Prioritized multiobjective optimization in WSN redeployment using waterfall selection

• Main Authors: Rungrote Kuawattanaphan, Paskorn Champrasert
• Format: Book Series
• Published: 2018
• Subjects: Agricultural and Biological Sciences
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84931281729&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/44582
• Institution: Chiang Mai University

© Springer International Publishing Switzerland 2015. This paper proposes and evaluates a novel evolutionary selection called waterfall selection in a multi-objective optimization evolutionary algorithm for a priority-based wireless sensor nodes redeployment problem. Since, there are a variety of sensor node types in a target area. Each sensor node may have different objectives (E.g., network lifetime, data transmission, and success rate). Practically, the objectives of sensor nodes are prioritized after the deployment process. This paper focuses on the redeployment process of wireless sensor nodes to achieve their prioritized objectives simultaneously. Simulation results show that the proposed novel waterfall selection in multi-objective optimization evolutionary algorithm seeks to the solutions that conform to the prioritized objectives in timely manner and outperforms a NSGA-II evolutionary algorithm for multi-objective optimization.