Online NFV-Enabled Multicasting in Mobile Edge Cloud Networks

Abstract

Mobile Edge Computing (MEC) reforms the cloud paradigm by bringing unprecedented computing capacity to the vicinity of mobile users at the mobile network edge. This provides end-users with swift and powerful computing, energy efficiency, storage capacity, mobility-and context-awareness support. Furthermore, provisioning virtualized network services in MEC can improve user service experience, simplify network service deployments, and ease network resource management. However, user requests usually arrive into the system dynamically and different user requests may have different resource demands. How to optimize and guarantee the performance of MEC is of significant importance and challenging. In this paper, we study the problem of online NFV-enabled multicasting in an MEC network with resource capacity constraints on both cloudlets and links. We first devise an approximation algorithm for the cost minimization problem for a single NFV-enabled multicast request admission. We then propose an online algorithm with a provable competitive ratio for the online throughput maximization problem where NFV-enabled multicast requests arrive one by one without the knowledge of future request arrivals. We admit the requests through placing or sharing VNF instances of network functions in their service chains to meet their computing and bandwidth resource demands, and we introduce a novel cost model to capture the dynamic usages of different resources and perform network resource allocations based on the proposed cost model. We finally evaluate the performance of the proposed algorithms through experimental simulations. Simulation results demonstrate that the proposed algorithms are promising.