大规模卫星集群网络自适应加权分簇算法

Adaptive Weighted Clustering Algorithm for Large-Scale Satellite Cluster Network

  • 摘要: 针对平面管理结构在大规模卫星集群网络中的缺点,提出了一种自适应分布式加权分簇算法(adaptive distributed weighted clustering algorithm,ADWCA),该算法根据卫星网络运行的可预测性,在初始化阶段由地面计算各卫星节点综合权值并划分簇首和成员节点,完成之后上注到星上,之后集群中卫星节点根据邻居及自身信息完全分布式地执行维护进程.仿真分析表明,与最小标识优先分簇算法和最大连接度优先分簇算法相比,该算法生成的簇结构具有更少的簇数量、良好的稳定性,且能够有效均衡簇头节点的负载.

     

    Abstract: To overcome the shortcomings of the plane management structure in the large-scale satellites cluster network, an adaptive distributed weighted clustering algorithm (ADWCA) was proposed. It was arranged to calculate the comprehensive weight of each satellite node in the initialization phase on the ground and to divide the nodes into cluster head and member node according to the predictability of the satellites network operation. And then, labeled cluster head and member node, the satellites were maintained in a completely distributed manner based on their neighbors and their own information. Simulation analysis results show that, compared with the lowest-Id algorithm and the highest-connectivity degree algorithm, the cluster structure generated by this algorithm possesses fewer clusters, better stability, and can effectively balance the load of cluster head nodes.

     

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