Ant Colony Optimization-Based Energy Efficient Clustering and Routing in Wireless Sensor Networks

Abstract

One of the major challenges in wireless sensor networks (WSNs) is extending the network's operational lifetime, given the limited battery power of sensor nodes. These nodes perform essential tasks such as sensing, processing, routing, and transmitting data to the base station, all of which consume significant energy. This Research reviews current energy-optimized routing protocols and evaluates their performance against a newly proposed method. We examine several well-known protocols—LEACH, DEEC, DDEEC, EDEEC, and EDDEEC—which employ their own algorithms for energy efficiency, often using probability-based cluster head (CH) selection. However, this probabilistic approach can result in energy imbalance, where nodes with low energy may be chosen as CHs while high-energy nodes are overlooked, ultimately affecting network longevity. Furthermore, these protocols often do not account for the real-time energy levels of nodes during CH selection. To address these limitations, this study introduces an Ant Colony Optimization (ACO)-based routing protocol inspired by the natural behavior of ants. This method incorporates energy level awareness during CH selection and employs a dual-cluster-head approach within each cluster to enhance network performance. Simulation results demonstrate that the proposed algorithm significantly improves network lifetime and throughput.