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Optimal and Approximate Approaches for Deployment of Heterogeneous Sensing Devices

EURASIP Journal on Wireless Communications and Networking volume 2007, Article number: 054731 (2007) Cite this article

Abstract

A modeling framework for the problem of deploying a set of heterogeneous sensors in a field with time-varying differential surveillance requirements is presented. The problem is formulated as mixed integer mathematical program with the objective to maximize coverage of a given field. Two metaheuristics are used to solve this problem. The first heuristic adopts a genetic algorithm (GA) approach while the second heuristic implements a simulated annealing (SA) algorithm. A set of experiments is used to illustrate the capabilities of the developed models and to compare their performance. The experiments investigate the effect of parameters related to the size of the sensor deployment problem including number of deployed sensors, size of the monitored field, and length of the monitoring horizon. They also examine several endogenous parameters related to the developed GA and SA algorithms.

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References

  1. Mainwaring A, Polastre J, Szewczyk R, Culler D, Anderson J: Wireless sensor networks for habitat monitoring. Proceedings of the 1st ACM International Workshop on Wireless Sensor Networks and Applications (WSNA '02), September 2002, Atlanta, Ga, USA 88-97.

    Chapter  Google Scholar 

  2. Kuorilehto M, Hännikäinen M, Hämäläinen TD: A survey of application distribution in wireless sensor networks. EURASIP Journal on Wireless Communications and Networking 2005,2005(5):774-788.

    Article  MATH  Google Scholar 

  3. Nguyen NT, Venkatesh S, West G, Bui HH: Multiple camera coordination in a surveillance system. Acta Automatica Sinica 2003,29(3):408-422.

    Google Scholar 

  4. Akyildiz IF, Su W, Sankarasubramaniam Y, Cayirci E: Wireless sensor networks: a survey. Computer Networks 2002,38(4):393-422. 10.1016/S1389-1286(01)00302-4

    Article  Google Scholar 

  5. Ilyas M, Mahgoub I: Handbook of Sensor Networks. CRC Press, Boca Raton, Fla, USA; 2005.

    Google Scholar 

  6. Estrin D, Girod L, Pottie G, Srivastava M: Instrumenting the world with wireless sensor networks. Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP '01), May 2001, Salt Lake, Utah, USA 4: 2033-2036.

    Google Scholar 

  7. Li D, Wong KD, Hu YH, Sayeed AM: Detection, classification, and tracking of targets. IEEE Signal Processing Magazine 2002,19(2):17-29. 10.1109/79.985674

    Article  Google Scholar 

  8. Chvátal V: A combinatorial theorem in plane geometry. Journal of Computorial Theory (B) 1975, 18: 39-41. 10.1016/0095-8956(75)90061-1

    Article  MATH  Google Scholar 

  9. O'Rourke J: Galleries need fewer mobile guards: a variation on Chvátal's theorem. Geometriae Dedicata 1983,14(3):273-283.

    Article  MATH  MathSciNet  Google Scholar 

  10. Chakrabarty K, Iyengar SS, Qi H, Cho E: Grid coverage for surveillance and target location in distributed sensor networks. IEEE Transactions on Computers 2002,51(12):1448-1453. 10.1109/TC.2002.1146711

    Article  MathSciNet  Google Scholar 

  11. Cardei M, Wu J: Coverage in wireless sensor networks. In Handbook of Sensor Networks. Edited by: Ilyas M, Mahgoub I. CRC Press, Boca Raton, Fla, USA; 2004.

    Google Scholar 

  12. Isler V, Kannan S, Daniilidis K: Sampling based sensor-network deployment. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '04), September-October 2004, Sendai, Japan 2: 1780-1785.

    Google Scholar 

  13. Liu X, Mahapatra P: On the deployment of wireless sensor nodes. Proceedings of the 3rd International Workshop on Measurement, Modeling, and Performance Analysis of Wireless Sensor Networks, in Conjunction with the 2nd Annual International Conference on Mobile and Ubiquitous Systems, July 2005, San Diego, Calif, USA

    Google Scholar 

  14. Hu W, Chou C, Jha S, Bulusu N: Deploying long-lived and cost-effective hybrid sensor networks. Proceedings of the 1st Workshop on Broadband Advanced Sensor Networks (BaseNets '04), October 2004, San Jose, Calif, USA

    Google Scholar 

  15. Lee J-J, Krishnamachari B, Kuo C-CJ: Impact of heterogeneous deployment on lifetime sensing coverage in sensor networks. Proceedings of the 1st Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks (SECON '04), October 2004, Santa Clara, Calif, USA 367-376.

