Edge-computing-assisted virtual reality computation offloading: an empirical study

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dc.contributor.authorNyamtiga, Baraka William
dc.contributor.authorHermawan, Airlangga Adi
dc.contributor.authorLuckyarno, Yakub Fahim
dc.contributor.authorKim, Tae-wook
dc.contributor.authorJung, Deok-young
dc.contributor.authorKwak, Jin sam
dc.contributor.authorYun, Ji-hoon
dc.date.accessioned2023-08-09T06:56:28Z
dc.date.available2023-08-09T06:56:28Z
dc.date.issued2022
dc.descriptionJournal Articleen_US
dc.description.abstractOffloading heavy virtual reality (VR) computational operations to a network edge computation entity is receiving increasing attention as a tool to wirelessly and energy efficiently provide low-end client devices with high-quality and immersive interactive VR services anytime and anywhere across the globe. In this work, we aim to provide an understanding of various characteristics of VR computation offloading through comprehensive experiments conducted using a prototype testbed for edge-assisted VR processing and streaming. First, we investigate the benefits of VR offloading in terms of computational load and power consumption reduction for a client device compared to standalone operation. Next, we measure VR traffic patterns, including frame size and data and packet rates with various settings, such as different resolution and encoding options. We also measure several performance metrics associated with the quality of experience, namely, frame rate, packet loss rate, and image quality, with various configuration settings. Then, we present latency measurement studies and investigate per-component latency with various settings. Furthermore, we report the rigorous experiments performed to study the impacts of latency and motion patterns on the black borders formed due to image reprojection and the overfilling technique used to eliminate these black borders.en_US
dc.description.sponsorshipThis work was supported by the Institute of Information & Communications Technology Planning & Evaluation (IITP), South Korea, funded by the Korean Government [Ministry of Science and ICT (MSIT)] [Biosignal-Based Predictive Content Creation for Cloud Virtual Reality (VR)] under Grant 2017-0-00650.en_US
dc.identifier.urihttp://www.suaire.sua.ac.tz/handle/123456789/5572
dc.language.isoenen_US
dc.publisherIEEE Accessen_US
dc.subjectVirtual realityen_US
dc.subjectEdge computingen_US
dc.subjectOffloadingen_US
dc.subjectVR streamingen_US
dc.subjectLatencyen_US
dc.subjectOverfillingen_US
dc.titleEdge-computing-assisted virtual reality computation offloading: an empirical studyen_US
dc.typeArticleen_US

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