Energy-hole avoidance and lifetime enhancement of a WSN through load factor

In wireless sensor networks, nonuniform communication load across a network often leads to the problem of energy holes or hot spots, i.e. nodes nearer high activity regions deplete their energy much faster than nodes elsewhere. This may partition the network into unreachable segments and thus adversely affect network lifetime. The problem is more acute in random and sparsely deployed networks. Therefore, we propose a deployment strategy that, using the least possible nodes, prolongs network lifetime by avoiding energy holes and also ensures full sensing and communication coverage. The scheme handles the energy imbalance by selecting an appropriate set of communication and sensing ranges for each node based on effective load on that node. After adjusting these ranges, nodes are strategically placed at locations where their energy drains uniformly and thus network lifetime is prolonged. The approach is veri ed analytically and validated through ns-2 based simulation experiments. The results reveal signi cant improvements over existing schemes.

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[1] Hahn R, Reichl H. Batteries and power supplies for wearable and ubiquitous computing. In: IEEE 1999 Third International Symposium on Wearable Computers, Digest of Papers; 18-19 Oct. 1999; San Francisco, CA, USA: IEEE. pp. 168-169.
[2] Stemm M, Katz RH. Measuring and reducing energy consumption of network interfaces in hand-held devices. IEICE T Commun 1997; 8: 1125-31.
[3] Kasten O. Energy consumption. Eth-Zurich, Swiss Federal Institute of Technology; 2001.
[4] Chen BJ, Jamieson K, Balakrishnan H, Morris R. Span: an energy-efficient coordination algorithm for topology maintenance in ad hoc wireless networks. Wireless Networks 2002; 8: 481-494.
[5] Raghunathan V, Ganeriwal S, Srivastava M. Emerging techniques for long lived wireless sensor networks. IEEE Commun Mag 2006; 44: 108-114.
[6] Siciliano B, Khatib O. Sonar Sensing. Handbook of Robotics. Berlin, Germany: Springer, 2008.
[7] Gregory OJ, You T. Ceramic temperature sensors for harsh environments. IEEE Sens J 2005; 5: 833-838.
[8] Melodia T, Kulhandjian H, Kuo LC, Demirors E. Advances in Underwater Acoustic Networking, in Mobile Ad Hoc Networking: Cutting Edge Directions. 2nd ed. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013.
[9] Perkins CE, Royer E. Ad hoc on-demand distance vector routing. In: IEEE 1999 Second Workshop on Mobile Computing Systems and Applications; 25-26 Feb. 1999; New Orleans, LA, USA: IEEE. pp. 90-100.
[10] Howard A, Mataric, MJ, Sukhatme, GS. An incremental self-deployment algorithm for mobile sensor networks. Auton Robots 2002; 13: 113-126.
[11] Wang Q, Hempstead M, Yang, W. A realistic power consumption model for wireless sensor network devices. In: IEEE 2006 3rd Annual IEEE Communication Society on Sensor and Ad Hoc Communications and Networks; 28-28 Sept. 2006; Reston, VA, USA: IEEE. pp. 286-295.
[12] Zhou Z, Das SR, Gupta, H. Variable radii connected sensor cover in sensor networks. ACM Trans Sens Netw 2009; 5: 8.
[13] Intanagonwiwat C, Govindan R, Estrin D, Heidemann J, Silva F. Directed diffusion for wireless sensor network- ing. IEEE/ACM T Networking 2003; 11: 2-16.
[14] Hedetniemi SM, Hedetniemi ST, Liestman AL. A survey of gossiping and broadcasting in communication net- works. Networks 1988; 18: 319-349.
[15] Bouabdallah F, Bouabdallah N, Boutaba R. Load-balanced routing scheme for energy efficient wireless sensor networks. In: IEEE 2008 Global Telecommunications Conference; 30 Nov.-4 Dec. 2008; New Orleans, LA, USA: IEEE. pp. 1-6.
[16] Halder S, Ghosal A, Bit SD. A pre-determined node deployment strategy to prolong network lifetime in wireless sensor network. Comput Commun 2011; 34: 1294-1306.