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 mobile edge computing (MEC)-enabled small-cell networks for VR delivery. In the proposed architecture, multiple MEC servers can jointly provide VR head-mounted devices (HMDs) with edge caching and viewpoint computation services, while the computation tasks can also be performed at HMDs or on the cloud. Power allocation at base stations (BSs) is considered in coordination with horizontal collaboration (HC) and vertical collaboration (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, and a discrete branch-reduce-and-bound (DBRB) algorithm inspired by monotone optimization is proposed to effectively solve the problem. Simulation results demonstrate the advantage of the proposed architecture and algorithm in terms of existing ones.
翻译:由于虚拟现实(VR)视频应用程序的宽带宽度、低悬浮度和计算密集性特点,目前资源有限的无线和边缘网络无法满足按需交付VR的要求。在本信中,我们提议在移动边缘计算(MEC)带动的小细胞网络中建立一个用于VR交付的横向和纵向联合协作架构。在拟议的架构中,多个MEC服务器可以联合提供VR头挂设备,提供边缘缓存和视图计算服务,而计算任务也可以在HMD或云上进行。基站的电力分配与横向合作(HC)和纵向合作(VC)考虑予以考虑,以获得VR交付的低端至端延迟。随后将制定一个联合缓存、电力分配和任务卸载问题,并提议由单调优化所启发的离散分支和离线(DBRB)算法,以有效解决问题。模拟结果显示拟议的结构和现有结构的优势。