Mobility-Aware Multi-Instance VNF Placement in Mobile Edge Computing Networks

Abstract

Mobile edge computing (MEC) is powerful for providing services with ultra-low latency and extremely high reliability to support newly emerging applications in 5G and beyond by leveraging network function virtualization (NFV) where each mobile user requests a service function chain (SFC). To guarantee the quality of experience (QoE), e.g., reduce the downtime of moving users, effective placement of virtual network functions (VNFs) in MEC networks is critical to cope with the user mobility. Placing multiple instances of SFC for each user is promising for reducing the downtime during moving. However, an extremely high resource cost is induced. Towards this challenge, this paper investigates the mobility-aware multi-instance (MAMI) VNF placement problem in MEC networks. According to the empirical probabilities that one user stays within the coverage of different edge nodes, both static and dynamic SFC instances are placed to balance the tradeoff between the downtime and resource cost. A MAMI VNF placement algorithm is proposed for resource cost minimization, where resource sharing among the SFC instances of each user is allowed to further reduce resource cost. Simulation results based on real-world-like moving users show the effectiveness of our proposed algorithm.