Energy Efficiency and Maximizing Network Lifetime for WSNs using ACO Algorithm
Y. Chalapathi Rao1, Santhi Rani2

1Y. Chalapathi Rao, Associate Professor, Department of ECE, Anurag Engineering College, Kodad, Nalgonda (Telangana), India.
2Dr. Ch. Santhi Rani, Professor, Department of ECE, DMSSVH College of Engineering, Machilipatnam, Krishna (Andhra Pradesh), India.
Manuscript received on 10 July 2015 | Revised Manuscript received on 20 July 2015 | Manuscript Published on 30 July 2015 | PP: 15-20 | Volume-5 Issue-2, July 2015 | Retrieval Number: B2136075215/15©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (

Abstract: Wireless Sensor Networks (WSNs) carry out both monitoring and communication task. WSN’s have attractive a great deal of study due to their low cost and wide range applications. A WSN is a distributed system consisting of many small sensor nodes delayed in environments to sense the physical world. WSNs have a large number of applications in real time monitoring, such as battle field surveillance, environment monitor, personal health monitor and so on. The main challenging problem in WSNs is power consumption and maximizing the network lifetime. WSNs is a demanding task, in this paper proposed an ACO based approaches that can be prolonging the network lifetime and minimizing the power consumption. ACO is a well known Meta heuristic inspired by the foraging behavior of real ants. Ants are stochastic constructive procedures that build solutions while walking on a constructive graph. This paper considers the problem of finding the maximum number of connected covers in different WSNs. A number of methods have been proposed for finding one connected cover from a WSN. The connected covers are a more direct way to minimize power consumption and prolong the network lifetime. The proposed approach has been applied to different WSNs. The compared result shows that the performance and efficiency of the approach with LEACH and PARA, ACO is a successful method for maximizing the network lifetime and minimize power consumption.
Keywords: Ant Colony Optimization (ACO) Algorithm, Energy Efficiency, LEACH, Network Lifetime, PARA, WSNs.

Scope of the Article: Computer Network