Energy minimization by removing data redundancy in wireless sensor networks

Energy consumption is a critical problem affecting the lifetime of wireless sensor networks (WSNs). In this paper we develop STCA-spatio-temporal correlation algorithm for wireless sensor networks. The main idea behind STCA is to remove redundant data transmission which doesn't make any sense in wireless sensor networks but the wastage of energy. By exploiting the spatial and temporal correlation STCA can be effectively used in event driven as well as continuous wireless sensor networks to increase the life time of sensor node. The proposed algorithm checks the temporal correlation in each node as local processing also it checks the spatial correlation in parent node and transmit only corresponding headers. This algorithm is very simple and it consumes less energy and time for execution which make more efficient for energy constrained devices. We implemented the algorithm in real-time and the result clearly show that by using STCA can reduce the number of transmission up to 40 % and thereby power consumption for transmission. The local processing made in each node can exploit temporal correlation to remove redundant data transmission in the earlier stage itself.