Multi-Objective Wireless Sensor Network Deployment Problem with Cooperative Distance-Based Sensing Coverage

• Published in: Mobile networks and applications Vol. 27; no. 1; pp. 3 - 14
• Main Authors: Wang, Sheng-Chuan, Hsiao, Han C. W., Lin, Chun-Cheng, Chin, Hui-Hsin
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.02.2022; Springer Nature B.V
• Subjects: Communications Engineering; Computer Communication Networks; Electrical Engineering; Engineering; IT in Business; Multiple objective analysis; Networks; Nodes; Optimization models; Sensors; Wireless networks; Wireless sensor networks; Wireless sensor network; Multi-objective optimization model; Non-dominated solution; Cooperative sensing coverage; Distance-based sensing coverage
• ISSN: 1383-469X; 1572-8153
• DOI: 10.1007/s11036-020-01704-2

This paper investigates the multi-objective problem of deploying wireless sensor networks with cooperative distance-based sensing coverage. This problem considers deploying a number of sensor nodes to cove multiple target points on a deployment area. Based on the locations of target points and the sensor nodes with their own inner and outer coverage radii, the distance-based sensing coverages of target nodes by sensor nodes are divided into three categories: full coverage (i.e., within the inner coverage radius), no coverage (i.e., outside the outer coverage radius), and partial coverage (i.e., between the inner and outer radii). Furthermore, this paper additionally considers the cooperative sensing coverage in which the sensing coverage of a target point is provided by more than one sensor node. The decision of sensor deployment in this paper is to select sensor nodes from potential sensor node positions so as to simultaneously maximize the collective sensing coverage of all target points and minimize the total distances between each target point and the selected sensor node(s). This paper first formulates this problem as a multi-objective optimization model, and then develops a solution procedure to determine the best non-dominated solution set for the problem model. Numerical experiments for the concerned problem by the proposed solution approach are demonstrated.