In-Network Data Processing Architecture for Energy Efficient Wireless Sensor Networks

In traditional WSNs, the sensor nodes are used only for capturing data, which is analyzed in a centralized base station. This requires a continuous communication but wastes the energy of sensor nodes and results in a reduction of the overall network lifetime. In this paper, we proposed an in-network data processing architecture to improve the energy efficiency and the scalability and the accuracy of sensor networks. We also adapted a data mining algorithm to process data for matching a specific event. The simulations show a reduction in energy consumption and an improvement in data accuracy.