A Data Fusion Algorithm Based on Bayes Sequential Estimation for Wireless Sensor Network
基于Bayes序贯估计的无线传感器网络数据融合算法

Mobile Agent(MA) is more suitable for wireless sensor networks than the C/S model in data fusion. In MA based data fusion, the order of nodes visited along the route by MA has a significant impact on the algorithm efficiency and life time of wireless sensor networks. This paper proposes a Mobile Agent Data Fusion (MADF) algorithm based on bayes sequential estimation for wireless sensor networks. By designing data packet and data table with specific structure, and considers MA in multihop environments and adopts gradient of Bayes sequential estimation to dispatch MA. MA accounts for performing data processing and making data aggregation decisions at nodes rather than bring data back to a central processor (sink), redundant sensory data will be eliminated. Theoretical analysis and experimental results show that the proposed scheme is able to provide less energy consumption and network delay compared to directed diffusion schemes.