International Journal of Electrical and Computer Engineering (IJECE) Vol. 13, No. 4, August 2023, pp. 4127~4135 ISSN: 2088-8708, DOI: 10.11591/ijece.v13i4.pp4127-4135  4127 Journal homepage: http://ijece.iaescore.com Proposed energy efficient clustering and routing for wireless sensor network Gundeboyina Srinivasalu 1 , Hanumanthappa Umadevi 2 1 Department of Electronics and Communication Engineering, Cambridge Institute of Technology, Bengaluru, India 2 Department of Electronics and Communication Engineering, Dr. Ambedkar Institute of Technology, Bengaluru, India Article Info ABSTRACT Article history: Received May 5, 2022 Revised Dec 5, 2022 Accepted Dec 7, 2022 Wireless sensor network (WSN) is considered a growing research field that includes numerous sensor nodes used to gather, process, and broadcast information. Energy efficiency is considered one of the challenging tasks in the WSN. The clustering and routing are considered capable approaches to solve the issues of energy efficiency and enhance the network’s lifetime. In this research, the multi-objective-energy based black widow optimization algorithm (M-EBWOA) is proposed to perform the cluster-based routing over the WSN. The M-EBWOA-based optimal cluster head discovery is used to assure an energy-aware routing over the WSN. The main goal of this M-EBWOA is to minimize the energy consumed by the nodes while improving the data delivery of the WSN. The performance of the M-EBWOA is analyzed as alive and dead nodes, dissipated energy, packets sent to base station, and life expectancy. The existing research such as low- energy adaptive clustering hierarchy (LEACH), hybrid grey wolf optimizer- based sunflower optimization (HGWSFO), genetic algorithm-particle swarm optimization (GA-PSO), and energy-centric multi-objective Salp Swarm algorithm (ECMOSSA) are used to evaluate the efficiency of M-EBWOA. The alive nodes of the M-EBWOA are 100 for 2,500 rounds, which is higher than the LEACH, HGWSFO, GA-PSO, and ECMOSSA. Keywords: Energy consumption Life expectancy route generation Multi-objective-energy based black widow optimization algorithm Selection of cluster head Wireless sensor network This is an open access article under the CC BY-SA license. Corresponding Author: Gundeboyina Srinivasalu Department of Electronics and Communication Engineering Department, Cambridge Institute of Technology Krishnarajapura, Bangalore-560036, India Email: Srinivasalu.ece@cambridge.edu.in 1. INTRODUCTION The huge amount of sensor nodes is spatially distributed in the wireless sensor network (WSN) for monitoring the environmental or physical conditions. Each sensor in the WSN collects the signal from the finite region. This collected signal is processed by the sensor and the sensed data is broadcasted to the base station (BS) [1]–[5]. The WSNs accomplish three essential tasks such as sensing, processing, and communicating. The communication task utilizes high energy than the remaining tasks [6]. WSN is subjected to various types of limits when compared to wired networks such as restricted communication distance, limited network communication bandwidth, and limited power resources [7]. Since, the WSN uses battery energy, energy consumption and restriction of sensors are specified as essential issues in the network [8]–[10]. WSN provides beneficial performances in unattended environments, harsh environments, environments with restricted resources, and other special environments [11]. Examples of the common citizen and military applications are environmental monitoring, battlefield surveillance, industrial process control, agricultural, medical care, and monitoring fire [12]–[16].