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Information Quality Aware Routing in Event-Driven Sensor Networks

Information Quality Aware Routing in Event-Driven Sensor Networks. Hwee-Xian TAN 1 , Mun Choon CHAN 1 , Wendong XIAO 2 , Peng-Yong KONG 2 and Chen-Khong THAM 2 1 School of Computing, National University of Singapore (NUS) 2 Institute for Infocomm Research (I 2 R), Singapore. Overview.

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Information Quality Aware Routing in Event-Driven Sensor Networks

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  1. Information Quality Aware Routing in Event-Driven Sensor Networks Hwee-Xian TAN1, Mun Choon CHAN1, Wendong XIAO2, Peng-Yong KONG2 and Chen-Khong THAM2 1School of Computing, National University of Singapore (NUS) 2Institute for Infocomm Research (I2R), Singapore

  2. Overview Introduction Related Work and Motivation System Model Topology-Aware Histogram-Based Aggregation IQAR – Information Quality Aware Routing Protocol Performance Evaluation Concluding Remarks Information Quality Aware Routing in Event-Driven Sensor Networks

  3. PoI Fusion center v0 Node that does not detect PoI Node that detects PoI Introduction v3 v2 v5 v1 v0 v6 v4 v7 v8 v9 Information Quality Aware Routing in Event-Driven Sensor Networks • Event-driven sensor networks • Deployed specifically for detection of Phenomenon of Interest (PoIs) • Converge-cast traffic characteristics • Sensory data is generated by multiple sensors only when PoI is detected • Severe data implosion and redundancy

  4. Introduction • Data aggregation and/or fusion • Mitigates congestion and medium access contention • Suppresses data to reduce traffic load and energy consumption by exploiting spatio-temporal correlation among sensory data • Comes at expense of loss in information quality (IQ) of data collected at fusion center • Results in reduction of (event) detection accuracy Information Quality Aware Routing in Event-Driven Sensor Networks

  5. Related Work and Motivation Aggregation/Fusion based Routing IQ Aware Routing • Alleviates medium contention, reduces transmission costs and reduces e2e delays. • All sensory data is forwarded to fusion center, resulting in high data redundancy and energy costs. • Considers information content of data during aggregation/fusion and forwarding. • Neighbor with highest information gain is selected to be next-hop. • Fused data is transmitted to fusion center when IQ threshold is satisfied. • Typically query-based rather than event-based. IQAR considers information content, and addresses both event-detection and multi-hop networks. Information Quality Aware Routing in Event-Driven Sensor Networks

  6. System Model Network has n sensors and fusion center v0 H1 denotes presence of PoI H0 denotes absence of PoI P(H1) = p, P(H0) = 1-p 0 < p < 1 Sensor observations are assumed to be i.i.d. at each sensor as well as across sensors. Information Quality Aware Routing in Event-Driven Sensor Networks

  7. System Model Event Detection at Sensor Event Detection at Fusion Center • Independent signal yi observed by node vi is: • where wi is noise and ri is distance between vi and PoI. • For each sampled signal yi, vi makes a per-sample binary decision bi {0,1}: • where Ti is the per-sample threshold. Information Quality Aware Routing in Event-Driven Sensor Networks

  8. System Model Event Detection at Sensor Event Detection at Fusion Center • Independent signal yi observed by node vi is: • where wi is noise and ri is distance between vi and PoI. • For each sampled signal yi, vi makes a per-sample binary decision bi {0,1}: • where Ti is the per-sample threshold. • Fusion center v0 detects presence of PoI by making a global binary decision H={H0,H1} based on data received. • Optimal fusion rule is the Likelihood Ratio Test (LRT): • where B={b1,b2,..,b|Va|} is the set of per-sample binary decisions received; and Va is set of activated nodes. Information Quality Aware Routing in Event-Driven Sensor Networks

