Quality of experience optimized scheduling in multi-service wireless mesh networks

Andre B. Reis, Jacob Chakareski, Andreas Kassler, Susana Sargento

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

A growing trend has emerged in network architecture research to switch focus from Quality of Service (QoS) to Quality of Experience (QoE) optimization. In this paper, we first present QoE models that characterize user satisfaction of video, audio, and data services over wireless networks. We then develop a novel packet scheduling algorithm for multi-hop wireless networks that jointly optimizes the delivery of multiple video, audio, and data flows according to the QoE metrics. We formulate a multidimensional optimization problem that minimizes the overall distortion across all flows for the given network resources on wireless links. Fairness constraints over the flows are also considered as part of the optimization. Our experimental results, obtained with the NS-2 IEEE 802.16 MESH-mode simulator, show that distortion-aware scheduling can significantly increase the perceived quality of different wireless services under bandwidth constraints. Additionally, improved fairness across the competing flows is demonstrated relative to conventional scheduling techniques.

Original languageEnglish (US)
Title of host publication2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings
Pages3233-3236
Number of pages4
DOIs
StatePublished - 2010
Externally publishedYes
Event2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong, Hong Kong
Duration: Sep 26 2010Sep 29 2010

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Conference

Conference2010 17th IEEE International Conference on Image Processing, ICIP 2010
Country/TerritoryHong Kong
CityHong Kong
Period9/26/109/29/10

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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