An enhanced obstacle-aware deployment scheme with an opposition-based competitive swarm optimizer for mobile WSNs. (1st March 2022)

• Record Type: Journal Article
• Authors: Musikawan, Pakarat; Kongsorot, Yanika; Muneesawang, Paisarn; So-In, Chakchai
• Is Part Of: Expert systems with applications. Volume 189(2022)
• Publication Date: 2022-03-01
• Subjects: Deployment optimization -- Mobile wireless sensor networks -- Competitive swarm optimizer -- Metaheuristic algorithm -- Voronoi diagram -- Virtual force algorithm -- Node deployment -- Coverage area; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2021.116035
• Languages: English
• ISSNs: 0957-4174

Abstract

Abstract: The network coverage problem for an area with a randomly deployed wireless sensor network (WSN) in the presence of obstacles can be alleviated through mobile sensor nodes. However, the requirement for the dissipated energy in mobility and sensing has increased. Therefore, energy efficient coverage is a significant issue and has been near-optimally solved by heuristic techniques. Focusing on this issue, this paper introduces an improved competitive swarm optimizer to maximize the coverage area and minimize the network energy simultaneously. The proposed method incorporates the virtual force algorithm (VFA) and the Voronoi diagram (VD) to improve the network performance during the optimization process. The VFA is combined with a boundary mechanism to control the locations of sensors, while the VD is utilized to extract the network information for the decoding process. The superior performance of the model is verified by intensive evaluations against state-of-the-art techniques in terms of the coverage ratio and network energy consumption. Highlights: Improve coverage redundancy and obstacle avoidance for WSN deployment. Propose an opposition-based modified CSO for WSN deployment optimization. Propose a hybrid boundary scheme in combination with the VFA as position controller. Adjust the sensing radius through the proposed decoding process based on the VD. Perform an intensive evaluation over recent state of the art WSN deployment methods.