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A Mini-survey of Dealing with Faults in Wireless Sensor Networks

A Mini-survey of Dealing with Faults in Wireless Sensor Networks. Qi Han. Motivation. Understanding packet delivery performance In dense wireless sensor networks J. Zhao and R. Govindan, SenSys 2003 (Best Paper Award)

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A Mini-survey of Dealing with Faults in Wireless Sensor Networks

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  1. A Mini-survey of Dealing with Faults in Wireless Sensor Networks Qi Han

  2. Motivation Understanding packet delivery performance In dense wireless sensor networks J. Zhao and R. Govindan, SenSys 2003 (Best Paper Award) Taming the underlying challenges of reliable multihop routing in sensor networks A. Woo, T. Tong and D. Culler, SenSys 2003 • Current WSNs exhibit high loss rates • In indoor environments, • half of the links: 10% packet loss • A third links: 30% packet loss • At MAC layer, link-layer re-transmissions are unable to mask this loss Assuming packet loss rate is p, then the probability that a message is successfully received Across n hops is (1-p)n

  3. Strategies to deal with faults • MAC layer • Apply ARQ • Network layer: • Select high quality paths for data transmission • Multi-path routing • Braided Diffusion • GRAB (Gradient Broadcast) • Transport layer • Downstream data delivery • PSFQ, GARUDA • Upstream data delivery • TAG, ESRT

  4. Braided Diffusion D. Ganesan, R. Govindan, S. Shenker, D. EstrinMobiHoc 2001 and MC2R 2002 • How to perform energy-efficient and robust dissemination of data from sources to sinks • tradeoff between resilience and energy consumed • Based on directed diffusion: • Construct dissemination path from multiple sources to multiple sinks on-demand

  5. Directed Diffusion • Source periodically broadcasts events at a low rate • Sink sends a reinforcement message to one of its neighbors • The message is propagated to the source, hop by hop • When a node on the reinforced path fails, the sink re-initiates reinforcement • Drawback: A periodic low-rate flooding scheme notifies the sink and other nodes • of available alternate paths --- Consumes energy

  6. Disjoint Multipath Localized algorithm: -using local information - use two kinds of reinforcements

  7. Braided Multipath - Alternate paths in a braid are partially disjoint from the primary path

  8. Failure Models (used for evaluation) • Isolated failures: • capture independent node failures • Patterned failures: • capture geographically correlated failures

  9. Gradient Broadcast F. Ye, G. Zhong, S. Lu, L. X. Zhang ACM WINET 2005 • The sink builds a cost field • Cost at a node: minimum energy overhead to forward a packet from this node to the sink along the path • The cost field gives the global direction towards the sink implicitly • At each hop, only nodes that have costs smaller than the sender can forward the packet

  10. Credit-based Forwarding Mesh • Limit the ‘width’ of the forwarding mesh • More than enough paths of decreasing cost exist • A source assigns a credit to the packets it sends out • Credit: An extra budget that can be used to send a packet to the sink along a path • The amount of credit controls the redundancy of the mesh

  11. Reliable Downstream Sensor Data Delivery • Data flows from sink to sources for the purpose of control or management • PSFQ • Assumptions: message loss occurs due to the poor quality of wireless links • Hop-by-hop recovery: node • In-sequence forwarding • GARUDA: reliable delivery • To all sensors, • To a sub-region, • To minimal sensors to cover the sensing field • To a certain percentage of the sensors

  12. Reliable Upstream Sensor Data Delivery • Data flows from sources to sink • TAG (Tiny Aggregation): • A node switches its parent in two cases: • Each node monitors the quality of the link to each of its neighbors by tracking the proportion of packets received from each neighbor • When a node observes that it has not heard from its parent for some fixed period of time, it assumes that its parent has failed

  13. ESRT: Event-to-Sink Reliable Transport in WSN [Y. Sankarasubramaniam, O. B. Zkan, I. F. Akyildiz, ACM MobiHoc 2003] A sensor node that can sense the event Event! Sink wants reliable event detection with minimum energy expenditure A sensor node [Slides modified based on the class presentation of A. Abouzeid from RPI]