  9. v1 vi v2 v3 IQ of node vi System Model Sequential Detection • Data acquisition can terminate at earliest subsequence of data which satisfies a pre-determined IQ threshold. • Reduces amount of data required to make an accurate global binary decision H = {H0,H1}. • Cumulative log-likelihood ratio at fusion center v0 is: where Va is set of activated nodes. • Cumulative log-likelihood at vi is: upstream nodes of vi Information Quality Aware Routing in Event-Driven Sensor Networks

  10. Topology-Aware Histogram-based Aggregation With Global View & Topological Knowledge v1 v4 v9 0.3 0.1 1.7 v5 v10 v2 1.0 0.2 v0 0.4 v6 v11 0.5 0.3 v12 v7 v3 0.8 0.4 1.2 v8 0.6 High communication costs and overheads! Information Quality Aware Routing in Event-Driven Sensor Networks 10

  11. Topology-Aware Histogram-based Aggregation Max IQ using subtree rooted at v1 histogram {0.3, 2.1, 3, {2, 0, 1, 0, 0}} Max cost using subtree rooted at v1 IQ of v1 v1 v4 v9 0.3 0.1 1.7 v5 v10 v2 1.0 0.2 0.4 v0 v6 v11 0.5 0.3 v12 v7 v3 0.8 0.4 1.2 v8 0.6 Information Quality Aware Routing in Event-Driven Sensor Networks 11

  12. Topology-Aware Histogram-based Aggregation Max IQ using subtree rooted at v2 histogram {0.4, 3.2, 6, {1, 2, 2, 1, 0}} Max cost using subtree rooted at v2 IQ of v2 v1 v4 v9 0.3 0.1 1.7 v5 v10 v2 1.0 0.2 0.4 v0 v6 v11 0.5 0.3 v12 v7 v3 0.8 0.4 1.2 v8 0.6 Information Quality Aware Routing in Event-Driven Sensor Networks 12

  13. IQ-Aware Routing Protocol Initialization Aggregation and Update Pruning v1 v4 v9 v5 v10 v2 v0 v6 v11 v12 v7 v3 v8 Information Quality Aware Routing in Event-Driven Sensor Networks

  14. IQ-Aware Routing Protocol Initialization Aggregation and Update Pruning v1 v4 v9 0.1 v5 v10 v2 1.0 0.2 0.4 v0 v6 v11 0.5 0.3 v12 v7 v3 0.8 0.4 v8 Information Quality Aware Routing in Event-Driven Sensor Networks

  15. IQ-Aware Routing Protocol Initialization Aggregation and Update Pruning • Objective is to prune off as many nodes as possible from initial distance-based aggregation tree such that: • IQ constraint is still satisfied. • Total transmission cost is minimized. v1 v4 v9 0.1 v5 v10 v2 1.0 0.2 0.4 v0 v6 v11 0.5 0.3 v12 v7 v3 0.8 0.4 v8 Information Quality Aware Routing in Event-Driven Sensor Networks 15

  16. Performance Evaluation Simulator: Qualnet 4.0 Fusion center near bottom left-hand corner of terrain. Exponential sensing model. Information Quality Aware Routing in Event-Driven Sensor Networks

  17. Performance Evaluation v3 v2 v5 0.8 v1 v0 v6 v4 aggTree 1.1 0.5 0.6 0.3 v7 v8 v9 v3 v2 v5 0.8 v1 v0 v6 v4 walk 1.1 0.5 0.6 0.3 v7 v8 v9 v3 v2 v5 0.8 v1 v0 v6 v4 brute-force 1.1 0.5 0.6 0.3 v7 v8 v9 Information Quality Aware Routing in Event-Driven Sensor Networks

  18. Performance Evaluation Information Quality Aware Routing in Event-Driven Sensor Networks

  19. Performance Evaluation Information Quality Aware Routing in Event-Driven Sensor Networks

  20. Concluding Remarks IQAR Considers individual IQ contributions of each sensory data, and collects only sufficient data for PoI to be detected reliably. Utilizes a compact topology-aware histogram to represent the IQ contributions of nodes in the network. Redundant data is suppressed for time interval to reduce traffic load and alleviate medium access contention. Achieves significant energy and delay savings while maintaining IQ. Information Quality Aware Routing in Event-Driven Sensor Networks

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