Maximizing Lifetime of WSNs using Duty Cycle Regulation via Adaptive Thresholding and Energy Aware Routing

Abstract

Wireless Sensor Network (WSNs) consist of hundreds to thousands of tiny sensor nodes equipped with sensing, data processing, and communication units. These sensor nodes are used to collect information about ambient environment, e.g. temperature, humidity, light, vibration, acoustic, etc. Due to these capabilities, WSNs can be applied in various potential applications such as target tracking, habitat monitoring, healthcare monitoring, surveillance, etc. However, to make WSNs feasible to be employed, a number of requirements in the design and operation of the network need to be satisfied. Since sensor nodes are powered by limited energy source, energy conservation is commonly considered the most key challenge in order to guarantee the connectivity of the network and extend the lifetime of the sensor nodes, especially when the deployment field is inaccessible, and battery cannot be replaced. This research is focused on improving lifetime of WSN by implementing adaptive thresholding while transmitting data, Fuzzy C-means (FCM) and sleeping scheduling based on Particle swarm optimization (PSO). This method aims to provide adequate sensing coverage area by balancing the energy load of the sensing and communication tasks among all the nodes in the network and putting some of the nodes into sleep state while other active nodes collect data. Simulation has been run and the performance has been compared with Low-energy adaptive clustering hierarchy (LEACH) and Minimum transmission Energy (MTE) which shows improvement of lifetime in network.