Dynamic Flow Migration for Embedded Services in SDN/NFV-Enabled 5G Core Networks

• Published in: IEEE transactions on communications Vol. 68; no. 4; pp. 2394 - 2408
• Main Authors: Qu, Kaige, Zhuang, Weihua, Ye, Qiang, Shen, Xuemin, Li, Xu, Rao, Jaya
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 5G mobile communication; Algorithms; Communication networks; Delays; dynamic flow migration; Dynamic scheduling; Embedding; end-to-end (E2E) delay; Heuristic methods; Mixed integer; Multiple objective analysis; Network function virtualization; network slicing; Optimization; Post-production processing; Provisioning; Quality of service; Quality of service architectures; Reconfiguration; Resource management; SDN/NFV-enabled 5G networks; Service function chaining (SFC); Software; Software-defined networking; Tradeoffs; Traffic delay; VNF state transfer
• ISSN: 0090-6778; 1558-0857
• DOI: 10.1109/TCOMM.2020.2968907

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.