Energy efficient system partitioning for distributed wireless sensor networks

A scheme for efficient system partitioning of computation in wireless sensor networks is presented. Local computation of the sensor data in wireless networks can be highly energy-efficient, because redundant communication costs can be reduced. It is important to develop energy-efficient signal processing algorithms to be run at the sensor nodes. This paper presents a technique to optimize system energy by parallelizing computation through the network and by exploiting underlying hooks for power management. By parallelizing computation, the voltage supply level and clock frequency of the nodes can be lowered, which reduces energy dissipation. A 60% energy reduction for a sensor application of source localization is demonstrated. The results are generalized for finding optimal voltage and frequency operating points that lead to minimum system energy dissipation.