Improving Target Coverage in Visual Sensor Networks by Adjusting the Cameras’ Field-of-View and Scheduling the Cover sets Using Simulated Annealing
Subject Areas : electrical and computer engineering
B.
Shahrokhzadeh
1
M.
Dehghan
2
M. R.
Shahrokhzadeh
3
Keywords: Network lifetime simulated annealing target coverage visual sensor networks,
Abstract :
In recent years, target coverage is one of the important problems in visual sensor networks. An efficient use of energy is required in order to increase the network lifetime, while covering all the targets. In this paper, we address the Maximum Lifetime with Coverage Scheduling (MLCS) problem that maximizes the network lifetime. We develop a simulated annealing (SA) algorithm that divides the sensors’ Field-of-View (FoV) to a number of cover sets that can cover all the targets and then applies a sleep-wake scheduling algorithm. On the other hand, we have to identify the best possible FoV of sensors according to the targets’ location using rotating cameras, to reduce the solution space and find a near-optimal solution. It also provides the balanced distribution of energy consumption by introducing a new energy and neighbor generating function as well as escaping from local optima. Finally, we conduct some simulation experiments to evaluate the performance of our proposed method by comparing with well-known solutions in the literature such as greedy algorithms.
[1] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, "Wireless sensor networks: a survey," Computer Networks, vol. 38, no. 4, pp. 393-422, Mar. 2002.
[2] S. Soro and W. Heinzelman, "A survey of visual sensor networks," Advances in Multimedia, vol. 2009, 21 pp., 2009.
[3] H. H. Yen, "Efficient visual sensor coverage algorithm in wireless visual sensor networks," in Proc. 9th Int. Wireless Communications and Mobile Computing Conf., IWCMC'13, pp. 1516-1521, 1-5 Jul. 2013.
[4] J. Ai and A. A. Abouzeid, "Coverage by directional sensors in randomly deployed wireless sensor networks," J. of Combinatorial Optimization, vol. 11, no. 1, pp. 21-41, Feb. 2006.
[5] Y. Cai, W. Lou, M. Li, and M. Li, "Energy efficient target-oriented scheduling in directional sensor networks," IEEE Trans. on Computers, vol. 58, no. 9, pp. 1259-1274, Sep. 2009.
[6] K. Han, L. Xiang, J. Luo, and Y. Liu, "Minimum-energy connected coverage in wireless sensor networks with omni-directional and directional features," in Proc. of the 13th ACM International Symposium on Mobile Ad Hoc Networking and Computing, pp. 85-94, 11-14 Jun. 2012.
[7] Y. Hong, et al., "Target-temporal effective-sensing coverage in mission-driven camera sensor networks," in Proc. of 22nd Int. Conf. on Computer Communications and Networks, ICCCN'13, 9 pp., 30 Jul.-2 Aug. 2013.
[8] Y. H. Kim, Y. H. Han, Y. S. Jeong, and D. S. Park, "Lifetime maximization considering target coverage and connectivity in directional image/video sensor networks," The J. of Supercomputing, vol. 65, no. 1, pp. 365-382, Jul. 2013.
[9] F. Xiao, et al., "Surface coverage algorithm in directional sensor networks for three-dimensional complex terrains," Tsinghua Science and Technology, vol. 21, no. 4, pp. 397-406, Aug. 2016.
[10] S. Xu, W. Lyu, and H. Li, "Optimizing coverage of 3D wireless multimedia sensor networks by means of deploying redundant sensors," International J. of Advanced Studies in Computers, Science and Engineering, vol. 4, no. 9, p. 28, 2015.
[11] M. Cardei, M. T. Thai, Y. Li, and W. Wu, "Energy-efficient target coverage in wireless sensor networks," in Proc. IEEE Proc. 24th Annual Joint Conf. of the IEEE Computer and Communications Societies, INFOCOM'05, vol. 3, pp. 1976-1984, 13-17 Mar. 2005.
[12] J. M. Gil and Y. H. Han, "A target coverage scheduling scheme based on genetic algorithms in directional sensor networks," Sensors, vol. 11, no. 2, pp. 1888-1906, 2011.
[13] G. S. Kasbekar, Y. Bejerano, and S. Sarkar, "Lifetime and coverage guarantees through distributed coordinate-free sensor activation," IEEE/ACM Trans. on Networking, vol. 19, no. 2, pp. 470-483, Apr. 2011.
[14] M. Hosseini, M. Dehghan, and H. Pedram, "Lifetime improvement of visual sensor networks for target coverage through uniform energy consumption," International J. of Ad Hoc and Ubiquitous Computing, vol. 14, no. 4, pp. 249-266, 2013.
[15] M. C. Wu and W. F. Lu, "On target coverage problem of angle rotatable directional sensor networks," in Proc. 7th Int. Conf. on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS'13, pp. 605-610, 3-5 Jul. 2013.
[16] V. P. Munishwar, V. Kolar, and N. B. Abu-Ghazaleh, "Coverage in visual sensor networks with Pan-Tilt-Zoom cameras: the MaxFoV problem," in Proc. IEEE INFOCOM, pp. 1492-1500, 27 Apr.-2 May 2014.
[17] M. Cardei and D. Z. Du, "Improving wireless sensor network lifetime through power aware organization," Wireless Networks, vol. 11, no. 3, pp. 333-340, May 2005.
[18] L. Ding, W. Wu, J. Willson, L. Wu, Z. Lu, and W. Lee, "Constant-approximation for target coverage problem in wireless sensor networks," in Proc. IEEE INFOCOM, pp. 1584-1592, Mar. 2012.
[19] Y. Li and S. Gao, "Designing k-coverage schedules in wireless sensor networks," J. of Combinatorial Optimization, vol. 15, no. 2, pp. 127-146, Feb. 2008.
[20] A. Rossi, A. Singh, and M. Sevaux, "Lifetime maximization in wireless directional sensor network," European J. of Operational Research, vol. 231, no. 1, pp. 229-241, Nov. 2013.
[21] S. Kirkpatrick, "Optimization by simulated annealing: quantitative studies," J. of Statistical Physics, vol. 34, no. 5-6, pp. 975-986, Mar. 1984.
[22] V. Cerny, "Thermodynamical approach to the traveling salesman problem: an efficient simulation algorithm," J. of Optimization Theory and Applications, vol. 45, no. 1, pp. 41-51, Jan. 1985.
[23] N. Metropolis and S. Ulam, "The monte carlo method," J. of the American Statistical Association, vol. 44, no. 247, pp. 335-341, 1949.
[24] D. H. Ackley, G. E. Hinton, and T. J. Sejnowski, "A learning algorithm for boltzmann machines," Cognitive Science, vol. 9, no. 1, pp. 147-169, Jan. 1985.