Optimal sensor deployment for wireless surveillance sensor networks by a hybrid steady-state genetic algorithm

IEICE Transactions on Communications

Volumn E91-B, Issue 11, 2008, Pages 3534-3543

  Seo, Jae Hyun ^a   Kim, Yong Hyuk ^a   Ryou, Hwang Bin ^a   Cha, Si Ho ^b   Jo, Minho ^c  

^a Kwangwoon University   (South Korea)

^b Sejong University   (South Korea)

^c Korea University   (South Korea)

Author keywords

Hybrid steady state genetic algorithm; Surveillance sensor deployment; Wireless sensor networks

Indexed keywords

COMPUTATIONAL EFFICIENCY; GENETIC ALGORITHMS; MONITORING;

CLASSIFICATION RATES; COMPUTATIONAL OVERHEADS; CROSSOVER AND MUTATION; OPTIMAL SENSOR PLACEMENT; STEADY-STATE GENETIC ALGORITHMS; SURVEILLANCE SENSORS; TARGET IDENTIFICATION; TARGETS OF INTEREST;

WIRELESS SENSOR NETWORKS;

EID: 67651112004     PISSN: 09168516     EISSN: 17451345     Source Type: Journal    
DOI: 10.1093/ietcom/e91-b.11.3534     Document Type: Article

References (16)

1. D. Culler, D. Estrin, and M. Srivastava, "Overview of sensor networks," Computer, vol. 37, no. 8, pp. 41-49, Aug. 2004.
2. X. Xu and S. Sahni, "Approximation algorithms for wireless sensor deployment," IEEE Trans. Comput., vol. 56, no. 12, pp. 1681-1695, Dec. 2007.
3. S.-H. Cha, J.-E. Lee, M. Jo, H. Y. Youn, S. Kang, and K.-H. Cho, "Policy-based management for self-managing wireless sensor networks," IEICE Trans. Commun., vol. E90-B, no. 11, pp. 3024-3033, Nov. 2007.
4. L. M. J. Lamm, Develop Measures of Effectiveness and Deployment Optimization Rules for Networked Ground Micro-sensors, M. S. Thesis, Division of Systems Engineering, School of Engineering and Applied Science, University of Virginia, May 2001.
5. L. M. J. Lamm, G. A. Lamm, P. J. Driscoll, B. Klimack, and M. L. McGinnis, "Networked unattended ground sensor fields: Tradeoff study and configuration rules methodology," USMA Operations Research Center Technical Report, West Point, New York, Aug. 2002.
6. R. H. Myers and D. G. Montgomery, Response Surface Methodology, John Wiley & Sons, New York, 1987.
7. Y. Zou and K. Chakrabarty, "Sensor deployment and target localization based on virtual forces," Proc. IEEE Infocom Conference, pp. 1293-1303, March 2003.
8. G. Wang, G. Cao, T. L. Porta, and W. Zhang, "Sensor relocation in mobile sensor networks," IEEE Infocom Conference, pp. 2302-2312, March 2005.
9. C. Sharp, S. Schaffert, A. Woo, N. Sastry, C. Karlof, S. Sastry, and D. Culler, "Design and implementation of a sensor network system for vehicle tracking and autonomous interception," European Workshop on Sensor Networks, pp. 93-107, 2005.
10. Y. Xu and X. Yao, "A GA approach to the optimal placement of sensors in wireless sensor networks with obstacles and preferences," Proc. 3rd IEEE Consumer Communications and Networking Conference, pp. 127-131, 2006.
11. C. Zhao, Z. Yu, and P. Chen, "Optimal deployment of nodes based on genetic algorithm in heterogeneous sensor networks," International Conference on, Wireless Communications, Networking and Mobile Computing, 2007, pp. 2743-2746, Sept. 2007.
12. N. Srour, "Unattended ground sensors a prospective for operational needs and requirements," Sensor and Electron Devices Directorate, U. S. Army Research Laboratory Technical Report, Oct. 1999.
13. J. Holland, Adaptation in Natural and Artificial Systems, University of Michigan Press, 1975.
14. C. Anderson, K. Jones, and J. Ryan, "A two-dimensional genetic algorithm for the Ising problem," Complex Systems, vol. 5, pp. 327-333, 1991.
15. D. Gale and L. S. Shapley, "College admissions and the stability of marriage," American Mathematical Monthly, vol. 69, pp. 9-14, 1962.
16. T. N. Bui and B. R. Moon, "Genetic algorithm and graph partitioning," IEEE Trans. Comput., vol. 45, no. 7, pp. 841-855, 1996.