Heavy-traffic analysis of QoE optimality for on-demand video streams over fading channels

Ping-Chun Hsieh, I. Hong Hou

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

This paper proposes online scheduling policies to optimize quality of experience (QoE) for video-on-demand applications in wireless networks. We consider wireless systems where an access point (AP) transmits video content to clients over fading channels. The QoE of each flow is measured by its duration of video playback interruption. We are specifically interested in systems operating in the heavy-traffic regime. We first consider a special case of ON-OFF channels and establish a scheduling policy that achieves every point in the capacity region under heavy-traffic conditions. This policy is then extended for more general fading channels, and we prove that it remains optimal under some mild conditions. We then formulate a network utility maximization problem based on the QoE of each flow. We demonstrate that our policies achieve the optimal overall utility when their parameters are chosen properly. Finally, we compare our policies against three popular policies. Simulation results validate that the proposed policy indeed outperforms existing policies.

Original languageEnglish
Title of host publicationIEEE INFOCOM 2016 - 35th Annual IEEE International Conference on Computer Communications
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467399531
DOIs
StatePublished - 27 Jul 2016
Event35th Annual IEEE International Conference on Computer Communications, IEEE INFOCOM 2016 - San Francisco, United States
Duration: 10 Apr 201614 Apr 2016

Publication series

NameProceedings - IEEE INFOCOM
Volume2016-July
ISSN (Print)0743-166X

Conference

Conference35th Annual IEEE International Conference on Computer Communications, IEEE INFOCOM 2016
CountryUnited States
CitySan Francisco
Period10/04/1614/04/16

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