Simon Shamoun
ABSTRACT
We study the problem of dynamically selecting sensors to maximize the number of steps covered on the path of a mobile target. The sensors are selected from those already deployed in a network as the target moves. The total number of sensors selected and rounds of selection are limited according to budget constraints. The variables are which sensors to select, when, and how. The best settings depend on how much is known about the target's path, such as its start and end locations and mobility pattern, which is updated as the target moves. We study how coverage is affected by these parameters, and how much such dynamic selection strategies can improve coverage over sensors selected in advance.
- H. Saito, "Theoretical optimization of sensing area shape for target detection, barrier coverage, and path coverage," IEICE Transactions, vol. 99-B, no. 9, pp. 1967--1979, 2016.Google Scholar
- J. Harada, S. Shioda, and H. Saito, "Path coverage properties of randomly deployed sensors with finite data-transmission ranges," Computer Networks, vol. 53, no. 7, pp. 1014--1026, 2009. {Online}. Available Google ScholarDigital Library
- P. Manohar, S. S. Ram, and D. Manjunath, "Path coverage by a sensor field: The nonhomogeneous case," TOSN, vol. 5, no. 2, pp. 17:1--17:26, 2009. {Online}. Available Google ScholarDigital Library
- S. S. Ram, D. Manjunath, S. K. Iyer, and D. Yogeshwaran, "On the path coverage properties of random sensor networks," IEEE Trans. Mob. Comput., vol. 6, no. 5, pp. 494--506, 2007. {Online}. Available Google ScholarDigital Library
- S. Shamoun, J. Mei, T. F. Abdelzaher, and A. Bar-Noy, "Leveraging knowledge for path exposure," in DCOSS, 2018, pp. 1--8.Google Scholar
- Z. Wang, E. Bulut, and B. K. Szymanski, "Distributed energy-efficient target tracking with binary sensor networks," TOSN, vol. 6, no. 4, pp. 32:1--32:32, 2010. {Online}. Available Google ScholarDigital Library
- N. Shrivastava, R. Mudumbai, U. Madhow, and S. Suri, "Target tracking with binary proximity sensors," TOSN, vol. 5, no. 4, pp. 30:1--30:33, 2009. {Online}. Available Google ScholarDigital Library
- S. Oh and S. Sastry, "Tracking on a graph," in Proceedings of the Fourth International Symposium on Information Processing in Sensor Networks, IPSN 2005, April 25--27, 2005, UCLA, Los Angeles, California, USA. IEEE, 2005, pp. 195--202. {Online}. Available Google ScholarDigital Library
- W. Kim, K. Mechitov, J. Choi, and S. K. Ham, "On target tracking with binary proximity sensors," in Proceedings of the Fourth International Symposium on Information Processing in Sensor Networks, IPSN 2005, April 25--27, 2005, UCLA, Los Angeles, California, USA. IEEE, 2005, pp. 301--308. {Online}. Available Google ScholarDigital Library
- E. Amaldi, A. Capone, M. Cesana, and I. Filippini, "Design of wireless sensor networks for mobile target detection," IEEE/ACM Trans. Netw., vol. 20, no. 3, pp. 784--797, 2012. {Online}. Available Google ScholarDigital Library
- S. Megerian, F. Koushanfar, G. Qu, G. Veltri, and M. Potkonjak, "Exposure in wireless sensor networks: Theory and practical solutions," Wireless Networks, vol. 8, no. 5, pp. 443--454, 2002. {Online}. Available Google ScholarDigital Library
- S. Meguerdichian, S. Slijepcevic, V. Karayan, and M. Potkonjak, "Localized algorithms in wireless ad-hoc networks: location discovery and sensor exposure," in Proceedings of the 2nd ACM Interational Symposium on Mobile Ad Hoc Networking and Computing, MobiHoc 2001, October 4--5, 2001, Long Beach, CA, USA. ACM, 2001, pp. 106--116. {Online}. Available Google ScholarDigital Library
- T. Clouqueur, V. Phipatanasuphorn, P. Ramanathan, and K. K. Saluja, "Sensor deployment strategy for detection of targets traversing a region," MONET, vol. 8, no. 4, pp. 453--461, 2003. {Online}. Available Google ScholarDigital Library
- C. C. Aggarwal, A. Bar-Noy, and S. Shamoun, "On sensor selection in linked information networks," Computer Networks, vol. 126, pp. 100--113, 2017. {Online}. Available Google ScholarDigital Library
- S. Joshi and S. Boyd, "Sensor selection via convex optimization," IEEE Trans. Signal Processing, vol. 57, no. 2, pp. 451--462, 2009. {Online}. Available Google ScholarDigital Library
- A. Krause, A. P. Singh, and C. Guestrin, "Near-optimal sensor placements in gaussian processes: Theory, efficient algorithms and empirical studies," Journal of Machine Learning Research, vol. 9, pp. 235--284, 2008. {Online}. Available Google ScholarDigital Library
- T. Chin, P. Ramanathan, and K. K. Saluja, "Optimal sensor distribution for maximum exposure in A region with obstacles," in Proceedings of the Global Telecommunications Conference, 2006. GLOBECOM '06, San Francisco, CA, USA, 27 November - 1 December 2006. IEEE, 2006. {Online}. AvailableGoogle Scholar
- Y. Yang, I.-H. Hou, J. C. Hou, M. Shankar, and N. S. V. Rao, "Sensor placement for detecting propagative sources in populated environments," in INFOCOM. IEEE, 2009, pp. 1206--1214.Google Scholar
- Proceedings of the Fourth International Symposium on Information Processing in Sensor Networks, IPSN 2005, April 25--27, 2005, UCLA, Los Angeles, California, USA. IEEE, 2005. {Online}. Available: http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=9840Google Scholar
Index Terms
- Dynamic sensor selection for path coverage
Recommendations
Maximum Gaps in Path Coverage
MSWIM '19: Proceedings of the 22nd International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile SystemsWe study the maximum size of coverage gaps by sensors selected to cover a path. Gap sizes, and not just total coverage, are important because significant events can be missed during uncovered periods. The amount of knowledge about a path affects the ...
PCRLB-based sensor selection for maneuvering target tracking in range-based sensor networks
Recent years have witnessed the shift of wireless sensor networks (WSNs) from theoretical research to practical applications. Due to their simplicity, range-based sensor networks have been widely used. To track a maneuvering target in range-based sensor ...
A Relaxation Approach to Dynamic Sensor Selection in Large-Scale Wireless Networks
ICDCSW '08: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems WorkshopsWireless sensor networks (WSNs) require more complex sensor selection strategies than other distributed networks to perform optimal state estimation. In addition to constraints associated with distributed state estimation, wireless sensor networks have ...
Comments