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An Efficient Distributed Collaborative Camera Actuation Algorithm for Redundant Data Elimination for Event Detection and Monitoring in Wireless Multimedia Sensor Networks

by Ahmed Salim, Hagar Ramdan
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 155 - Number 6
Year of Publication: 2016
Authors: Ahmed Salim, Hagar Ramdan
10.5120/ijca2016912331

Ahmed Salim, Hagar Ramdan . An Efficient Distributed Collaborative Camera Actuation Algorithm for Redundant Data Elimination for Event Detection and Monitoring in Wireless Multimedia Sensor Networks. International Journal of Computer Applications. 155, 6 ( Dec 2016), 1-10. DOI=10.5120/ijca2016912331

@article{ 10.5120/ijca2016912331,
author = { Ahmed Salim, Hagar Ramdan },
title = { An Efficient Distributed Collaborative Camera Actuation Algorithm for Redundant Data Elimination for Event Detection and Monitoring in Wireless Multimedia Sensor Networks },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2016 },
volume = { 155 },
number = { 6 },
month = { Dec },
year = { 2016 },
issn = { 0975-8887 },
pages = { 1-10 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume155/number6/26606-2016912331/ },
doi = { 10.5120/ijca2016912331 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:00:31.239106+05:30
%A Ahmed Salim
%A Hagar Ramdan
%T An Efficient Distributed Collaborative Camera Actuation Algorithm for Redundant Data Elimination for Event Detection and Monitoring in Wireless Multimedia Sensor Networks
%J International Journal of Computer Applications
%@ 0975-8887
%V 155
%N 6
%P 1-10
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Wireless Multimedia Sensor Network(WMSN) is an extension of Wireless Sensor Network(WSN), where in addition to scalar sensors camera sensors are present. In wireless multimedia sensor networks (WMSNs), a high cost of processing and communicating the multimedia data is required. So it is critical to reduce possible data redundancy. Data redundancy occurs due to overlapping of Field of view (FOV) of camera sensors. Data redundancy affects on the communication cost in terms of bandwidth used, CPU processing etc. increases. Therefore, camera sensors should only be actuated when an event is detected within their vicinity. The scalar sensors first detect the occurrence of an event in the region of interest. Then the scalar sensors reports their corresponding camera sensors regarding the occurrence of event. In this paper, a distributed actuation scheme is proposed which depends to activate the least number of cameras while still preserving the necessary event coverage to avoid possible redundancy in the multimedia data. Even though the camera sensors have heard from scalar sensors about an occurring event, they may not cover the event. These nodes unnecessarily undergo distributed camera actuation scheme and some or all of them are activated. So our objective is to keep such cameras in turned off condition and to activate optimum number of camera sensors while preserving the necessary event coverage. The basic idea of this scheme is the collaboration of camera sensors that have heard from scalar sensors about an occurring event to minimize the possible coverage overlaps and also their FoVs intersect with the event region. This paper also proposes distributed actuation schemes for monitoring the event boundary. Simulation are presented to show the performance of our and other work in terms of coverage ratio, and the number of activated camera sensors under several random deployment schemes.

