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针对车辆自组织网络中数据融合的研究,目前主要集中于大规模簇间数据融合分析,而对簇内数据融合的研究却很少涉及.为了评估簇内数据融合性能,研究了节点可信特征以及动态车辆自组网的网络结构变化特征,提出了一种基于纳什均衡的数据融合算法,用于分析簇内节点在数据融合过程中存在的竞争和合作关系,进而分析簇特征冗余度和网络结构变化程度的均衡关系.通过对算法进行扰动,可以得到效益最优传输策略.实验结果证明,最优效益解在数据融合精确度和网络结构稳定性方面具有优势.
At present, the research on data fusion in vehicle self-organizing networks is mainly focused on large-scale inter-cluster data fusion analysis, and few studies on data fusion in clusters are involved.In order to evaluate the intra-cluster data fusion performance, As well as the characteristics of the network structure of dynamic vehicle ad hoc networks, a data fusion algorithm based on Nash equilibrium is proposed to analyze the competition and cooperation between nodes in the data fusion process. Then the cluster redundancy and The equilibrium relationship between the network structure and the degree of network structure change.The optimal transmission strategy can be obtained by perturbing the algorithm.Experimental results show that the optimal efficiency solution has advantages in data fusion accuracy and network structure stability.