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

Types of Traffic in Sensor Networks 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

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

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

Problems for Traditional MAC 1.Spatially-correlated contention: correlation between geographical neighbors’ traffic. 2.Bursty traffic: the number of senders can quickly change. 3.Suppression (counter-intuitively) Suppression: often, not all sensing nodes need to report an event.

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

The Status Quo: CSMA 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 Time

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 Success: exactly one node in first non-vacant slot Node A: Node B: Slot choice (slot #4) Slot choice (slot #8) Time

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

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

Solving the Problem of Collisions in CSMA 1.Create more slots –Conventional approach –Called “binary exponential backoff” (BEB) 2.Change the way we pick slots –Sift takes this approach

Create More Slots: Binary Exponential Backoff (BEB) The basis for Ethernet, B-MAC, S-MAC, , MACAW, many other MAC layers Acknowledgement? Reduce CW Double CW and resend YesNo

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

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)

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 1.Reduce the chance of collisions Penalty: one packet- or RTS-time (ms) 2.Reduce wastage of backoff slots Penalty: one slot time (μs)

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 →

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

Sift’s Slot Selection Distribution

Optimal Non-Persistent CSMA Performance With knowledge of number of nodes (IEEE J-SAC ’04) Numerical simulation

Sift Approaches Optimal Sift needs no knowledge of the number of nodes Numerical simulation Sift keeps success rate above this unacceptable range

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

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

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

Sift Outperforms as R Increases Experimental evaluation: N=128

Exploring Sift’s Performance Space Experimental evaluation

Hidden Terminal Experiment Setup 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

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

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

Sift Improves Fairness Eight nodes 64 nodes Experimental evaluation

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

Sift Outperforms When R is Large Trace-driven experimental evaluation

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

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

Detailed Experimental Parameters Average of five runs with different random number seeds for each run ARQ with 5 retransmit limit Control packets sent at 1 MBps; data at 2 MBps 20 μs slot time; 192 bit preamble; 30 byte packet CWmin=31, CWmax=1023

Sift Provides Good Throughput Two nodes 32 nodes

Optimal Non-Persistent CSMA Let s be a slot number, assume N ≥ 2 sensors transmitting. Define: “Collision Minimizing CSMA and its Applications to Wireless Sensor Networks.” IEEE J. Selected Areas in Comm. 22:6 (2004) pp