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Achieving Long-Term Surveillance in VigilNet Tian He, Pascal Vicaire, Ting Yan, Qing Cao, Gang Zhou, Lin Gu, Liqian Luo, Radu Stoleru, John A. Stankovic,

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Presentation on theme: "Achieving Long-Term Surveillance in VigilNet Tian He, Pascal Vicaire, Ting Yan, Qing Cao, Gang Zhou, Lin Gu, Liqian Luo, Radu Stoleru, John A. Stankovic,"— Presentation transcript:

1 Achieving Long-Term Surveillance in VigilNet Tian He, Pascal Vicaire, Ting Yan, Qing Cao, Gang Zhou, Lin Gu, Liqian Luo, Radu Stoleru, John A. Stankovic, Tarek F. Abdelzaher Department of Computer Science University of Virginia Charlottesville, USA

2 Motivating Application: Battlefield Surveillance

3 Other Applications Wildlife Monitoring Alarm System Flock Protection Border Surveillance

4 Our Solution: VigilNet MICA2 / MICAz / XSM Motes MACSensor Drivers RoutingPower Mngt 1 Signal Filtering Time Sync LocalizationGroup Mngt Power Mng 2 Power Mngt 3 Programming Abstractions Target Classification Velocity / Trajectory Inference Physical Data-Link Routing Middleware Application

5 Focus of This Presentation: Power Consumption No power management => 4 days lifetime! 99% of energy consumed waiting for potential targets! Energy Distribution

6 Focus of This Presentation: Power Consumption Power management => 10 months lifetime!  Lifetime x 75 98% of energy consumed in sleep mode! Energy Distribution 98%

7 State of the Art Topics:  Hardware  Energy Scavenging  Topology Control  Sensing Coverage  Predefined Scheduling  Data Aggregation  Etc… Practicality? Performance in Real Deployments? Applicability to Surveillance System? Combination of Schemes?

8 Power Management in VigilNet Turning nodes off as often and as long as possible. Questions:  When to turn nodes off (to save power)?  When to wake nodes up (to optimize system performance)?  What are the tradeoffs? Combination of four schemes:  Node level power management.  Group level power management.  Network level power management.  On-demand wakeup.

9 Group Level: Sentry Selection Redundant Coverage!

10 Group Level: Sentry Selection Redundant Coverage! => Sentry Selection

11 Group Level: Sentry Selection Load Balancing?

12 Group Level: Sentry Selection Load Balancing? => Sentry Rotation

13 Group Level: Sentry Selection Tradeoff: Detection Latency versus Density Probability of Target Detected Within First 1,000m Number of Nodes in Area 100m x 1,000m 10010 1,000 Area 1,000m 100m Radius=20m Radius=8m Radius=2m 50125500

14 Sentry Level: Duty Cycle Scheduling Target Takes Time To Go Through the Network.

15 Sentry Level: Duty Cycle Scheduling Target Takes Time To Go Through the Network. => Duty Cycle Scheduling

16 Sentry Level: Duty Cycle Scheduling Putting It All Together

17 Sentry Level: Duty Cycle Scheduling Tradeoff: Detection Latency Versus Duty Cycle Area 1,000m 100m Probability of Target Detected Within First 1,000m Duty Cycle 40% 100% 0% 20% 1000 Nodes, V=10m/s 1000 Nodes, V=30m/s

18 Network Level: Tripwire Scheduling Exploiting Knowledge About the Target

19 Network Level: Tripwire Scheduling Exploiting Knowledge About the Target

20 Network Level: Tripwire Scheduling Tripwire partition based on distance to a base

21 On-Demand Wakeup Wakeup Wakeup Path To Base Station Wakeup Nodes For Future Detection

22 Details of Wakeup Operation Sleeping Node: Wakeup x% of the Time Wakeup Operation: Send Message with Long Preamble

23 Evaluation by Third Party: Test Field Mote Field 300m X 200m, 200 motes

24 Evaluation by Third Party: Interactive Display

25 Evaluation by Third Party: Detection, Classification, and Tracking 1.Initial Detection 2.Classification 3.Periodic updates Average Localization Error: 6.24m Average Velocity Error: 6%

26 Lifetime Evaluation: Hybrid Simulation

27 Key Results: Lifetime Lifetime  No Power Management => 4 Days  + Sentry Selection and Rotation => 28 Days  + Duty Cycle Scheduling => 5 Months (12.5% Duty Cycle)  + Tripwire Service => 10 Months (16 Tripwires, ¼ Awake) Tracking Performance Penalty  ~ 3 to 5 Seconds

28 Key Results: Detection Performance Penalty ~ 3 to 5 Seconds

29 Summary Successfully integrate 4 power management strategies into real system. Analytical model and extensive simulation to predict system performance under various configurations. Practical feasibility of tracking system using XSM2s with 10 months lifetime.

30 My Webpage: www.cs.virginia.edu/~pv9f www.cs.virginia.edu/~pv9f Tian’s Webpage: www.cs.umn.edu/~tianhe www.cs.umn.edu/~tianhe Research Group Webpage: www.cs.virginia.edu/~control www.cs.virginia.edu/~control Questions?


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