4.3 Article

Improving the performance of hierarchical wireless sensor networks using the metaheuristic algorithms: efficient cluster head selection

期刊

SENSOR REVIEW
卷 41, 期 4, 页码 368-381

出版社

EMERALD GROUP PUBLISHING LTD
DOI: 10.1108/SR-03-2021-0094

关键词

Clustering; Metaheuristic; WSN; DIoT; Energy-efficiency

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This paper introduces three new methods based on metaheuristic algorithms for optimal cluster head selection, aiming to extend the network lifetime, conserve energy, enhance overhead, and improve packet delivery ratio.
Purpose Efficient resource utilization in wireless sensor networks is an important issue. Clustering structure has an important effect on the efficient use of energy, which is one of the most critical resources. However, it is extremely vital to choose efficient and suitable cluster head (CH) elements in these structures to harness their benefits. Selecting appropriate CHs and finding optimal coefficients for each parameter of a relevant fitness function in CHs election is a non-deterministic polynomial-time (NP-hard) problem that requires additional processing. Therefore, the purpose of this paper is to propose efficient solutions to achieve the main goal by addressing the related issues. Design/methodology/approach This paper draws inspiration from three metaheuristic-based algorithms; gray wolf optimizer (GWO), incremental GWO and expanded GWO. These methods perform various complex processes very efficiently and much faster. They consist of cluster setup and data transmission phases. The first phase focuses on clusters formation and CHs election, and the second phase tries to find routes for data transmission. The CH selection is obtained using a new fitness function. This function focuses on four parameters, i.e. energy of each node, energy of its neighbors, number of neighbors and its distance from the base station. Findings The results obtained from the proposed methods have been compared with HEEL, EESTDC, iABC and NR-LEACH algorithms and are found to be successful using various analysis parameters. Particularly, I-HEELEx-GWO method has provided the best results. Originality/value This paper proposes three new methods to elect optimal CH that prolong the networks lifetime, save energy, improve overhead along with packet delivery ratio.

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