Multi-Tier CloudVR: Leveraging Edge Computing in Remote Rendered Virtual Reality

dc.contributorAalto Universityen
dc.contributor.authorMehrabi, Abbasen_US
dc.contributor.authorSiekkinen, Mattien_US
dc.contributor.authorKämäräinen, Teemuen_US
dc.contributor.authorYlä-Jääski, Anttien_US
dc.contributor.departmentDepartment of Computer Scienceen
dc.contributor.groupauthorHelsinki Institute for Information Technology (HIIT)en
dc.contributor.groupauthorComputer Science Professorsen
dc.contributor.groupauthorComputer Science - Computing Systems (ComputingSystems)en
dc.contributor.groupauthorProfessorship Ylä-Jääski A.en
dc.contributor.organizationNorthumbria Universityen_US
dc.contributor.organizationUniversity of Helsinkien_US
dc.descriptionPublisher Copyright: © 2021 ACM.
dc.description.abstractThe availability of high bandwidth with low-latency communication in 5G mobile networks enables remote rendered real-time virtual reality (VR) applications. Remote rendering of VR graphics in a cloud removes the need for local personal computer for graphics rendering and augments weak graphics processing unit capacity of stand-alone VR headsets. However, to prevent the added network latency of remote rendering from ruining user experience, rendering a locally navigable viewport that is larger than the field of view of the HMD is necessary. The size of the viewport required depends on latency: Longer latency requires rendering a larger viewport and streaming more content. In this article, we aim to utilize multi-access edge computing to assist the backend cloud in such remote rendered interactive VR. Given the dependency between latency and amount and quality of the content streamed, our objective is to jointly optimize the tradeoff between average video quality and delivery latency. Formulating the problem as mixed integer nonlinear programming, we leverage the interpolation between client's field of view frame size and overall latency to convert the problem to integer nonlinear programming model and then design efficient online algorithms to solve it. The results of our simulations supplemented by real-world user data reveal that enabling a desired balance between video quality and latency, our algorithm particularly achieves the improvements of on average about 22% and 12% in term of video delivery latency and 8% in term of video quality compared to respectively order-of-arrival, threshold-based, and random-location strategies.en
dc.description.versionPeer revieweden
dc.identifier.citationMehrabi, A, Siekkinen, M, Kämäräinen, T & Ylä-Jääski, A 2021, ' Multi-Tier CloudVR : Leveraging Edge Computing in Remote Rendered Virtual Reality ', ACM Transactions on Multimedia Computing, Communications and Applications, vol. 17, no. 2, 49 .
dc.identifier.otherPURE UUID: d027cf2f-542d-493d-ba97-6dc26ff17b62en_US
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dc.publisherAssociation for Computing Machinery (ACM)
dc.relation.ispartofseriesACM Transactions on Multimedia Computing, Communications and Applicationsen
dc.relation.ispartofseriesVolume 17, issue 2en
dc.subject.keywordgreedy algorithmen_US
dc.subject.keywordinteger nonlinear programming (INLP)en_US
dc.subject.keywordjoint optimizationen_US
dc.subject.keywordMulti-access edge computing (MEC)en_US
dc.subject.keywordrendered virtual reality (VR)en_US
dc.titleMulti-Tier CloudVR: Leveraging Edge Computing in Remote Rendered Virtual Realityen
dc.typeA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessäfi