A Hybrid Artificial Bee Colony and Harmony Search Algorithm-Based Metahueristic Approach for Efficient Routing in WSNs

• Published in: Wireless personal communications Vol. 121; no. 4; pp. 3263 - 3279
• Main Authors: Jayalakshmi, P., Sridevi, S., Janakiraman, Sengathir
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.12.2021; Springer Nature B.V
• Subjects: Algorithms; Clusters; Communications Engineering; Computer Communication Networks; Data management; Energy consumption; Energy utilization; Engineering; Global optimization; Heuristic methods; Networks; Search algorithms; Sensors; Signal,Image and Speech Processing; Swarm intelligence; Wireless sensor networks; Wireless sensor networks; Cluster head selection; Swarm intelligence; Artificial bee colony; Lifetime expectancy; Harmony search algorithm
• ISSN: 0929-6212; 1572-834X
• DOI: 10.1007/s11277-021-08875-5

The replacement of sensor node battery in wireless sensor network (WSN) is considered to be the highly crucial task in hostile environments. The process of partitioning the region of sensing in WSNs into clusters is determined to be the ultimate solution for attaining maximized network lifetime and gaining high energy efficiency. However, proper selection of CHs plays an anchor role in enhancing the network lifetime, since they need to utilize addition energy to handle the task of data gathering and data aggregation from the sensor member nodes of clusters and finally disseminate them to the base station.In this paper, a Hybrid Artificial Bee Colony (ABC) and Harmony Search Algorithm-based Metaheuristic Approach (HABC-HSA-MA) is proposed for attaining efficient CH selection with the view to sustain stable energy utilization with enhanced network lifetime. This HABC-HSA-MA includes the global optimization potential of Harmony Search Algorithm (HSA) and local exploitation potential of the classical ABC algorithm for achieving significant CH selection for stabilizing energy and extending network lifetime. It also incorporated the benefits of harmony adjusting factor for inducing the process of improving the dynamic search efficiency during the process of CH selection in order to prevent worst candidates from being selected as CHs. The simulation results of the proposed HABC-HSA-MA confirms an enhancement in mean network lifetime of 23.64% and balanced average energy consumption rate of 20.28% compared to the benchmarked hybrid meta-heuristic CH selection schemes.