1 A Technique for Cluster Head Selection in Wireless Sensor Networks Using African Vultures Optimization Algorithm V. Kusla 1,* , G. S. Brar 2 1 Department of Computer Science and Application, CT University, Ludhiana, Punjab, India 2 Department of Computer Science and Engineering, CT University, Ludhiana, Punjab, India Abstract INTRODUCTION: Wireless Sensor Network (WSN) has caught the interest of researchers due to the rising popularity of Internet of things(IOT) based smart products and services. In challenging environmental conditions, WSN employs a large number of nodes with limited battery power to sense and transmit data to the base station(BS). Direct data transmission to the BS uses a lot of energy in these circumstances. Selecting the CH in a clustered WSN is considered to be an NP-hard problem. OBJECTIVES: The objective of this work to provide an effective cluster head selection method that minimize the overall network energy consumption, improved throughput with the main goal of enhanced network lifetime. METHODS: In this work, a meta heuristic based cluster head selection technique is proposed that has shown an edge over the other state of the art techniques. Cluster compactness, intra-cluster distance, and residual energy are taken into account while choosing CH using multi-objective function. Once the CHs have been identified, data transfer from the CHs to the base station begins. The residual energy of the nodes is finally updated during the data transmission begins. RESULTS: An analysis of the results has been performed based on average energy consumption, total energy consumption, network lifetime and throughput using two different WSN scenarios. Also, a comparison of the performance has been made other techniques namely Artificial Bee Colony (ABC), Ant Colony Optimization (ACO), Atom Search Optimization (ASO), Gorilla Troop Optimization (GTO), Harmony Search (HS), Wild Horse Optimization (WHO), Particle Swarm Optimization (PSO), Firefly Algorithm (FA) and Biogeography Based Optimization (BBO). The findings show that AVOA's first node dies at round 1391 in Scenario-1 and round 1342 in Scenario-2 which is due to lower energy consumption by the sensor nodes thus increasing lifespan of the WSN network. CONCLUSION: As per the findings, the proposed technique outperforms ABC, ACO, ASO, GTO, HS, WHO, PSO, FA, and BBO in terms of performance evaluation parameters and boosting the reliability of networks over the other state of art techniques. Keywords: Wireless Sensor Network (WSN), Cluster Head Selection, Network Lifetime. Received on 09 September 2022, accepted on 22 December 2022, published on 11 January 2023 Copyright © 2023 V.Kusla et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsis.v10i3.2680 * Corresponding author. Email: vipankusla@gmail.com 1. Introduction WSNs are self-configured and infrastructure-free wireless networks that monitor physical or environmental conditions such as temperature, sound, vibration, pressure, motion, or pollution and collectively transfer their data via the network to a central point or sink where the data may be examined and analyzed [1]. A variety of physical and environmental characteristics can be monitored using these sensors [2]. Sensor node has several obstacles in terms of hardware, communication method, battery life and computational cost. The battery powers processors, transmitters, and receivers in sensor nodes, but its limited life can collapse the network [3]. One of the primary limitations of the WSN is energy utilization of sensor nodes, which limits its computation, EAI Endorsed Transactions on Scalable Information Systems Research Article EAI Endorsed Transactions on Scalable Information Systems Online First