Energy efficient data aggregation of moving object in Wireless Sensor Networks

Abstract

In Wireless Sensor Networks (WSNs), sensor nodes power consumption is main challenge. Emerging in-network aggregation techniques are increasingly being sought to overcome this constraint and to save precious energy. In our previously proposed method, entitled “Data Aggregation for Mobile Object Using Rate-Distortion” (DAMORD), we introduced a mathematical model for data aggregation for the moving object and exploited spatial correlation in sensed data. However, due to the complex computation arising from movement of the object, a more practical version of the original algorithm, DAMORD-SC, is presented here which significantly reduces the computation overhead using Static Clustering (SC) mechanism. In this innovative approach, predefined clusters are split into grids and pre-calculated correlation matrices are used to perform data aggregation. With the new mechanism to assess the accuracy of the method, proper grid size for clusters is obtained under different conditions with consideration to energy consumption and data accuracy. Detailed energy consumption measurements are made using the precise energy model for communication operation as well as sim-Panalyser for computation energy. Simulation results in NS-2 demonstrate that this enhanced scheme achieves substantial energy saving under a high correlation setup within the user-defined distortion rate.