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Deploying default paths by joint optimization of flow table and group table in SDNs

机译:通过联合优化SDN中的流表和组表来部署默认路径

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Software Defined Networking (SDN) separates the control plane from the data plane to ease network management and provide flexibility in packet routing. The control plane interacts with the data plane through the forwarding tables, usually including a flow table and a group table, at each switch. Due to high cost and power consumption of Ternary Content Addressable Memory (TCAM), commodity switches can only support flow/group tables of limited size, which presents serious challenge for SDN to scale to large networks. One promising approach to address the scalability problem is to deploy aggregate default paths specified by wildcard forwarding rules. However, the multi-dimensional interaction among numerous system parameters and performance/scalability considerations makes the problem of setting up the flow/group tables at all switches for optimal overall layout of default paths very challenging. This paper studies the joint optimization of flow/group tables in the complex setting of large-scale SDNs. We formulate this problem as an integer linear program, and prove its NP-Hardness. An efficient algorithm with bounded approximation factors is proposed to solve the problem. The properties of our algorithm are formally analyzed. We implement the proposed algorithm on an SDN testbed for experimental studies and use simulations for large-scale investigation. The experimental results and simulation results demonstrate high efficiency of our proposed algorithm.
机译:软件定义网络(SDN)将控制平面与数据平面分开,以简化网络管理并在数据包路由中提供灵活性。控制平面通过每个交换机上的转发表(通常包括流表和组表)与数据平面进行交互。由于三态内容可寻址存储器(TCAM)的高成本和功耗,商品交换机只能支持有限大小的流/组表,这对SDN扩展到大型网络提出了严峻的挑战。解决可伸缩性问题的一种有前途的方法是部署通配符转发规则指定的聚合默认路径。但是,众多系统参数之间的多维交互以及性能/可伸缩性考虑因素使得在所有交换机上建立流/组表以实现默认路径的最佳总体布局这一问题变得非常具有挑战性。本文研究了在大型SDN复杂环境中流/组表的联合优化。我们将此问题公式化为整数线性程序,并证明其NP-Hardness。提出了一种有界近似因子的有效算法。正式分析了我们算法的特性。我们在SDN测试平台上实施提出的算法以进行实验研究,并使用模拟进行大规模调查。实验结果和仿真结果证明了该算法的高效率。

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