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The developments in technologies such as wireless communication and microelectronics have enabled Wireless Sensor Network (WSN) applications to be deployed for many applications such as battlefield surveillance and environment monitoring. An important aspect of such networks is that the nodes are unattended, resource-constrained, their energy cannot be replenished and network topology is unknown. The resource constrained limitations make it essential for these sensor nodes to conserve energy to increase life-time of the sensor network (Akyildiz, Su, Sankarasubramaniam & Cayirici, 2002; Akyildiz & Kasimoglu, 2004; Giordano & Rosenberg, 2006; Karaki & Kamal, 2004; Yang, Mino, Barolli, Ikeda, Xhafa & Duresi, 2011; Wang, Huang & Lin, 2012).
Recently, there are lot of research efforts towards the optimization of standard communication paradigms for such networks. In fact, the traditional Wireless Network (WN) design has never paid attention to constraints such as the limited or scarce energy of nodes and their computational power. Also, in WSN paths can change over time, because of time-varying characteristics of links, local contention level and nodes reliability. These problems are important especially in a multi-hop scenario, where nodes accomplish also at the routing of other nodes’ packets (Al-Karaki & Kamal, 2004)
There are many fundamental problems that sensor networks research will have to address in order to ensure a reasonable degree of cost and system quality. Some of these problems include sensor node clustering, Cluster Head (CH) selection and energy dissipation. There are many research works that deal with these challenges (Chatterjee, Das & Turgut, 2002; Banerjee & Khuller, 2001; Chen, How & Sha, 2004; Basagni, 1999; Amis, Prakash, Vuong & Huynh, 2000; Chan & Perrig, 2004; Heinzelman, Chandrakasan & Balakrishnan, 2004; Heinzelaman, Chandrakasan & Balakrishnan, 2000; Lindsey, Raghvendra & Sivalingam, 2002).
The cluster based algorithms could be used for partition- ing the sensor nodes into subgroups for task subdivision or energy management. Cluster formation is one of most important problems in sensor network applications and can drastically affect the network’s communication energy dis- sipation. Clustering is performed by assigning each sensor node to a specific CH. All communication to (from) each sensor node is carried out through its corresponding CH node. Obviously one would like to have each sensor to communicate with the closest CH node to conserve its energy, however CH nodes can usually handle a specific number of communication channels. Therefore, there is a maximum number of sensors that each CH node can handle. This does not allow each sensor to communicate to its closest CH node, because the CH node might have already reached its service capacity. CHs can fuse data from sensors to minimize the amount of data to be sent to the sink. When network size increases, clusters can also be organized hierarchically.