Nature Inspired Algorithms for Energy Efficient Clustering in Wireless Sensor Networks

Recently, Wireless Sensor Networks (WSNs) have come up as an efficient communication technology with the rapid increase in their wide variety of applications. Sensors are deployed in harsh and unattended regions to predict various environmental hazards, so that required safety measures must be taken before their occurrence. These sensors nodes are resource constrained and have very restricted energy available with them. As the time passes the energy of the sensor nodes keeps on draining that result into node failure and consequently the system failure. So, the primary concern in WSNs is their energy efficient performance. Clustering a wireless sensor network emerges as an efficient topology control approach to deal with both these issues. Clustering divides the network into small non overlapping sets called clusters. Within every cluster formed, a special node is picked as a head node to relay the useful information assembled by the remaining nodes to the sink. Consequently, it helps in minimizing the energy dissipation by the rest of the nodes. This paper focuses on how different metaheuristic approaches and their hybrids are playing very important role for the designing energy aware clustering algorithms. Also, an energy efficient clustering approach has been proposed in this paper.