Power Estimation for Wireless Sensor Networks based on Modular Quantitative Analysis

Wireless sensor networks (WSNs) are increasingly used in many aspects of our daily life. However, the performance is limited due to the extremely constrained power source in sensor nodes. Therefore, it is very important to find an efficient approach to predict the power consumption of WSNs in an accurate manner. Modular Quantitative Analysis (MOQA) is a new high level language used to obtain the average case timing information of randomness preserving programs. Time in this context refers to a broad notion of cost, which can be used to estimate the actual running time, but also other quantitative information such as power consumption. The aim of this paper is to build and validate a static approach to estimate the average-case power consumption of running suitable sorting algorithms on a single node, as well as in network level, based on MOQA. Experimental analysis on three sorting algorithms is provided supporting the MOQA approach. Our model predictions are validated through