ABSTRACT
Recently, wireless sensor networks are very demanding in industrial automation due to advancements in microelectronical systems (MEMS) and embedded system technologies. These networks are efficiently used in environmental monitoring, process automation, and condition monitoring. However, wireless sensor network applications require a constant power supply, which is available in only a few industries. Therefore, sensor nodes are generally battery operated and required energy preservation for longer stability. Clustered architecture is one of the most well-accepted solutions for increasing the lifetime of the wireless networks. However, the selection of optimal cluster centers is a problem of combinatorial optimization and it is very difficult to solve. Therefore, in this chapter, a new clustering method is introduced in which a multi-objective genetic algorithm has been used to find the optimal set of cluster heads. The optimal solution is decided based on two objectives, namely compactness and separation. The new method has been compared with another clustering method, namely the evolutionary routing protocol. Based on the results and discussion, it is established that the new clustering method outperforms in terms of network lifetime and stability period.
