一个新基于核心的分享的树算法, viz 核心簇基于联合的分享的树(CCST ) 算法和加权的版本(即 w-CCST 算法) 被建议以便解决隧道资源浪费问题在典型基于来源多点传送在低地球轨道(狮子座) 的路由算法卫星 IP 网络。CCST 算法包括动态近似中心(数模转换器) 核心选择方法和核心簇联合多点传送线路构造计划。没有复杂机载的计算, DAC 方法特别地为期刊和常规运动的高度有活力的网络被开发。核心簇联合方法作为起始的核心簇拿核心节点,并且扩展它对在最低的树的一棵全部 multicast 树由在最新产生的核心簇和剩余之间的一个最短的路径计划花费了的构造逐步组织成员,它导致大带宽利用。而且, w-CCST 算法能由调整加权的因素满足一些的严格的端对端的延期要求寻求在树费用和端对端的繁殖延期的性能之间的平衡即时多点传送在损坏树的细微增加的情况下的服务花费了。最后,性能比较在狮子座卫星 IP 网络在建议算法和典型算法之间被进行。模拟结果证明 CCST 算法显著地减少平均的树费用对到其它,并且也, w-CCST 算法的平均端对端的繁殖延期比 CCST 算法的低。
A new core-based shared tree algorithm, viz core-cluster combination-based shared tree (CCST) algorithm and the weighted version (i.e. w-CCST algorithm) are proposed in order to resolve the channel resources waste problem in typical source-based multicast routing algorithms in low earth orbit (LEO) satellite IP networks. The CCST algorithm includes the dynamic approximate center (DAC) core selection method and the core-cluster combination multicast route construction scheme. Without complicated onboard computation, the DAC method is uniquely developed for highly dynamic networks of periodical and regular movement. The core-cluster combination method takes core node as the initial core-cluster, and expands it stepwise to construct an entire multicast tree at the lowest tree cost by a shortest path scheme between the newly-generated core-cluster and surplus group members, which results in great bandwidth utilization. Moreover, the w-CCST algorithm is able to strike a balance between performance of tree cost and that of end-to-end propagation delay by adjusting the weighted factor to meet strict end-to-end delay requirements of some real-time multicast services at the expense of a slight increase in tree cost. Finally, performance comparison is conducted between the proposed algorithms and typical algorithms in LEO satellite IP networks. Simulation results show that the CCST algorithm significantly decreases the average tree cost against to the others, and also the average end-to-end propagation delay ofw-CCST algorithm is lower than that of the CCST algorithm.