Accurate prediction of power consumption in sensor networks

Abstract

Energy consumption is a crucial characteristic of sensor networks and their applications as sensor nodes are commonly battery-driven. Although recent research focuses strongly on energy-aware applications and operating systems, energy consumption is still a limiting factor. Once sensor nodes are deployed, it is challenging and sometimes even impossible to change batteries. As a result, erroneous lifetime prediction causes high costs and may render a sensor network, useless before its purpose is fulfilled. In this paper, we present AEON (accurate prediction of power consumption), a novel evaluation tool to quantitatively predict energy consumption of sensor nodes and whole sensor networks. Our energy model, based on measurements of node current draw and the execution of real code, enables accurate prediction of the actual energy consumption of sensor nodes. Consequently, it prevents erroneous assumptions on node and network lifetime. Moreover, our detailed energy model allows us to compare different low power and energy aware approaches in terms of energy efficiency. Thus, it enables a highly precise estimation of the overall lifetime of a sensor network.