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Optimal QoS-aware Sleep/Wake Scheduling for Time Synchronized Sensor Networks

Optimal QoS-aware Sleep/Wake Scheduling for Time Synchronized Sensor Networks. CISS 06. Yan Wu, Sonia Fahmy, Ness B. Shroff Center for Wireless Systems and Applications(CWSA) Purdue University. Application specific networks Habitat monitoring, military surveillance etc Sensor Nodes

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Optimal QoS-aware Sleep/Wake Scheduling for Time Synchronized Sensor Networks

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  1. Optimal QoS-aware Sleep/Wake Scheduling for Time Synchronized Sensor Networks CISS 06 Yan Wu, Sonia Fahmy, Ness B. Shroff Center for Wireless Systems and Applications(CWSA) Purdue University

  2. Application specific networks • Habitat monitoring, military surveillance etc • Sensor Nodes • Unattended during their life cycle • Limited in processing/communication capabilities • Constrained in battery life time • One large application class: Continuous Monitoring • Examples: habitat monitoring, civil structure maintenance • Nodes monitor the environment and periodically upload sensing data to a Base Station Wireless Sensor Networks

  3. Continuous Monitoring Applications • Duty cycle is usually low • Clustering is often used [1] • Nodes in the same neighbourhood elect a cluster head (CH) • 2-step communication: intra-cluster and inter-cluster • Cluster Head (CH) is heavily utilized • To extend the lifetime of the CH • Re-clustering – extensively investigated • Sleep/wake scheduling – our interest • Idle energy is significant for low duty cycle networks • Turn off the CH radio when no transmissions • Wake it up right before transmissions occur • Good match with periodic traffic pattern • [1] S. Tilak, N. B. Abu-Ghazaleh, and W. Heinzelman. A taxonomy of wireless micro-sensor network models. ACM Mobile Computing and Communication Review, April 2002.

  4. Motivation • Under periodic traffic pattern • If time synchronization is perfect Sleep/wake scheduling of CH will be trivial • Most previous sleep/wake scheduling work assumes perfect synchronization--This assumption is not always true! • Existing synchronization protocols[2] achieve precise (µs) synchronization immediately after exchange of synchronization messages • But clock drifts away as time progresses • E.g., two nodes exchange a message every 5 minutes • Motes datasheet: max clock skew = 100ppm • After 5 minutes, clock disagreement = 30ms • Larger than message transmission time in sensor networks • Synchronization error is non-trivial! [2] J. Elson, L. Girod, and D. Estrin. Fine-Grained Network Time synchronization Using Reference Broadcasts. In Proceedings of OSDI, 2002.

  5. Motivation (summary) • Environment • Continuous monitoring applications with periodic transmissions • Network has already been clustered using some existing clustering algorithm. • Problem • Cluster Head (CH) is heavily utilized • Goal: save energy for CH via sleep/wake scheduling • Difficulty • Trivial if synchronization is perfect • But in practice synchronization is imperfect and synchronization error is non-negligible Sleep/wake scheduling with consideration of synchronization error

  6. Outline • Motivation • Review Time Synchronization • System model • Problem definition • Solution • Conclusions and future work

  7. Time Synchronization • Why are clocks different from each other? • Phase offset: clock disagreement at a given time instant • Clock skew: clocks run with different speed • May slowly change over time Synchronization is to estimate phase offset and clock skew • Mechanism -- exchange messages to synchronize • Example: one node sends a message to another • Uncertainty: sender (random backoff), receiver (PHY/MAC layer)  Random Estimation Error • Many synchronization protocols try to reduce the uncertainty • RBS[2]/TPSN[3] • [2] J. Elson, L. Girod, and D. Estrin. Fine-Grained Network Time synchronization Using Reference Broadcasts. In Proceedings of OSDI, 2002. • [3] S. Ganeriwal, R. Kumar, and M. Srivastava. Timing-sync Protocol for Sensor Networks. In Proceedings of ACM SenSys, November 2003.

  8. A single cluster with a CH and M members:n1, …nM • Each member uploads to the CH every T seconds System Model • Time is divided into epochs • Epoch = Synchronization interval + Transmission interval

  9. System Model • Assumptions • Neighbouring clusters use orthogonal frequency channels • Focus on intra-cluster communications • Clock skew and phase offset are constant over each epoch • Only account for communication energy • Synchronization Scheme in This Work • Adopt the widely used RBS[2] synchronization scheme • RBS Procedure • Exchange sync. messages to obtain multiple corresponding time pairs • Use linear regression to estimate clock skew and phase offset

  10. RBS Synchronization Scheme • C: time of CH, tx : time of member x • a/b: clock skew/phase offset • a’/b’: estimation of a/b • Recall that clock skew and phase offset are constant over an epoch • For a given epoch, tx = a×C + b • RBS • Obtain Ns corresponding time pairs (txi, Ci) i=1…Ns txi = a×Ci + b + ei, ei: random error • System measurements show that ei is normally distributed • Chi-square test, 99.8% confidence level • Use linear regression to estimate a and b • The existence of ei causes estimation error: (a’, b’) ≠(a, b)

