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大规模卫星集群网络自适应加权分簇算法

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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
投稿时间:2021-03-22
DOI:10.15918/j.tbit1001-0645.2021.072
中文关键词:大规模卫星集群分簇算法网络管理负载均衡
English Keywords:large-scale satellites clusterclustering algorithmnetwork managementload balancing
基金项目:中国科学院重点部署项目(ZDRW-KT-2016-02)
作者单位E-mail
陈宇中国科学院 国家空间科学中心, 北京 100190
张勇中国科学院 国家空间科学中心, 北京 100190
中国科学院大学 计算机科学与技术学院, 北京 101408
陈实中国科学院 国家空间科学中心, 北京 100190chenshi@nssc.ac.cn
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中文摘要:
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.
English Summary:
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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