A hybrid elephant herding optimization and cultural algorithm for energy‐balanced cluster head selection scheme to extend the lifetime in WSNs

• Published in: International journal of communication systems 2020-10, Vol.33 (15), p.n/a
• Main Authors: Murugadass, Gopal, Sivakumar, Poruran
• Format: Article
• Language: English
• Subjects: Algorithms; clan updating operator; Clustering; Computer simulation; cultural algorithm; elephant herding optimization; Nodes; optimal cluster head selection; Optimization; Residual energy; separating operator; Wireless networks; Wireless sensor networks
• ISSN: 1074-5351; 1099-1131
• DOI: 10.1002/dac.4538

Summary Clustering‐based optimal cluster head selection in wireless sensor networks (WSNs) is considered as the efficient technique essential for improving the network lifetime. But enforcing optimal cluster head selection based on energy stabilization, reduced delay, and minimized distance between sensor nodes always remain a crucial challenge for prolonging the network lifetime in WSNs. In this paper, a hybrid elephant herding optimization and cultural algorithm for optimal cluster head selection (HEHO‐CA‐OCHS) scheme is proposed to extend the lifetime. This proposed HEHO‐CA‐OCHS scheme utilizes the merits of belief space framed by the cultural algorithm for defining a separating operator that is potent in constructing new local optimal solutions in the search space. Further, the inclusion of belief space aids in maintaining the balance between an optimal exploitation and exploration process with enhanced search capabilities under optimal cluster head selection. This proposed HEHO‐CA‐OCHS scheme improves the characteristic properties of the algorithm by incorporating separating and clan updating operators for effective selection of cluster head with the view to increase the lifetime of the network. The simulation results of the proposed HEHO‐CA‐OCHS scheme were estimated to be superior in percentage of alive nodes by 11.21%, percentage of dead nodes by 13.84%, residual energy by 16.38%, throughput by 13.94%, and network lifetime by 19.42% compared to the benchmarked cluster head selection schemes. The key contributions of the proposed HEHO‐CA‐OCHS scheme are listed as follows: (a) In the hybrid HEHO‐CA, the merits of CA are used for permitting the search agents of HEHO to move from one region to another by updating its position and rate of transition at the end of each round. (b) This proposed hybrid HEHO‐CA incorporates the high searching efficiency of CA integrated with dynamic updating and separating nature of HEHO for efficient cluster head selection for prolonging lifetime.