vix.ing · top · new · best · stats · spec

Cross-Layer Assisted Early Congestion Control for Cloud VR Services in 5G Edge Network

2023/07/10 by Wanghong Yang, Wenji Du, Yang, Wanghong +9
Computer Science · Engineering · #FOS: Computer and information sciences #Image and Video Quality Assessment #Networking and Internet Architecture (cs.NI) #Software-Defined Networks and 5G #Telecommunications and Broadcasting Technologies

paper · pdf · doi:10.48550/arxiv.2307.04529

openalex publication_date 2023/07/10 · openalex created_date 2023/07/12 · openalex updated_date 2026/07/28

Abstract

Cloud virtual reality (VR) has emerged as a promising technology, offering users a highly immersive and easily accessible experience. However, the current 5G radio access network faces challenges in accommodating the bursty traffic generated by multiple cloudVR flows simultaneously, leading to congestion at the 5G base station and increased delays. In this research, we present a comprehensive quantitative analysis that highlights the underlying causes for the poor delay performance of cloudVR flows within the existing 5G protocol stack and network. To address these issues, we propose a novel cross-layer informationassisted congestion control mechanism deployed in the 5G edge network. Experiment results show that our mechanism enhances the number of concurrent flows meeting delay standards by 1.5x to 2.5x, while maintaining a smooth network load. These findings underscore the potential of leveraging 5G edge nodes as a valuable resource to effectively meet the anticipated demands of future services.

Related