Optimizing Energy Consumption and Network Lifetime in Wireless Sensor Networks Using Ant Colony Optimization

Abstract

Wireless Sensor Networks (WSNs) are widely used for monitoring and data collection in various applications, but their limited energy resources often lead to reduced node lifetime, which is a critical challenge. This paper proposes an innovative approach to improve the lifetime of nodes in WSNs using Ant Colony Optimization (ACO). ACO, a nature-inspired optimization algorithm, is applied to optimize the routing paths and energy consumption in the network. The proposed method focuses on enhancing the number of node connections, minimizing the path length, and efficiently managing energy consumption. Experimental results demonstrate that the application of ACO in WSNs yields significant improvements, with energy consumption of 0.7 W over 400 iterations, leading to an increase in network lifetime and more effective utilization of available energy resources. The approach shows promise for improving the performance and sustainability of WSNs in various real-time monitoring applications.