Hybrid grasshopper and Harris hawk optimization algorithm‐based energy efficient routing protocol for extending network lifetime in wireless sensor networks

• Published in: International journal of communication systems Vol. 37; no. 13
• Main Authors: Kodati, Sarangam, Dhasaratham, Meghavath, Kishor, Bodla, Narayana, Garlapati
• Format: Journal Article
• Language: English
• Published: Chichester Wiley Subscription Services, Inc 10.09.2024
• Subjects: Algorithms; CH (CH) selection; clustering; Clusters; Energy consumption; Fault tolerance; grasshopper optimization algorithm (GRHOA); Grasshoppers; Harris hawk optimization algorithm (HHOA); Heuristic methods; Life span; network lifetime; Optimization; Optimization algorithms; Residual energy; Routing (telecommunications); Wireless sensor networks; wireless sensor networks (WSNs)
• ISSN: 1074-5351; 1099-1131
• DOI: 10.1002/dac.5851

Summary In wireless sensor networks (WSNs), routing based on cluster construction is highly preferred as it greatly supports reliable data communication, load balancing, and fault tolerance with extended network lifetime. In specific, metaheuristic approach‐based dynamic cluster heads (CHs) selection has the possibility of enhancing the lifespan of network and at the same time is capable in reducing the energy consumption. In this paper, hybrid grasshopper and Harris hawk optimization algorithm‐based energy efficient routing protocol (HGHHOA) is propounded for optimal CH selection. This proposed HGHHOA approach adopted a fitness function that incorporated the factors of residual energy, distance between CH and cluster members, distance between selected CHs and the sink, node centrality, and node degree into account. The fitness function values of optimality facilitate a potential CH selection with significant cost‐effective routing. It is proposed with primary objective of improving the network lifespan through optimized selection of CHs that balances the available energy in a predominant way. It is proposed with significance of handling premature convergence with minimized energy consumption and network lifetime through the possibility of establishing an ideal balance between number of alive and dead nodes. The results of this proposed HGHHOA approach with varying rounds of implementation exhibited better results in throughput and residual energy which is 23.98% and 29.21%, better than the bassline CH selection mechanisms. Hybrid grasshopper and Harris hawk optimization algorithm‐based energy efficient routing protocol (HGHHOA) is propounded for optimal cluster head (CH) selection. This proposed HGHHOA approach adopted a fitness function that incorporated the factors of residual energy, distance between CH and cluster members, distance between selected CHs and the sink, node centrality, and node degree into account. The fitness function values of optimality facilitate a potential CH selection with significant cost‐effective routing. It is proposed with primary objective of improving the network lifespan through optimized selection of CHs that balances the available energy in a predominant way. It is proposed with significance of handling premature convergence with minimized energy consumption and network lifetime through the possibility of establishing an ideal balance between number of alive and dead nodes.