Adaptive Data Fusion for Energy Efficient Routing in Wireless Sensor Network

The data fusion process has led to an evolution for emerging Wireless Sensor Networks (WSNs) and examines the impact of various factors on energy consumption. Significantly there has always been a constant effort to enhance network efficiency without decreasing the quality of information. Based on Adaptive Fusion Steiner Tree (AFST), this paper proposes a heuristic algorithm called Modified Adaptive Fusion Steiner Tree (M-AFST) for energy efficient routing which not only does adaptively adjusts the information routes but also receives the required information from data sources and uses an extra buffer for backlogging incoming packets, so that the process of data fusion could be optimized by minimizing the overall data transmission. Experimental results prove the effectiveness of the proposed algorithm and achieve better performance than few existing algorithms discussed in the paper.