LAUSR

Due to the large bandwidth, low latency and computationally intensive features of virtual reality (VR) video applications, the current resource-constrained wireless and edge networks cannot meet the requirements of on-demand VR delivery. In this letter, we propose a joint horizontal and vertical collaboration architecture in multi-access edge computing (MEC)-enabled small-cell networks for downlink VR delivery. In the proposed architecture, multiple MEC servers can jointly provide VR head-mounted devices (HMDs) with edge caching and viewpoint computation services, i.e., horizontal collaboration (HC), while the caching and computation strategies can collaborate among vertical layers, i.e., vertical collaboration (VC). Power allocation at base stations (BSs) is considered in coordination with HC and VC of MEC servers to obtain lower end-to-end latency of VR delivery. A joint caching, power allocation and task offloading problem is then formulated. By exploiting the hidden monotonicity of the problem, a discrete branch-reduce-and-bound (DBRB) algorithm is proposed to obtain the optimal solution efficiently. Simulation results demonstrate the advantage of the proposed architecture and algorithm in terms of existing ones.