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Dynamic Service Function Chaining in SDN-enabled networks with middleboxes

机译:具有中间盒的SDN网络中的动态服务功能链接

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Network functions typically need to be visited in a specific order to meet certain objectives, giving rise to the notion of Service Function Chaining. Software-Defined-Networking enables fine-grained traffic routing optimization while satisfying correct traversal of network functions. In this work, we investigate the problem of maximizing throughput in SDN-enabled networks with respect to service chaining specifications under both traditional and new constraints. Besides the algorithm design, we also derive rigorous performance bounds. In the offline traffic routing case, we propose Traffic-Merging-Algorithm and prove that, although the underlying optimization problem is generally NP-hard, our algorithm can efficiently compute the optimal solution in practical settings. In the online traffic routing case, we propose the Primal-Dual-Update-Algorithm, which comes with a system parameter that trades off the algorithm's throughput competitiveness and its meeting of QoS requirements, and prove that our online algorithm achieves optimal tradeoff. We demonstrate that our solutions can be used to address practical problems by conducting simulation-based evaluation over backbone and data center topologies.
机译:通常需要按照特定的顺序访问网络功能以满足特定的目标,从而产生了服务功能链的概念。软件定义的网络可实现细粒度的流量路由优化,同时满足对网络功能的正确遍历。在这项工作中,我们研究了在传统约束和新约束下,相对于服务链规范,在启用SDN的网络中最大化吞吐量的问题。除了算法设计之外,我们还导出了严格的性能范围。在离线交通路由的情况下,我们提出了Traffic-Merging-Algorithm并证明,尽管基本的优化问题通常是NP难的,但是我们的算法可以在实际设置中有效地计算最优解决方案。在在线流量路由的情况下,我们提出了Primal-Dual-Update-Algorithm,它带有一个权衡该算法的吞吐量竞争力和满足QoS要求的系统参数,并证明了我们的在线算法实现了最佳的权衡。我们证明,通过对骨干网和数据中心拓扑进行基于仿真的评估,我们的解决方案可用于解决实际问题。

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