ABSTRACT
In wireless sensor networks (WSNs), a many-to-one traffic pattern is adopted in a way that large numbers of sensor nodes transmit data packets to the sink. Thereby nodes located near the sink suffer from early demise due to their relaying the data traffic from the far-located nodes, and such problem is termed as a hot-spot problem. The sensing technology has brought all advancements in human lives. In this chapter, we have presented a comparative evaluation to minimize the overall energy consumption of the sensor network, by separating sensor nodes into various clusters and selecting one node from every cluster as a cluster head (CH), which is responsible for receiving and aggregating information from member nodes and then transmitting data to the sink. We give an empirical analysis of the existing methods that will help readers to select the appropriate approach for their applications. The modified artificial fish swarm algorithm (MAFS) is used to group nodes optimally along with the weighted k-means clustering algorithm. There has been a great magnitude of efforts reported for acquiring the energy efficiency in WSN; these efforts vary from conventional approaches to the metaheuristic approach for enhancing network performance. The modified artificial fish swarm optimization approach benefits by obtaining energy efficiency in the WSN.
