SAG: Smart Aggregation Technique for Continuous-Monitoring in Wireless Sensor Networks

Diversified opportunities (possible numerous applications) and challenges (resource constrained nodes) are contributing factors behind the extensive research in sensor networks. Continuous monitoring of the natural phenomenon is one of the major streams of the possible application in this arena. Sensing and monitoring of natural phenomenon involve dealing with correlated data in both spatial and temporal dimension. Aggregation technique plays a significant role by reducing the amount of data transmission in wireless sensor networks (WSN)as correlation is dominating in the real world. This reduction on the amount of data is vital due to the energy scarcity of the WSN. This paper presents a simple aggregation technique named smart aggregation (SAG) for the continuous-monitoring applications in WSNs. SAG maintains a tolerable deviation i.e. limited error in the aggregated data while compressing both spatially and temporarily. We present simulated results that rationalize the development of the protocol. The comparison is made with k-hop aggregation and CM-EDR algorithm in terms of energy efficiency showing the potential improvement gained by applying our aggregation scheme.