1 / 21

Sink Deployment in Wireless Surveillance Networks

Sink Deployment in Wireless Surveillance Networks. Michael Chien -Chun Hung , Kate Ching-Ju Lin March 31, 2011. Network and Mobile System Lab(NMS Lab) Research Center for Information Technology Innovation (CITI) Academia Sinica , Taipei, Taiwan. Wireless Surveillance System (WSS).

ronnie
Download Presentation

Sink Deployment in Wireless Surveillance Networks

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. Sink Deployment in Wireless Surveillance Networks Michael Chien-Chun Hung, Kate Ching-Ju Lin March 31, 2011 Network and Mobile System Lab(NMS Lab) Research Center for Information Technology Innovation (CITI) Academia Sinica, Taipei, Taiwan

  2. Wireless Surveillance System (WSS) • Meerkat • Panoptes

  3. Camera Deployment • Camera placement • Environment-dependent • Location: where to put? • Angle: how to place ? • Camera management • Application-dependent • Resolution: how to set? • Tracking: how to group?

  4. Wireless Surveillance System Camera Deployment Sink Deployment Camera Placement Camera Management

  5. Sink Deployment: Scenario 1 A 2 Mbps Link reliability: 65% C 54 Mbps Link reliability: 85% B 1 Mbps Link reliability: 50%

  6. Sink Deployment: Scenario 2 • Camera’s demand rate • The sink should be closer to the camera with higher demand • Each camera should utilize the same bit-rate • The sink should have similar distance to all cameras C A 5.5 Mbps Link reliability: 60% 5.5 Mbps Link reliability: 50% B 5.5 Mbps Link reliability: 60%

  7. Sink Deployment • Goal: maximize overall satisfaction of all cameras • di: demand streaming rate of camera i • ui: effective throughput of camera i • Similar to circumcenter in a polygon • Circumcenter may not exist in general case • Exhausted searchis achievable • Enormous deployment-cost

  8. Spring-Cam Approach C dA = 1000 kbps dC = 750 kbps A A C B dB = 1500 kbps Vector Diagram SUM B

  9. Spring-Cam Framework • Step 1: Initialization • Origin (corner) • Central point • Average point • Average point weighted by the camera’s demand • Random • Step 2: Adjustment • Move the sink according to the net force of the mass-spring system

  10. Spring-Cam Framework (Cont.) • Step 3: Termination • When the potential energy cannot be further reduced • Step 4: Advanced search • (x,y): the result of step 3 • Spring-Cam+5 returns the best result within (x ± 5, y ± 5)

  11. Performance Evaluation • Parameters: • 350*350 square meter field • Demand rate between [500, 1000] kbps • Performance metric: • Total Satisfaction : • Hit Ratio: • , Hk =

  12. Total Satisfaction 23% Number of cameras ↑, performance metric ↓ Spring-Cam outperforms average location by 23% Advanced search ↑, performance metric ↑

  13. Hit Ratio Advanced search ↑, hit ratio ↑ Number of cameras ↑, hit ratio ↓

  14. Conclusion • Introducing sink deployment problem • Maximizing the overall satisfaction of all cameras • Proposing Spring-Cam • Locating the sink that satisfies each camera’s demand • Reducing the overhead of exhausted search

  15. Thank You for Your Attendance! Michael Chien-Chun Hung shinglee@citi.sinica.edu.tw http://nms.citi.sinia.edu.tw/shinglee Network and Mobile System Group(NMSGroup) Research Center for Innovation Technology Information (CITI) Academia Sinica, Taipei, Taiwan

  16. Appendix

  17. Sink deployment • Topology-dependent • Supplementary to camera deployment • Multiple bit-rates supported by IEEE 802.11 • Auto rate-selection based on transmission quality • Distance to the sink significantly affect SNR • 802.11 performance anomaly1 • Huge throughput decrement • Rate selection in WSSs is mutually dependent • 1 M. Heusse, F. Rousseau, G. Berger-Sabbatel and A. Duda, “Performance anomaly of 802.11 b” in INFOCOM’03

  18. System overview • Independent rate selectionfor each camera • The quality of the link between itself and the sink • Multi-path fading、interference、channel fading • Focus on channel fading determined by the distance • The impact of 802.11 performance anomaly • All cameras obtain similar throughput2 • : approximated achievable uploading throughput • pi: link reliability between camera i and the sink • 2 K.-J. Lin and C. fu Chou, “Exploiting multiple rates to maximize the throughput of wireless mesh networks,” IEEE Transactions on Wireless Communications, 2009

  19. System overview (cont.) ≒ • Maximizing equals to minimizing • By AM-GM Inequality Property: • Maximum: when all cameras use the same bit-rate • Bit-rate selection mainly bases on the distance • The sink must have similar distance to all cameras

  20. Spring-Cam in a nutshell • The sink must have similar distance to all cameras • zi: the distance between camera i and the sink • : the average distance of all zi • Similar to mass-spring system in Physics • A virtual spring connecting a camera and the sink • If zi > : the sink should be placed closer to camera i • If zi < : the sink should be placed further to camera i

  21. Spring-Cam Overview • Utilizing mass-spring operations • Virtual spring between the sink and each camera • Demand rate as elasticity coefficient. • Efficient in locating possible position • Promptly converge to a potential point • Supplementary to exhausted search • Reduce search cost

More Related