Delay-tolerant resource scheduling in large-scale virtualized radio access networks

Network virtualization facilitates radio access network (RAN) sharing by decoupling the physical network infrastructure from the wireless services. This paper considers a scenario in which a virtual network operator (VNO) leases wireless resources from a software-defined networking based virtualized RAN set up by a third-party infrastructure provider (InP). In order to optimize the revenue, the VNO explores jointly the delay tolerance in mobile traffic and the weak load coupling across the base stations (BSs) when making the resource scheduling decisions to serve its mobile users (MUs). The problem faced by the VNO can be straightforwardly transformed to the problem of minimizing the payments to the InP, which is formulated as a finite time horizon constrained Markov decision process (MDP). However, for a large-scale network with a huge number of MUs, the problem solving becomes extremely challenging. Through the dual decomposition approach, we decompose the problem into a series of per-MU MDPs, which can be solved distributedly. Moreover, the independence of channel conditions between a MU and the BSs is expected to further simplify solving each per-MU MDP. The simulations carried out in this paper show that our proposed scheme achieves minimal average payments compared with other existing approaches in literature.