A Swarm Intelligence Based Clustering Technique with Scheduling for the Amelioration of Lifetime in Sensor Networks

For regulating the physical phenomena, for example, temperature, humidity, vibrations, and seismic event set cetera; a wireless sensor network (WSN) encompasses different sensor nodes over a geological zone. A sensor node is a small device comprising of three fundamental parts: a system for sensing data, a system for processing, and a communication system that operates wirelessly. Energy effectiveness for WSN is considered as an important issue since sensor nodes have constrained batteries. In recent work several numbers of distributed scheduling algorithms are introduced to solve the energy efficient problem, however it doesn’t increase network lifetime of the WSN. To solve this problem, artificial bee colony (ABC) based clustering with distributed scheduling is introduced here. The major objective of this work is to tradeoff between network lifetime and energy efficiency. In the main stage ABC based clustering is done to perceive the optimal target node in the all the cluster groups. This stage decreases the time utilization and upgrade the network lifetime. In the following phase distributed scheduling is performed to recognize the best cluster group. Therefore this approach is actualized in matrix laboratory and the results proved the efficiency of the examined approach when matched up with the ordinary methodologies. The results of the proposed ABC distributed scheduling clustering algorithm is measured in terms of energy, network lifetime, packet delivery ratio, throughput, and latency.