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In this paper, we study a new approach to model the overall EnergyConsumption (EC) in Wireless Sensor Networks (WSN). First, we extractparameters involving in the EC of WSNs. The dependency between configurationparameters and the average residual energy of a specific application is theninvestigated. Our approach has three key steps: profiling, parameter reduction,and modeling. In profiling, a sensor network simulator is re-run 800 times withdifferent values of the configuration parameters in order to profile theaverage residual energy in nodes. In the parameter reduction, three statisticalanalyses (p-value, linear and non-linear correlation) are applied to theoutcome of profiled experiments in order to separate the effective parameterson WSN residual energy. Finally, linear regression is used to model therelation between the chosen effective parameters and the residual energy. Theevaluation based on running the simulator for another 200 times with differentvalues of the effective parameters shows that the model can predict theresidual energy of nodes in WSN with average error of less than 13%.

A study on Modeling of Dependency between Configuration Parameters and Overall Energy Consumption in Wireless Sensor Network (WSN)