An Ant Colony Optimization Based Approach for Minimum Cost Coverage on 3-D Grid in Wireless Sensor Networks

• Published in: IEEE communications letters Vol. 22; no. 6; pp. 1140 - 1143
• Main Authors: Qasim, Tehreem, Zia, Muhammad, Minhas, Qurratul-Ain, Bhatti, Naeem, Saleem, Khalid, Qasim, Tooba, Mahmood, Hasan
• Format: Journal Article
• Language: English
• Published: IEEE 01.06.2018
• Subjects: Ant colony optimization; ant colony optimization (ACO); Buildings; coverage cost reduction; node deployment; Particle swarm optimization; redundant sensors removal; Sensors; Simulation; Wireless sensor networks; Wireless sensor networks (WSNs)
• ISSN: 1089-7798
• DOI: 10.1109/LCOMM.2018.2819643

The application of swarm intelligence algorithms to wireless sensor networks (WSNs) deployment has been the focus of research community for past few years. One such algorithm is ant colony optimization (ACO), whose application in reducing the cost of WSNs in terms of deployed sensor nodes has recently attracted attention of the researchers. In this letter, we propose an ACO-based framework for WSN deployment in a realistic 3-D environment, by making modifications to the standard ACO algorithm. The simulation results lead to the conclusion that the proposed framework achieves better performance compared with the state-of-the-art ACO-based algorithms in terms of size of the solution for node deployment. In addition, in a 3-D environment, time overhead problem arises in standard ACO-based algorithms since they require a large number of iterations to achieve better solutions. In contrast, the performance of the proposed approach does not degrade with reduction in number of iterations, which enables the algorithm to achieve quick convergence.