面向网络功能虚拟化的低复杂度多资源分组调度

Xin Li, Chen Qian
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引用次数: 47

摘要

网络功能在现代网络中被广泛部署,提供从入侵检测到HTTP缓存等各种网络服务。各种虚拟网络功能实例可以整合到一个物理中间盒中。根据服务类型的不同,不同流的数据包处理在中间盒中消耗不同的硬件资源。以往的多资源包调度方案存在着数据包缓冲和调度的计算复杂度和内存消耗高的问题,特别是在流量较大的情况下。本文设计了一种新颖的低复杂度和空间效率的数据包调度算法——近视算法,该算法支持网络功能虚拟化等多资源环境。近视是基于这样一个事实,即大多数互联网流量是由大象流量的一小部分贡献的。近视算法对大象流进行精确的调度,对老鼠流进行FIFO处理,实现了数据包缓冲和调度的简单性。我们将通过理论分析、原型实现和模拟来证明,近视以低成本和短数据包延迟实现多资源公平性。
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Low-complexity multi-resource packet scheduling for network function virtualization
Network functions are widely deployed in modern networks, providing various network services ranging from intrusion detection to HTTP caching. Various virtual network function instances can be consolidated into one physical middlebox. Depending on the type of services, packet processing for different flows consumes different hardware resources in the middlebox. Previous solutions of multi-resource packet scheduling suffer from high computational complexity and memory cost for packet buffering and scheduling, especially when the number of flows is large. In this paper, we design a novel low-complexity and space-efficient packet scheduling algorithm called Myopia, which supports multi-resource environments such as network function virtualization. Myopia is developed based upon the fact that most Internet traffic is contributed by a small fraction of elephant flows. Myopia schedules elephant flows with precise control and treats mice flows using FIFO, to achieve simplicity of packet buffering and scheduling. We will demonstrate, via theoretical analysis, prototype implementation, and simulations, that Myopia achieves multi-resource fairness at low cost with short packet delay.
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