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Multi-objective optimization of multicast overlays for collaborative applications

机译:用于协作应用的多播覆盖的多目标优化

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Current real-time collaborative application implementations use dedicated infrastructure to carry out all communication and synchronization activities. Specifically, they require all end nodes to communicate directly with and through the central server. In this paper, we investigate scenarios in which the most resource intensive functionality of continuous communication among collaborators to disseminate changes is decentralized, utilizing the end users themselves as relays. We observe that communication characteristics of realtime collaboration makes use of existing multicast mechanisms unsuitable. As collaborative editing sessions are typically long and repeated, it is possible to gather and leverage node behavior (their instabilities and frequency of sending updates) and communication links (latencies and average costs). Several criteria to determine the quality of a multicast tree can be identified: cost, latency and instability. In this paper, we analyze the complexity of the problem of finding optimal communication topologies, and propose approximate algorithms to optimize the same. We also consider the multiobjective problem in which we search for a topology that provides good trade-off between these sometimes conflicting measures. Validation of our proposed algorithms on numerous graphs shows that it is important to consider the multiobjective problem, as optimal solutions for one performance measure can be far from optimal for the other metrics. Finally, we briefly present an implementation of a communication library that uses the proposed algorithms to periodically adjust the dissemination tree.
机译:当前的实时协作应用程序实现使用专用的基础结构来执行所有通信和同步活动。具体来说,它们要求所有终端节点直接与中央服务器通信并通过中央服务器进行通信。在本文中,我们研究了以下场景:利用最终用户自身作为中继,分散了协作者之间持续通信以传播变更的最耗费资源的功能。我们观察到实时协作的通信特性使使用现有的多播机制不合适。由于协作编辑会话通常很长且重复,因此可以收集和利用节点行为(它们的不稳定性和发送更新的频率)和通信链接(延迟和平均成本)。可以确定确定组播树质量的几个标准:成本,等待时间和不稳定性。在本文中,我们分析了寻找最佳通信拓扑问题的复杂性,并提出了近似算法来对其进行优化。我们还考虑了多目标问题,在该问题中,我们寻找一种拓扑结构,这些拓扑结构在这些有时相互冲突的度量之间提供了良好的折衷。在众多图表上对我们提出的算法进行验证表明,考虑多目标问题非常重要,因为针对一种性能指标的最优解决方案可能远非针对其他指标的最优解决方案。最后,我们简要介绍一个通信库的实现,该通信库使用所提出的算法来定期调整传播树。

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