Dynamic data aggregation for energy optimization in multi-hop Wireless Sensor Networks

This paper proposes a model where the energy usage of sensor nodes in a multi-hop Wireless Sensor Network (WSN) is optimized by using data aggregation, a technique which discards “unnecessary” packets so as to save bandwidth. It does so in two steps; first of which uses an Exponential Weighted Moving Average (EWMA) data aggregation technique to compare the current data value with all the previous values before deciding whether to forward or drop the packet. The second step optimizes the network even further by considering readings from neighboring sensors into the equation. Some flexibility has been designed in the algorithm allowing the precision level to be adjusted based on the users requirements. Simulated results show how the scheme reduces the number of packets transmitted and the normalized energy consumed by the nodes.