Dynamic Rendering-Aware VR Service Module Placement Strategy in MEC Networks. (18th August 2022)

• Record Type: Journal Article
• Authors: Liu, Chunyu; Zhang, Heli; Li, Xi; Ji, Hong
• Other Names: Alamoodi A.H. Academic Editor.
• Is Part Of: Wireless communications and mobile computing. Volume 2022(2022)
• Publication Date: 2022-08-18
• Subjects: Wireless communication systems -- Periodicals; Mobile communication systems -- Periodicals; 621.38205
• DOI: 10.1155/2022/1237619
• Languages: English
• ISSNs: 1530-8669

Abstract

Abstract : Combining multiaccess edge computing (MEC) technology and wireless virtual reality (VR) game is a promising computing paradigm. Offloading the rendering tasks to the edge node can make up for the lack of computing resources of mobile devices. However, the current offloading works ignored that when rendering is enabled at the MEC server, the rendering operation depends heavily on the environment deployed on this MEC serve. In this paper, we propose a dynamically rendering-aware service module placement scheme for wireless VR games over the MEC networks. In this scheme, the rendering tasks of VR games are offloaded to the MEC server and closely coupled with service module placement. At the same time, to further optimize the end-to-end latency of VR video delivery, the routing delay of the rendered VR video stream and the costs of the service module migration are jointly considered with the proposed placement scheme. The goal of this scheme is to minimize the sum of the network costs over a long time under satisfying the delay constraint of each player. We model our strategy as a high-order, nonconvex, and time-varying function. To solve this problem, we transform the placement problem into the min-cut problem by constructing a series of auxiliary graphs. Then, we propose a two-stage iterative algorithm based on convex optimization and graphs theory to solve our object function. Finally, extensive simulation results show that our proposed algorithm can ensure low end-to-end latency for players and low network costs over the other baseline algorithms.