A Fuzzy Fusion Algorithm Based on Clustering Model for Wireless Sensor Networks

In wireless sensor networks, the accuracy of data fusion is likely to be contaminated by the environment affects nearby the nodes. In this paper, an appropriate fusion model and algorithm is given to solve this problem. According to the clustering fusion model, a weighted fuzzy fusion algorithm based on fuzzy reasoning for cluster heads, is proposed. The advantage of this algorithm is to vary weight value of each cluster head and dynamically update the weight values of each cluster head by using membership function. The accuracy of the proposed algorithm is improved evidently compared with the traditional algorithm.