminals

  28. Experimental evaluation: N=128, R=64 Sift Resilient to Jitter in Event Time

  29. Experimental evaluation Sift Improves Fairness 64 nodes Eight nodes

  30. Trace-Driven Experimental Setup • Simulated vehicle tracking • Captured live video from a street scene • Extract motion events from image analysis • Event trace drives ns-2 simulation • 128 sensors laid out in a grid over the scene • Sensors nearby each event send traffic in response to movement

  31. Trace-driven experimental evaluation Sift Outperforms When R is Large

  32. Related Work • TDMA suffers in terms of latency • PTD (Mowafi et al.), TSMA (Chlamtac et al.) • BEB-based protocols waste time in backoff • MACAW (Bharghavan et al.), S-MAC (Ye et al.), FAMA (Garcia-Luna-Aceves et al.) • The HIPERLAN standard for wireless LANs uses noise bursts of exponentially-distributed length • Periodic-sleeping and other MAC protocols can work with Sift • S-MAC (Ye et al.), B-MAC (Polastre) Sift is a composable MAC primitive

  33. Conclusion • Sift is a latency- (and sometimes throughput-) enhancing MAC for event-driven sensor networks • Sift can be used as a building block in many MAC protocols http://nms.csail.mit.edu/projects/sift

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