Energy Efficient Scheduling Strategy for Data Collection in Wireless Sensor Networks

Abstract

Wireless Sensor Networks represents a new pattern for extracting the data from the environment for many agricultural, industrial and scientific applications. Data gathering protocols are formulated for configuring the network and collecting the information from the desired environment. Sensors have limited battery power and the communication module consumes the maximum power in the sensors. A key challenging issue in case of wireless sensor networks is to decide on a fixed pattern for the purpose of data collection. For this it is very important to schedule the various activities of the sensors which would lead to the reduction in the energy consumption by the network as a whole. In this paper we have focused on two major aspects. One is the construction of data gathering tree and the other is the energy efficient scheduling. Here we have proposed a scheduling strategy which makes use of TDMA and schedules the activities of a subset of a sensors into different groups with successive time slots thereby reducing the state transition and hence the energy consumption. The proposed scheduling algorithm has been simulated in NS-2.32 and the performance has been evaluated on the various performance metrics of Wireless Sensor Networks. The simulation result shows that our proposed scheduling strategy improves the performance metrics like Delivery Ratio and Energy as compared to the traditional method of scheduling.