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Cost Minimization for Rule Caching in Software Defined Networking

机译：软件定义网络中规则缓存的成本最小化

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摘要

Software-defined networking (SDN) is an emerging network paradigm that simplifies network management by decoupling the control plane and data plane, such that switches become simple data forwarding devices and network management is controlled by logically centralized servers. In SDN-enabled networks, network flow is managed by a set of associated rules that are maintained by switches in their local Ternary Content Addressable Memories (TCAMs) which support high-speed parallel lookup on wildcard patterns. Since TCAM is an expensive hardware and extremely power-hungry, each switch has only limited TCAM space and it is inefficient and even infeasible to maintain all rules at local switches. On the other hand, if we eliminate TCAM occupation by forwarding all packets to the centralized controller for processing, it results in a long delay and heavy processing burden on the controller. In this paper, we strive for the fine balance between rule caching and remote packet processing by formulating a minimum weighted flow provisioning ( ) problem with an objective of minimizing the total cost of TCAM occupation and remote packet processing. We propose an efficient offline algorithm if the network traffic is given, otherwise, we propose two online algorithms with guaranteed competitive ratios. Finally, we conduct extensive experiments by simulations using real network traffic traces. The simulation results demonstrate that our proposed algorithms can significantly reduce the total cost of remote controller processing and TCAM occupation, and the solutions obtained are nearly optimal.
机译：软件定义网络（SDN）是一种新兴的网络范例，它通过将控制平面和数据平面解耦来简化网络管理，从而使交换机成为简单的数据转发设备，并且网络管理由逻辑上集中的服务器控制。在启用SDN的网络中，网络流由一组关联的规则管理，这些规则由交换机在其本地三进制内容可寻址内存（TCAM）中维护，这些内存支持对通配符模式进行高速并行查找。由于TCAM是昂贵的硬件并且非常耗电，因此每个交换机只有有限的TCAM空间，在本地交换机上维护所有规则效率低下甚至不可行。另一方面，如果我们通过将所有数据包转发到集中式控制器进行处理来消除TCAM占用，则会导致较长的延迟，并给控制器带来沉重的处理负担。在本文中，我们通过制定最小加权流配置（）问题，力求在规则缓存和远程数据包处理之间达到最佳平衡，目的是最大程度地减少TCAM占用和远程数据包处理的总成本。如果给出了网络流量，我们提出一种有效的离线算法，否则，我们提出两种具有保证竞争比的在线算法。最后，我们通过使用真实的网络流量跟踪进行仿真来进行广泛的实验。仿真结果表明，我们提出的算法可以显着降低遥控器处理和TCAM占用的总成本，并且所获得的解决方案几乎是最优的。

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