A novel approach for trade-off between computation and communication cost in wireless sensor networks

Wireless sensor networks consist of nodes with severe energy constraints and thus, they must use energy saving algorithms in different layers. Despite the prior work, the computational cost in a wireless sensor network is usually neglected compared to the communication cost; it may not admit to in which large volumes of data packets are being transmitted, such as those cases in which This packets are video frames captured by video sensor nodes. In this paper, we consider the problem of minimizing the communication needed to send readings from a set of sensors to a single destination with obtaining a trade-off between computation and communication energy. We propose a centralized as well as a distributed algorithm. In the former, the sink node and in the latter, each node endeavors to reduce network energy consumption adaptively, making a trade-off between data compression at the appropriate level and sending row data. The data compression technique used is dependent on the application type and considers spatial correlation. Comparing the simulation results of our approach with similar work, without consideration of trade-off between computation and comparison, shows significant improvement in energy saving of the network.