Analytic modeling of detection latency in mobile sensor networks

Proceedings of the Fifth International Conference on Information Processing in Sensor Networks, IPSN '06

Volumn 2006, Issue , 2006, Pages 194-201

  Chin, Tai Lin ^a   Ramanathan, Parameswaran ^a   Saluja, Kewal K ^a  

^a Wisconsin Electric Machines and Power Electronics Consortium   (United States)

Author keywords

Analytic model; Collaborative detection; Detection latency; Mobile sensor networks

Indexed keywords

ANALYTIC MODEL; COLLABORATIVE DETECTION; DETECTION LATENCY; MOBILE SENSOR NETWORKS;

DATA ACQUISITION; MATHEMATICAL MODELS; PACKET NETWORKS; PROBLEM SOLVING; SENSOR NETWORKS; TARGET TRACKING; INFORMATION RETRIEVAL; SENSOR DATA FUSION; WIRELESS SENSOR NETWORKS;

MOBILE TELECOMMUNICATION SYSTEMS; SIGNAL DETECTION;

EID: 34247374386     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1127777.1127810     Document Type: Conference Paper

References (30)

1. P. Santi and D. M. Blough. The critical transmitting range for connectivity in sparse wireless ad hoc networks. IEEE Transactions on Mobile Computing, 2:25-39, Jan. 2003.
2. R. Shah, S. Roy, S. Jain, and W. Brunette. Data MULEs: modeling a three-tier architecture for sparse sensor networks. In Proc. of the first IEEE International Workshop on Sensor Network Protocols and Applications, pages 30-41, May 2003.
3. W. Zhao, M. Arnmar, and E. Zegura. A message ferrying approach for data delivery in sparse mobile ad hoc networks. In ACM International Symposium on Mobile Ad Hoc Networking and Computing, pages 187-198, Roppongi, Japan, May 2004.
4. D. K. Goldenberg, J. Lin, A. S. Morse, B. E. Rosen, and Y. R. Yang. Towards mobility as a network control primitive. In ACM International Symposium on Mobile Ad Hoc Networking and Computing, pages 163-174, Roppongi, Japan, May 2004.
5. T.-L. Chin, P. Rarnanathan, K. K. Saluja, and K.-C. Wang. Exposure for collaborative detection using mobile sensor networks. In Proc. of MASS, Nov. 2005.
6. G. T. sibley, M. H. Rahimi, and G. S. Sukhatme. Robomote: A tiny mobile robot platform for large-scale ad-hoc sensor networks. In Proceedings of IEEE International Conference on Robotics and Automation, pages 1143-1148, 2002.
7. M. B. McMickell, B. Goodwine, and L. A. Montestruque. MICAbot: A robotic platform for large-scale distributed robotics. In Proceedings of IEEE International Conference on Robotics and Automation, pages 1600-1605, 2003.
8. M. Rahimi, H. Shah, G. S. Sukhatme, J. Heidemann, and D. Estrin. Studying the feasibility of energy harvesting in a mobile sensor network. In Proceedings of IEEE International Conference on Robotics and Automation, pages 19-24, 2003.
9. M. Haenggi. Mobile sensor-actuator networks: Opportunities and challenges. In Proceedings of IEEE International Workshop on Cellular Neural Networks and Their Applications, pages 283-290, 2002.
10. G. Kesidis, T. Konstantopoulos, and S. Phoha. Surveillance coverage of sensor networks under a random mobility strategy. In Proceedings of IEEE Sensors, pages 961-965, 2003.
11. J. S. Litt, E. Wong, M. J. Krasowski, and L. C. Greer. Cooperative multi-agent mobile sensor platforms for jet engine inspection - Concept and implementation. In Proceedings of International Conference on Integration of Knowledge Intensive Multi-Agent Systems, pages 716-721, 2003.
12. T. D. Parsons. Pursuit-evasion in a graph. In Y. Alani and D. R. Lick, editors, Theory and Application of Graphs, pages 426-441. Springer-Verlag, 1976.
13. N. Mediggo, S. L. Hakimi, M. R. Garey, D. S. Johnson, and C. H. Papadimitriou. The complexity of searching a graph. Journal of the ACM, 35(1):18-44, January 1988.
14. J. P. Hespanha, H. J. Kim, and S. Sastry. Multiple-agent probabilistic pursuit-evasion games. In Proceedings of the Conference on Decision and Control, December 1999.
15. T. S. Rappaport. Wireless communications : principles and practice. Prentice Hall, Upper Saddle River, N.J., 2002.
16. M. Hata. Empirical formula for propagation loss in land mobile radio service. IEEE Transactions on Vehicular Technology, 29:317-325, Aug. 1980.
17. G. R. Grimmett and D. R. Stirzaker. Probability and random processes. Oxford University Press, New York, 2001.
18. S. Meguerdichian, F. Koushanfar, M. Potkonjak, and M. Srivastava. Coverage problems in wireless ad-hoc sensor networks. In Proc. of INFOCOM, pages 1380-1387, Apr. 2001.
19. T. Clouqueur, V. Phipatanasuphorn, P. Ramanathan, and K. K. Saluja. Sensor deployment strategy for detection of targets traversing a region. Journal on Mobile Networks and Applications, pages 453-461, 2003.
20. A. Howard, M. Mataric, and G. Sukhatme. Mobile sensor network deployment using potential fields: A distributed, scalable solution to the area coverage problem. In DARS, June 2002.
21. Y. Zou and K. Chakrabarty. Sensor deployment and target localization in distributed sensor networks. ACM Trans. on Embedded Computing Sys., 3(1):61-91, 2004.
22. G. Wang, G. Cao, and T. La Porta. Movement-assisted sensor deployment. In Proc. of INFOCOM, pages 2469-2479, Mar. 2004.
23. B. Liu, P. Brass, O. Dousse, P. Nain, and D. Towsley. Mobility improves coverage of sensor networks. In Proceedings of the 6th ACM international symposium on Mobile ad hoc networking and computing, pages 300-308, Urbana-Champaign, IL, 2005. ACM Press.
24. M. Batalin, M. Rahimi, Y. Yu, D. Liu, A. Kansal, G. Sukhatme, W. Kaiser, M. Hansen, G. Pottie, M. Srivastava, and D. Estrin. Call and response: Experiments in sampling the environment. In SenSys 04, Baltimore, Maryland, Novemeber 3-5, 2004.
25. M. Rahimi, R. Pon, W. J. Kaiser, G. S. Sukhatme, D. Estrin, and M. Srivastava. Adaptive sampling for environmental robotics, in IEEE Int. Conf. on Robotics and Automation, New Orleans, LA, 2004.
26. D. MacKay. Information-based objective functions for active data selection. Neural Computation, 4(4):590-604, 1992.
27. R. Nowak, U. Mitra, and R. Willett. Estimating inhomogeneous fields using wireless sensor networks. IEEE Journal on Selected Areas in Communications, pages 999-1006, August 2004.
28. R. Willett, A. Martin, and R. Nowak. Backcasting: A new approach to energy conservation in sensor networks. Technical Report TRECE-03-4, University of Wisconsin, 2003.
29. K.-C. Wang and P. Ramanathan. Collaborative sensing using sensors of uncoordinated mobility. In DCOSS, pages 293-306, June 2005.
30. P. Juang, H. Oki, Y. Wang, M. Martonosi, L. Peh, and D. Rubenstein. Energy-efficient computing for wildlife tracking: Design tradeoffs and early experiences with Zebranet. In Proceedings of ASPLOS, pages 96-107, Oct. 2002.