Software defined networking (SDN) and network function virtualization (NFV) are key enabling technologies in fifth generation (5G) communication networks for embedding service-level customized network slices in a network infrastructure, based on statistical resource demands to satisfy long-term quality of service (QoS) requirements. However, traffic loads in different slices are subject to changes over time, resulting in challenges for consistent QoS provisioning. In this paper, a dynamic flow migration problem for embedded services is studied, to meet end-to-end (E2E) delay requirements with time-varying traffic. A multi-objective mixed integer optimization problem is formulated, addressing the trade-off between load balancing and reconfiguration overhead. The problem is transformed to a tractable mixed integer quadratically constrained programming (MIQCP) problem. It is proved that there is no optimality gap between the two problems; hence, we can obtain the optimum of the original problem by solving the MIQCP problem with some post-processing. To reduce time complexity, a heuristic algorithm based on redistribution of hop delay bounds is proposed to find an efficient solution. Numerical results are presented to demonstrate the aforementioned trade-off, the benefit from flow migration in terms of E2E delay guarantee, as well as the effectiveness and efficiency of the heuristic solution.

中文翻译：

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支持 SDN/NFV 的 5G 核心网络中嵌入式服务的动态流迁移

软件定义网络 (SDN) 和网络功能虚拟化 (NFV) 是第五代 (5G) 通信网络中的关键使能技术，用于在网络基础设施中嵌入服务级定制网络切片，基于统计资源需求以满足长期质量服务 (QoS) 要求。然而，不同切片中的流量负载会随着时间的推移而发生变化，这给一致的 QoS 提供带来了挑战。在本文中，研究了嵌入式服务的动态流迁移问题，以满足具有时变流量的端到端 (E2E) 延迟要求。制定了多目标混合整数优化问题，解决了负载平衡和重新配置开销之间的权衡问题。该问题转换为易于处理的混合整数二次约束规划 (MIQCP) 问题。证明了这两个问题之间不存在最优性差距；因此，我们可以通过一些后处理来解决 MIQCP 问题，从而获得原始问题的最优解。为了降低时间复杂度，提出了一种基于跳时延边界重新分配的启发式算法来寻找有效的解决方案。数值结果展示了上述权衡、流迁移在端到端延迟保证方面的好处，以及启发式解决方案的有效性和效率。为了降低时间复杂度，提出了一种基于跳时延边界重新分配的启发式算法来寻找有效的解决方案。数值结果展示了上述权衡、流迁移在端到端延迟保证方面的好处，以及启发式解决方案的有效性和效率。为了降低时间复杂度，提出了一种基于跳时延边界重新分配的启发式算法来寻找有效的解决方案。数值结果展示了上述权衡、流迁移在端到端延迟保证方面的好处，以及启发式解决方案的有效性和效率。