A WSN lifetime improvement algorithm reaping benefits of data aggregation and state transitions

Abstract

Wireless sensor networks consist of different subsystems such as sensing, transmission, reception, power and processing systems. Battery power of sensor nodes is one of the important factors to consider in a wireless sensor system. Moreover, when such systems are deployed in remote environments for critical applications where the availability of electrical power is less, the factor presents a major constraint. Prior work has tackled this problem by introducing sleep, sense, transmit and receive states. Although most work employed these states in tree and cluster based networks they only incorporated at the leaf nodes. This paper introduces state transitions for cluster head nodes to further reduce energy. The algorithm basically combines data aggregation and state transition to improve the overall life time of the network. To validate the algorithm, we apply to a landslide monitoring and detection system and obtain 33% energy savings for leaf node and 30% energy saving for cluster head node when compared to naive algorithms that do not apply state transitions.