  14. Problem Definition • Motivating application: • Reliable detection/estimation of event features based on the collective reports from a number of sensors, not on individual sensor reports • The sink must decide on the event feature every  time units • Definition • The reliability of even feature is measured by the number of received data packets • Observed event reliability ri • Desired event reliability R • Problem statement: (congestion solution) • Model any increase in source information as a increase in the sensor reporting rate f • To configure the reporting rate f of source nodes so as to achieve the required event detection reliabilityRat the sink with minimum resourceutilization

  15. Evaluation Environments-- to study the relationship between f and r • ns-2 simulator • 200 sensor nodes • 100m x 100m area • 40m transmission range • 30 byte packets • 65 packets buffer size • 10 sec decision interval (τ)

  16. network gets congested sooner with increasing number of source nodes r linearly increases with f until f=fmax, then drops After fmax, it is wavy with increasing n, the drop in r is more significant Effect of varying sensor reporting rate f on the event reliability r This confirms the need for a reliable transport solution with a congestion control mechanism

  17. Five characteristic regions Not Congested Congested Higher reliability than required Lower reliability than required Goal: To stay in OOR where energy expenditure is optimal OOR

  18. Main Idea of ESRT • Sink • Based on current state Si, calculates a updated reporting frequency fi+1, broadcasts it to sensor ndoes • Si {(NC,LR),(C,LR)}: aggressively update f to reliably track event ASAP (Primary objective: reliably detect event) • Si{(NC,HR),(C,HR)}: decrease f conservatively (Secondary objective: conserve energy) • Sensors • Listen to the sink broadcast at the end of each decision interval and update f • Deploy a local congestion detection support mechanism

  19. ESRT Actions

  20. Stability of ESRT • ESRT converges to OOR from any of four initial states {(NC,LR), (NC,HR), (C,HR), (C,LR)} • From (NC,HR), ESRT stays in the state until converges to OOR • Convergence time depends on ε – smaller ε causes longer convergence time

  21. Congestion Detection • Congestion status is required at the sink to determine the network state • Based on expectation of buffer overflow at sensor nodes • During a single interval, f and n do not change much • If pending congestion (bk+b>B) is detected CN bit is set in event reports

  22. From (NC,LR) Reaches OOR in two intervals

  23. From (NC,HR) ESRT stays in (NC,HR) until reaching OOR in five intervals

  24. (C,HR) to (NC,HR) then OOR

  25. (C,LR) to (NC,LR) then OOR

  26. Power savings from (NC,HR) Reporting rate gets reduced conservatively while maintaining reliability

  27. What I like about the paper • Collective reliability • Individual sensor ID is not necessary • Each source attaches event ID • Biased implementation • Almost entirely in sink

  28. What I dislike about this paper • Sink must broadcast the updated reporting frequency at high energy so that all sources can hear it • Ongoing event transmission would be disrupted • Regulating all sensors to have the same reporting rate may not work well with heterogeneous sensors • Assuming that sensors report periodically may not be true for all applications • Congestion in WSN not just caused by frequent sensor reporting

  29. My class project- reliable upstream data delivery • Acquisitional query • How to interpret the answer A • Is A based on a very incomplete subset • What about the remaining sensors • Query may specify its reliability requirements(how good it wants A to be) • Percentage of sensors (e.g. A is based on reports from 80% of the sensors) • Recall (answer-set/exact-set)

  30. Quality Metrics Sensors of interest N Answer Nyes Missing at most N-Nyes-Nno Answer Nyes Answer Nyes Nno recall r=Nyes/(N-Nno)

  31. Problem Description Given: 1 sink (where continuous queries are injected) and n sensors with constant failures in the sensor network Objective: minimize energy consumption s.t. r>=R, where r=Nyes/(N-Nno)

  32. Issues to Address • How to distribute rq from the sink to intermediate nodes ? • Given the assigned rq’, what should each intermediate node do after finishing the transmission of the reports from all children? • Go to sleep immediately • Re-transmit immediately • Stay awake in case re-transmission is requeted

  33. Our Approaches • To come

  34. Evaluation Methodology • ns-2 simulator • Comparison against • Plain collection (CSMA/CA) • Link layer acknowledgement (CSMA/CA + ack/re-transmission) • Multi-path routing

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