    Google Scholar 

  16. Wang G, Cao G, La Porta TF: Movement-assisted sensor deployment. IEEE Transactions on Mobile Computing 2006,5(6):640-652.

    Article  Google Scholar 

  17. Poduri S, Sukhatme GS: Constrained coverage for mobile sensor networks. Proceedings of IEEE International Conference on Robotics and Automation (ICRA '04), April-May 2004, New Orleans, La, USA 165-171.

    Google Scholar 

  18. Howard A, Mataríc MJ, Sukhatme GS: An incremental self-deployment algorithm for mobile sensor networks. Autonomous Robots 2002,13(2):113-126. 10.1023/A:1019625207705

    Article  MATH  Google Scholar 

  19. Dhillon SS, Chakrabarty K, Iyengar SS: Sensor placement for grid coverage under imprecise detections. Proceedings of the 5th International Conference on Information Fusion, July 2002, Washington, DC, USA 2: 1581-1587.

    Article  Google Scholar 

  20. Zou Y, Chakrabarty K: Sensor deployment and target localization in distributed sensor networks. ACM Transactions on Embedded Computing Systems 2004,3(1):61-91. 10.1145/972627.972631

    Article  Google Scholar 

  21. Zou Y, Chakrabarty K: Sensor deployment and target localization based on virtual forces. Proceedings of the 22nd Annual Joint Conference on the IEEE Computer and Communications Societies (INFOCOM '03), March-April 2003, San Francisco, Calif, USA 2: 1293-1303.

    Google Scholar 

  22. Lee J-J, Krishnamachari B, Kuo C-CJ: Node aging effect on connectivity of data gathering trees in sensor networks. Proceedings of the 60th IEEE Vehicular Technology Conference (VTC '04), September 2004, Los Angeles, Calif, USA 4630-4634.

    Google Scholar 

  23. Ye W, Heidemann J, Estrin D: An energy-efficient MAC protocol for wireless sensor networks. Proceedings of the 21st Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM '02), June 2002, New York, NY, USA 3: 1567-1576.

    Google Scholar 

  24. Xu Y, Heidemann J, Estrin D: Geography-informed energy conservation for ad hoc routing. Proceedings of the Annual International Conference on Mobile Computing and Networking (MOBICOM '01), July 2001, Rome, Italy 70-84.

    Chapter  Google Scholar 

  25. Gage D: Command control for many-robot systems. Proceedings of the 19th Annual Technical Symposium and Exhibition of the Association for Unmanned Vehicle Systems (AUVS '92), June 1992, Huntsville, Ala, USA

    Google Scholar 

  26. Huang C-F, Tseng Y-C: The coverage problem in a wireless sensor network. Proceedings of the 2nd ACM International Workshop on Wireless Sensor Networks and Applications (WSNA '03), September 2003, San Diego, Calif, USA 115-121.

    Google Scholar 

  27. Zhou Z, Das S, Gupta H: Connected K-coverage problem in sensor networks. Proceedings of the 13th International Conference on Computer Communications and Networks (ICCCN '04), October 2004, Chicago, Ill, USA 373-378.

    Google Scholar 

  28. Lee DT, Lin AK: Computational complexity of art gallery problems. IEEE Transactions on Information Theory 1986,32(2):276-282. 10.1109/TIT.1986.1057165

    Article  MATH  MathSciNet  Google Scholar 

  29. Gwiazda, Tomasz, Dominik A: Genetic Algorithms Reference Volume I Crossover for Single-Objective Numerical Optimization Problems. Tomasz Gwiazda, Lomianki, Poland; 2006.

    Google Scholar 

  30. Goldberg D: Genetic Algorithms in Search, Optimization and Machine Learning. Kluwer Academic, Boston, Mass, USA; 1989.

    MATH  Google Scholar 

  31. Randy L, Haupt S: Practical Genetic Algorithms. John Wiley & Sons, New York, NY, USA; 2004.

    MATH  Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Southern Methodist University, Dallas, TX, 75275-0122, USA

    Rabie Ramadan & Hesham El-Rewini

  2. Department of Environmental and Civil Engineering, Southern Methodist University, Dallas, TX, 75275-0340, USA

    Khaled Abdelghany

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  1. Rabie Ramadan
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  2. Hesham El-Rewini
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  3. Khaled Abdelghany
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Correspondence to Rabie Ramadan.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Ramadan, R., El-Rewini, H. & Abdelghany, K. Optimal and Approximate Approaches for Deployment of Heterogeneous Sensing Devices. J Wireless Com Network 2007, 054731 (2007). https://doi.org/10.1155/2007/54731

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