Fire Fly Optimization Algorithm based Clustering by Preventing Residual Nodes in Mobile Wireless Sensor Networks

This paper regarding the use of the natural phenomenon’s based optimization techniques to resolve the problem of nonclustered nodes. Objectives: This research minimizes energy consumption. Its objective is to provide efficient clustering for avoidance of residual nodes and prevents occurrence of dead nodes with usage of mobile nodes. Methods: In this research paper firstly deploy number of mobile nodes in specified region with usage of MATLAB environment. For grouping of these nodes LEACH protocol uses for clustering. During clustering with LEACH some nodes residual and not become part of any cluster. Firefly Optimization used for prevention of residual nodes and efficient clustering. It uses distance and light intensity parameters for clustering. GSA algorithm used for finding best path for data transmission with less energy consumption. Findings: In this research paper shows efficient clustering of nodes with prevention of residual nodes. In existing LEACH protocol some static nodes are residual and not become part of any cluster. These nodes send data directly to base station and consume large amount of energy. These individual nodes die early due to maximum energy consumption. But in this research mobile nodes are used and occurrence of dead nodes prevented on basis of distance and light intensity parameters. Nodes which are at minimum distance are brighter than farthest nodes. Minimum distance nodes join nearest cluster and prevent formation of remaining nodes. Improvements: In this paper results shown that it performs better in terms of network lifetime, energy consumption, end to end delay and throughput and number of dead nodes.