  11. Outline • Motivation • Review Time Synchronization • System model • Problem definition • Solution • Conclusions and future work

  12. Problem Definition • CH and the member x agree upon a message send time t (CH clock) • x should transmit at t by CH clock (scheduled send time) • x coverts t into its own clock: tx = a’× t + b’ and transmits at tx • The actual send time is tx (x’s clock), express it using CH clock τ = (tx – b)/a = a’/a × t + (b-b’)/a Ifthere is no estimation error, (a’, b’)=(a, b), thenτ =t But there exists random estimation error, so τ≠ t Because of estimation error, message may not be sent at scheduled time. • How does the CH combat the estimation error? • Uses a wake up interval to “capture” the message

  13. Question: how early should the CH wake up and how long should it stay active? • wakes up early and stays up long -- wastes energy • wakes up late and stays up short -- miss msg. Trade-off between energy consumption and message capture probability! • Guarantee a minimum message capture probability th • Minimize the expected energy consumption Problem Definition

  14. Sleep/wake scheduling – considering sync. error • Minimize the expected energy consumption under constraint on capture probability Minimize: such that where: w: wake up time s: sleep time τ: actual message arrival time l: message length R: data rate : idle/receiving power : Probability Density Function of τ th: QoS parameter Problem Definition

  15. Outline • Motivation • Review Time Synchronization • System model • Problem definition • Solution • Conclusions and future work

  16. Computing PDF τ = a’/a × t + (b-b’)/a • a’/b’ are computed from standard Linear Regression • sync. error is Normal τ is also Normal E(τ) = t, VAR(τ) Solution Sketch

  17. Put the PDF into the formulation • Change of variable: x=[w-E(τ)]/στ, y =[s-E(τ)]/στ • Minimize: such that • Non-convex optimization problem • Compute the Hessian Matrix • Cannot directly solve it using conventional techniques Solution Sketch

  18. Solution Sketch • Proposition: optimal solution satisfies Q(x)-Q(y) = th • Meaning: optimum is achieved when capture_probability=th • Put this result into F(x,y)

  19. Simplified Formulation Minimize such that • Solve the simplified formulation • Proposition: G”(x) >0 Proof:Implicit Differentiation and Mean Value Theorem • The simplified formulation is convex

  20. Performance Evaluation • A previous scheme to combat sync. error • Assume an upper bound on the clock disagreement and use it as a guard time • Simulation results • In order to guarantee the same capture performance, the energy consumption of our scheme is 20-40% less than the previous scheme

  21. So far • Assumed capture probability threshold th is already given • Extension -- How to assign th for different nodes n1, … nM? • Uniform assignment: assign same value to all nodes • Problem: heterogeneity among nodes • Some nodes: expensive high-precision thermometer • Others: cheap low-precision thermometer Differentiated Assignment

  22. Conclusions • This work • Studied sleep/wake scheduling in clustered networks • Identified the impact of sync. error on sleep/wake scheduling • Proposed an optimal sleep/wake scheduling scheme with consideration for sync. error • Simulations validate the effectiveness of our scheme • Future work • This work • Focus on intra-cluster communications (memberCH) • CH  Base Station? • Future work • Inter-cluster communications -- Multi-hop

  23. RBS • Receiver-receiver synchronization • Nodes A and B want to synchronize with each other • Requires an additional beacon node C • Procedure • Beacon Node send reference beacons to A and B • A and B record the arrival time of the beacon, tA and tB • A and B compare the arrival times • Properties • Removes completely randomness caused by the sender • Leaves only one source of error – receiver

  24. Clock skew • crystal oscillator • expected frequency: the frequency that it should work. • actual frequency: might differ from expected frequency. • Accuracy: <100 ppm • Decided by manufacturing imprecision and aging effect • Affected by environment factors like variations in temperature, humidity etc. • Slow changing • For off-the-shelf oscillator, clock skew < 100pm

  25. Transmission Error • Not considered in the current formulation • During cluster construction, nodes will select nearby CH • Error probability should not be very large • In case of transmission error, our scheme is still robust • Prob(receive) = Prob(capture) * (1-Pe)

  26. Adaptive adjustment of the wake up interval • Idea: a message not received synchronization is wrongadjust the wake up interval for next message • Implicit assumption: message not received is only caused by wrong synchronization • Not necessarily true: message not received might also be caused by transmission error

  27. Retransmission • No retransmissions • Retransmissions need acknowledge mechanism, cost energy • Sensor networks usually deployed with redundancy

  28. Problem definition • CH and member x • The difference between them is 10 minutes. • They estimate the difference to be 10 minutes • CH tells x: “Send the message to me at 6pm.” • x will compute: ”CH’s 6pm is my 6:10” and send at 6:10pm (by its own clock) • Now suppose their difference is 10 minutes, but they estimate the difference to be 9 minutes. • X will compute: “CH 6pm is my 6:09”transmit at 6:09 by its own clock  6:09 in x is 5:59pm in CH, not 6pm in CH!

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