1 / 30

Achieving Long-Term Surveillance in VigilNet

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.

zeal
Download Presentation

Achieving Long-Term Surveillance in VigilNet

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

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 Flock Protection Alarm System Border Surveillance

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

  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! 98% Energy Distribution

  7. 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? State of the Art

  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 50 125 500 Probability of Target Detected Within First 1,000m Radius=20m Radius=8m Radius=2m 1,000m 1,000 10 100 100m Number of Nodes in Area 100m x 1,000m Area

  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 100% Probability of Target Detected Within First 1,000m 1000 Nodes, V=10m/s 1000 Nodes, V=30m/s 40% 0% 20% Duty Cycle 1,000m 100m Area

  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 Detection 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 300m X 200m, 200 motes Mote Field

  24. Evaluation by Third Party:Interactive Display

  25. 1.Initial Detection 2.Classification 3.Periodic updates Evaluation by Third Party:Detection, Classification, and Tracking 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 • Tian’s Webpage:www.cs.umn.edu/~tianhe • Research Group Webpage:www.cs.virginia.edu/~control Questions?

More Related