Hybridization of Metaheuristic Algorithm for Dynamic Cluster-Based Routing Protocol in Wireless Sensor Networksx

• Published in: IEEE access Vol. 9; pp. 83751 - 83761
• Main Authors: Al-Otaibi, Shaha, Al-Rasheed, Amal, Mansour, Romany F., Yang, Eunmok, Joshi, Gyanendra Prasad, Cho, Woong
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Clustering; Clustering algorithms; Energy efficiency; Experimentation; Heuristic methods; metaheuristics; Optimization; Polynomials; Radio equipment; Route selection; Routing; Routing (telecommunications); Routing protocols; Voting; Water waves; Wireless networks; Wireless sensor networks; WSN
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2021.3087602

Energy efficiency is considered the major design issue in wireless sensor networks (WSN), which can be addressed using clustering and routing techniques. They are treated as Non-deterministic Polynomial (NP)-hard optimization problems and are solved using metaheuristic algorithms to identify the optimal or near-optimal solutions. With this motivation, this paper develops a hybridization of the metaheuristic cluster-based routing (HMBCR) technique for WSN. The HMBCR technique initially involves a brainstorm optimization with levy distribution (BSO-LD) based clustering process using a fitness function incorporating four parameters such as energy, distance to neighbors, distance to the base station, and network load. Besides, a water wave optimization with a hill-climbing (WWO-HC) based routing process is carried out for optimal route selection. Extensive experimentation analysis is performed to ensure the energy efficiency and network lifetime performance of the HMBCR technique. The experimental outcome ensured the superior results of the HMBCR technique over the compared methods under different aspects.