ACO of Energy Efficient Clustering Routing Method

Abstract

A distributed type of network in which there are large numbers of sensor nodes deployed such that the surroundings of the area can be monitored and important information can be gathered is known as wireless sensor network. There are limited and irreplaceable energy resources present within the sensor nodes. The power consumption is minimized by applying the energy efficient clustering algorithm known as energy efficient structured clustering algorithm (EESCA). The approach in which the original data is combined into smaller sized data such that only important information can be forwarded to the individual sensors is known as aggregation which is used within EESCA. The algorithm called ant colony optimization is applied for the path establishment from source to destination. The MATLAB is the tool which is used to implement EESCA with ant colony optimization algorithm. The performance of the EESCA with ACO algorithm is compared with the existing EESCA algorithm. The throughput and number of alive nodes in EESCA with ACO is increased as compared to EESCA algorithm. The number of dead nodes is reduced in EESCA with ACO algorithm as compared to EESCA Algorithm.