Service function chaining along with network function virtualization enable flexible and rapid provisioning of network services to meet increasing demand for short-lived services with diverse requirements. In this paradigm, the main question to be answered is how to deploy the requested services by means of creating virtual network function (VNF) instances and routing the traffic between them, according to the services specifications. In this paper, we define the energy aware service deployment problem, and present the ILP formulation of it by considering limited traffic processing capacity of VNF instances and management concerns. We apply the Benders decomposition technique to decompose the problem into two smaller problems: master and sub-problem. As it is NP-Hard to find a non-trivial solution to the ILP master problem, we resort to the relaxed LP version of the problem. Then, we design methods based on the feasibility pump and duality theorem to rapidly calculate a near-optimal integer solution. The extensive simulation results show even in a network with 24 switches and 40 servers, our algorithm can deploy 35 requests in less than 3 seconds while the total power consumption is only about 1.3 times of the optimal solution obtained by the exhaustive exact approach. Moreover, it significantly outperforms the prominent SFC deployment algorithms in the fat-tree topology.

中文翻译：

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一种用于能量感知 SFC 部署的快速接近最优方法

服务功能链结合网络功能虚拟化，可以灵活、快速地提供网络服务，满足多样化需求的短期服务需求。在这种范式中，要回答的主要问题是如何根据服务规范，通过创建虚拟网络功能 (VNF) 实例并在它们之间路由流量来部署请求的服务。在本文中，我们定义了能量感知服务部署问题，并通过考虑 VNF 实例的有限流量处理能力和管理问题来提出它的 ILP 公式。我们应用 Benders 分解技术将问题分解为两个较小的问题：主问题和子问题。由于找到 ILP 主问题的非平凡解决方案是 NP-Hard，我们求助于问题的宽松 LP 版本。然后，我们设计了基于可行性泵和对偶定理的方法来快速计算接近最优的整数解。大量仿真结果表明，即使在具有 24 台交换机和 40 台服务器的网络中，我们的算法也可以在不到 3 秒的时间内部署 35 个请求，而总功耗仅为通过详尽精确方法获得的最优解的 1.3 倍左右。此外，它显着优于胖树拓扑中突出的 SFC 部署算法。我们的算法可以在不到 3 秒的时间内部署 35 个请求，而总功耗仅为穷举精确方法获得的最优解的 1.3 倍左右。此外，它显着优于胖树拓扑中突出的 SFC 部署算法。我们的算法可以在不到 3 秒的时间内部署 35 个请求，而总功耗仅为穷举精确方法获得的最优解的 1.3 倍左右。此外，它显着优于胖树拓扑中突出的 SFC 部署算法。