Service Function Chaining and Network Function Virtualization are enabling technologies that provide dynamic network services with diverse QoS requirements. Regarding the limited infrastructure resources, service providers need to prioritize service requests and even reject some of low-priority requests to satisfy the requirements of high-priority services. In this paper, we study the problem of deployment and reconfiguration of a set of chains with different priorities with the objective of maximizing the service provider’s profit; wherein, we also consider management concerns including the ability to control the migration of virtual functions. We show the problem is more practical and comprehensive than the previous studies, and propose an MILP formulation of it along with two solving algorithms. The first algorithm is a fast polynomial-time heuristic that calculates an initial feasible solution to the problem. The second algorithm is an exact method that utilizes the initial feasible solution to achieve the optimal solution quickly. Using extensive simulations, we evaluate the algorithms and show the proposed heuristic can find a feasible solution in at least 83% of the simulation runs in less than 7 seconds, and the exact algorithm can achieve 25% more profit 8 times faster than the state-of-the-art MILP solving methods.

中文翻译：

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动态服务功能链优先部署

服务功能链和网络功能虚拟化是提供具有不同 QoS 要求的动态网络服务的使能技术。针对有限的基础设施资源，服务提供者需要对服务请求进行优先级排序，甚至拒绝一些低优先级的请求，以满足高优先级服务的需求。在本文中，我们研究了以服务提供商利润最大化为目标的一组具有不同优先级的链的部署和重新配置问题；其中，我们还考虑了管理问题，包括控制虚拟功能迁移的能力。我们表明该问题比以前的研究更实际和全面，并提出了它的 MILP 公式以及两种求解算法。第一种算法是快速多项式时间启发式算法，用于计算问题的初始可行解。第二种算法是一种精确方法，它利用初始可行解快速获得最优解。使用广泛的模拟，我们对算法进行了评估，并表明所提出的启发式算法可以在至少 83% 的模拟运行中在不到 7 秒的时间内找到可行的解决方案，并且精确的算法可以实现 25% 的利润，比状态快 8 倍——最先进的 MILP 求解方法。