References
  1. I. F. Akyildiz , W. Su , Y. Sankarasubramaniam , Y. , and E. Cayirci , Wireless sensor networks: A survey , Computer Networks (Elsevier) Journal , vol. 38 , no. 4 , Mar. 2002 , pp. 393 422.
  2. I. F. Akyildiz , T. Melodia , and K. R. Chowdhury , A survey on wireless multimedia sensor networks , Computer Networks (Elsevier) , vol. 51 , no. 4, Mar. 2007 , pp. 921 960 .
  3. M. Rahimi, R. Baer, O.I. Iroezi, J.C. Garcia, J. Warrior, D. Estrin, M. Srivastava, Cyclops: in situ image sensing and interpretation in wireless sensor networks, in: ACM Conference on Embedded Networked Sensor Systems (SenSys), San Diego, CA, 2006.
  4. S. Hengstler, D. Prashanth, S. Fong, H. Aghajan, Mesheye: a hybridresolution smart camera mote for applications in distributed intelligent surveillance, in: Information Processing in Sensor Networks (IPSN-SPOTS), Cambridge, MA, April 2007.
  5. Crossbow IMote2. ¡http://www.xbow.com.
  6. A. Rowe, A. Goode, D. Goel, I. Nourbakhsh, CmuCam3: An Open Programmable Embedded Vision Sensor, in: Technical Report, RI-TR- 07-13, Carnegie Mellon Robotics Institute, 2007.
  7. Andrew Newell, Kemal Akkaya.,”Distributed collaborative camera actuation for redundant data elimination in Wireless Multimedia Sensor Networks”, AdHoc Networks, vol 9, pp. 514-527, 2011.
  8. K. Akkaya, M. Demirbas, R.S. Aygun, The impact of data aggregation on the performance of wireless sensor networks, Wireless Communications and Mobile Computing Journal 8 (2008) 171193.
  9. Z. Xue, K. Loo, J. Cosmas, P. Yip, Distributed video coding in wireless multimedia sensor network for multimedia broadcasting, WSEAS Transactions on Communications 7 (2008) 418427.
  10. T. Melodia, I.F. Akyildiz, Cross-layer quality of service support for uwb wireless multimedia sensor networks, in: IEEE INFOCOM, Mini- Conference, Phoenix, AZ, April 2008.
  11. L. Savidge, H. Lee, H. Aghajan, A. Goldsmith, Qos-based geographic routing for event-driven image sensor networks, in: Broadband Advanced Sensor Networks (BaseNets), Boston, MA, October 2005.
  12. J. ORourke, Open problem from art gallery solved, International Journal of Computational Geometry and Applications 2 (1992) 215 217.
  13. X. Han, X. Cao, E. Lloyd, C.-C. Shen, Deploying directional sensor networks with guaranteed connectivity and coverage, in: 5th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, 2008, SECON 08, 2008, pp. 153160. doi:10.1109/SAHCN.2008.28.
  14. J. Ai and A. Abouzeid, Coverage by directional sensors in randomly deployed wireless sensor networks, Journal of Combinatorial Optimization, vol. 11, no. 1, pp. 2141, 2006.
  15. Y. Cai, W. Lou, M. Li, and X.-Y. Li, Target-oriented scheduling in directional sensor networks, in Proceedings of IEEE INFOCOM, 2007.
  16. H. Ma and Y. Liu, Some problems of directional sensor networks, International Journal of Sensor Networks, vol. 2, no. 1/2, pp. 4452, 2007
  17. Mittal, A.; Davis, L. Visibility Analysis and Sensor Planning in Dynamic Environments. In Proceedings of 8th European Conference on Computer Vision, Prague, Czech Republic, May 1114, 2004; pp. 175-189.
  18. Pito, R. A Solution to the Next Best View Problem for Automated Surface Acquisition. IEEE Trans. Patt. Anal. Mach. Int. 1999, 21, 1016-1030.
  19. Mayer, J.; Bajcsy, R. Occlusions as a Guide for Planning the Next View. IEEE Trans. Patt. Anal. Mach. Int. 1993, 15, 417- 433.
  20. R. Dai, I. Akyildiz, A spatial correlation model for visual information in wireless multimedia sensor networks, Multimedia, IEEE Transactions 11 (6) (2009) 11481159, doi:10.1109/ TMM.2009.2026100.
  21. N. Tezcan, W. Wang, Self-orienting wireless multimedia sensor networks for occlusion-free viewpoints, Computer Networks 52 (2008) 25582567.
  22. article/cuj geometry article.html, accessed 4/07/2015. N. Patwari, J.N. Ash, S. Kyperountas, A.O. Hero, R.L. Moses, N.S. Correal, Locating the nodes: cooperative localization in wireless sensor networks, Signal Processing Magazine, IEEE 22 (4) (2005) 54 69.
  23. K. Ren, K. Zeng, W. Lou, Fault-tolerant event boundary detection in wireless sensor networks, in: IEEE GLOBECOM, vol. 7, 2006, pp. 354 363.
  24. M. Ding, D. Chen, K. Xing, X. Cheng, Localized faulttolerant event boundary detection in sensor networks, vol. 2, 2005, pp. 902913. doi:10.1109/INFCOM.2005.1498320.
  25. C. Moreno, http://www.mochima.com/articles/cuj geo metry
  26. Zhong C, Worboys M (2007) Energy-efficient continuous boundary monitoring in sensor networks. Technical report.
  27. A. Mainwaring, J. Polastre, R. Szewczyk, D. Culler, and J. Anderson, Wireless Sensor Networks for Habitat Monitoring, ACM WSNA02, Atlanta GA, September 2002.
  28. N. Xu, A Survey of Sensor Network Applications, http://enl.usc.edu/ ningxu/papers/survey.pdf
  29. B. Krishnamachari and S. Iyengar, Distributed Bayesian Algorithms for Fault-Tolerant Event Region Detection in Wireless Sensor Networks, IEEE Transactions on Computers, Vol. 53, No. 3, pp. 241-250, March 2004.
  30. M. Ding, D. Chen, K. Xing, and X. Cheng, Localized Fault- Tolerant Event Boundary Detection in Sensor Networks, IEEE INFOCOM 2005, 13-17 March 2005.
Index Terms

Computer Science
Information Sciences

Keywords

Wireless Multimedia Sensor Network(WMSN) boundary node event detection camera actuation Field of View(FoV) redundancy scalar sensors

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