NATURE-INSPIRED OPTIMIZED ARTIFICIAL BEE COLONY FOR DECISION MAKING IN ENERGY-EFFICIENT WIRELESS SENSOR NETWORKS

Abstract

In recent times, there has been a surge in the popularity of nature-inspired algorithms (NIAs) for addressing challenging and complex nonlinear difficult problems. Wireless sensor networks (WSNs) provide a wide range of concerns and challenges that must be addressed when formulating methodologies and algorithms aimed at conserving energy and enhancing the overall lifespan of the network. This chapter examines and analyzes optimization-based energy-efficient strategies for clustering and routing using optimization algorithms. The major challenges in WSNs are to provide low energy consumption, enhancing network lifetime, minimizing interference in communication, improving data rate, balancing network load and quality network functioning, etc. The chapter improves the quality of service of the network by lengthening network lifetime for more packet transmission. The proposed optimized artificial bee colony (OABC) outperformed in comparison to the existing algorithms in terms of less packet loss, higher network lifetime, minimum energy consumption, and lesser average execution time.