SCTP多宿主的路径选择技术

Kai Kamphenkel, Susanne Laumann, Jens Bauer, Georg Carle
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引用次数: 3

摘要

本文提出了一个新的创新概念,即使用机器学习技术来优化低带宽网络上具有多条并行传输数据路径的整体数据吞吐量。流控制传输协议的多归属特性用于在多个端到端路径上并行传输用户数据。这项工作的重点是选择实际的最佳路径,其中当前路径的容量不一定事先知道。路径选择是由一个新的网络组件,即所谓的智能网络,以自主和灵活的方式适应于网络层。使用这种自适应机制,可以在移动场景中实现远程医疗等应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Path Selection Techniques for SCTP Multihoming
This paper proposes a new innovative concept for using machine learning techniques to optimize the overall data throughput over low bandwidth networks with several paths for a parallel transmission of data. The multihoming feature of the stream control transmission protocol is used to transfer user data parallel over several end-to-end paths. The work focuses on the selection of the actual best path, where the capacities of the present paths are not necessarily known in advance. The path selection is adapted in an autonomic and flexible way by a new network component, the so called intelligent network placed at the network layer. Using this adaptive mechanism it is possible to implement applications like long-distance medicine in mobile scenarios.
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