Network Congestion-aware Online Service Function Chain Placement and Load Balancing

Abstract

Emerging virtual network functions (VNFs) introduce new flexibility and scalability into traditional middlebox. Specifically, middleboxes are virtualized as software-based platforms running on commodity servers known as network points of presence (N-PoPs). Traditional network services are therefore realized by chained VNFs, i.e., service function chains (SFCs), running on potentially multiple N-PoPs. SFCs can be flexibly placed and routed to reduce operating cost. However, excessively pursuing low cost may incur congestion on some popular N-PoPs and links, which results in performance degradation or even violation of the service level of agreements. In this paper, we first propose an optimization problem for joint SFC placement and routing. Given the problem is NP-hard, we design an approximation algorithm named candidate path selection (CPS) with a theoretical performance guarantee. We then propose an online optimization problem for placement of SFCs with fast demand fluctuation. The problem concerns migration costs of VNFs between time slots, and we design an online candidate path selection (OCPS) algorithm to handle it. Extensive simulation results highlight that the CPS and OCPS algorithms provide efficient placement and routing of SFCs comparable to the optimal solution.