Adaptive Approach for Reducing Energy Consumption, Considering Nodes' Mission in Wireless Sensor Networks

The computational cost in a wireless sensor network is usually considered neglected in comparison to the communication cost. While this assumption is considered true, it may fail if data volumes are significantly large. In such situations, it is more rational to consider the computational cost as well as the communication cost for energy related decisions in the network. In this paper, we want to reduce the energy consumed within a wireless sensor network, considering each node in charge of a mission. Every node, obtaining a trade-off between computation and communication energy, does its best to reduce the overall energy. In other words, each node endeavors to reduce network energy consumption adaptively, regarding application type, by means of making a trade-off between data compression at an appropriate level, considering spatial correlation, and sending row data. Simulation results, compared to similar work, show that our approach reduces energy consumption of nodes in the network.