MASCOT: Mobility-Aware Service Function Chain Routing in Mobile Edge Computing

In Mobile Edge Computing (MEC), users' traffic needs to traverse a set of service functions in a specific order, referred to as a service function chain (SFC), to complete service requests. Thus, SFC routing is an essential issue in MEC. In practice, user mobility and resource limitation are two critical challenges of SFC routing in MEC. However, the previous works either ignore the user mobility or resource limitation, especially the flow-table resources, leading to high transmission latency and resource overhead. In this paper, we study the mobility-aware service function chain routing in MEC. We design an SFC routing scheme called MASCOT to address the above challenges. MASCOT implements SFC routing through three steps: user location prediction, routing path decision, and packet forwarding. For user location prediction, we adopt the order-K Markov prediction method to predict users' next accessed base station. For routing path decision, we formulate the SFC routing selection (SRS) problem, which respects the resource constraints. We propose a primal-dual online SFC routing algorithm (POSR) for the SRS problem and prove that POSR can achieve good competitiveness. For packet forwarding, we propose a forwarding scheme based on segment routing to address the resource limitation challenge further. Extensive simulation results show that our scheme can improve the system throughput by about 40% compared with the state-of-the-art approaches.