网络架构权衡的案例研究

N. Matni, A. Tang, J. Doyle
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引用次数: 12

摘要

软件定义网络(SDN)在控制平面和数据平面之间建立了分离,允许集中网络智能和状态——通过这种方式,底层网络基础设施对应用程序是隐藏的。这与现有的分布式网络架构形成鲜明对比,在现有的分布式网络架构中,控制平面和数据平面垂直结合,网络智能和状态以及应用程序分布在整个网络中。也可以想象,网络功能的一些元素通过SDN以集中的方式实现,而其他组件以分布式的方式实现。此外,分布式实现可以具有不同级别的去中心化,范围从短视(本地算法仅使用本地信息)到协调(本地算法同时使用本地和共享信息)。通过这种方式,短视的分布式架构和完全集中式架构处于更广泛的混合软件定义网络(HySDN)设计空间的两个极端。以准入控制为例,我们利用分布式最优控制的最新发展,为网络设计师提供定量比较不同架构的工具,使他们能够以原则性的方式探索相关的HySDN设计空间。特别是,我们假设路由在较慢的时间尺度上完成,并寻求在理想的工作点周围稳定网络,尽管网络和快速变化的流量需求造成了物理通信延迟。我们展示了存在这样的场景,其中一种架构允许比另一种架构具有更好的性能,从而突出了本文中提出的方法的有用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A case study in network architecture tradeoffs
Software defined networking (SDN) establishes a separation between the control plane and the data plane, allowing network intelligence and state to be centralized -- in this way the underlying network infrastructure is hidden from the applications. This is in stark contrast to existing distributed networking architectures, in which the control and data planes are vertically combined, and network intelligence and state, as well as applications, are distributed throughout the network. It is also conceivable that some elements of network functionality be implemented in a centralized manner via SDN, and that other components be implemented in a distributed manner. Further, distributed implementations can have varying levels of decentralization, ranging from myopic (in which local algorithms use only local information) to coordinated (in which local algorithms use both local and shared information). In this way, myopic distributed architectures and fully centralized architectures lie at the two extremes of a broader hybrid software defined networking (HySDN) design space. Using admission control as a case study, we leverage recent developments in distributed optimal control to provide network designers with tools to quantitatively compare different architectures, allowing them to explore the relevant HySDN design space in a principled manner. In particular, we assume that routing is done at a slower timescale, and seek to stabilize the network around a desirable operating point despite physical communication delays imposed by the network and rapidly varying traffic demand. We show that there exist scenarios for which one architecture allows for fundamentally better performance than another, thus highlighting the usefulness of the approach proposed in this paper.
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