Data aggregation using spatial and temporal data correlation

In wireless sensor networks (WSNs), the major challenge for sensor nodes is to send sensed data to sink in an energy efficient way due to limited energy of sensor nodes. Data Aggregation protocols are applied to maximize lifetime of sensor nodes and hence of wireless sensor networks. The approach of normal routing protocols relies only on sending data to sink from sensors without considering energy available with nodes. This means that lot of redundant transmissions occur in WSNs. The main contribution of this paper is to introduce a novel Spatial and Temporal Data Correlation algorithm for Data Aggregation (DASTDC). Our algorithm uses the features of spatial relationship in data along with the time based prediction of data to minimize the loss of energy by less number of transmissions. This algorithm improves the lifetime of Wireless Sensor Networks and almost eliminates the redundancy due to forwarding of essential data to nodes.