Innovative Study to the Graph Based Data Mining Application of the Data Mining in Dotnet

This paper deals with a novel forwarding scheme for wireless sensor networks aimed at combining low computational complexity and high performance in terms of energy efficiency and reliability. The proposed approach relies on a packet-splitting algorithm based on the Chinese Remainder Theorem (CRT) and is characterized by a simple modular division between integers and a Kalman filter is used to reduce the noise in the receiving end. An analytical model for estimating the energy efficiency of the scheme is presented, and several practical issues such as the effect of unreliable channels, topology changes and MAC overhead are discussed. The Simulation is done through MATLAB which show that the proposed algorithm outperforms traditional approaches in terms of power saving, simplicity and fair distribution of energy consumption among all nodes in the network and reduces the noise in the receiver end.