A metaheuristic optimization approach for energy efficiency in the IoT networks. (11th February 2020)

• Record Type: Journal Article
• Authors: Iwendi, Celestine; Maddikunta, Praveen Kumar Reddy; Gadekallu, Thippa Reddy; Lakshmanna, Kuruva; Bashir, Ali Kashif; Piran, Md. Jalil
• Other Names: Kumar Neeraj guestEditor.; Jindal Anish guestEditor.; Villari Massimo guestEditor.; Srirama Satish Narayana guestEditor.
• Is Part Of: Software, practice & experience. Volume 51:Number 12(2021)
• Page Start: 2558
• Page End: 2571
• Publication Date: 2020-02-11
• Subjects: cluster head -- hybrid algorithms -- Internet of things -- metaheuristic algorithms -- simulated annealing -- whale optimization -- wireless sensor networks; Computer software -- Periodicals; Computer programming -- Periodicals; Computer programs -- Periodicals; 005.3
• DOI: 10.1002/spe.2797
• Languages: English
• ISSNs: 0038-0644

Abstract

Summary: Recently Internet of Things (IoT) is being used in several fields like smart city, agriculture, weather forecasting, smart grids, waste management, etc. Even though IoT has huge potential in several applications, there are some areas for improvement. In the current work, we have concentrated on minimizing the energy consumption of sensors in the IoT network that will lead to an increase in the network lifetime. In this work, to optimize the energy consumption, most appropriate Cluster Head (CH) is chosen in the IoT network. The proposed work makes use of a hybrid metaheuristic algorithm, namely, Whale Optimization Algorithm (WOA) with Simulated Annealing (SA). To select the optimal CH in the clusters of IoT network, several performance metrics such as the number of alive nodes, load, temperature, residual energy, cost function have been used. The proposed approach is then compared with several state‐of‐the‐art optimization algorithms like Artificial Bee Colony algorithm, Genetic Algorithm, Adaptive Gravitational Search algorithm, WOA. The results prove the superiority of the proposed hybrid approach over existing approaches.