QoE Prediction for Radio Resource Management

M. Hirth; B. Staehle; F. Wamser; R. Pries; D. Staehle

Testbeds and Research Infrastructures. Development of Networks and Communities. 6th International ICST Conference, TridentCom 2010, Berlin, Germany, May 18-20, 2010, Revised Selected Papers

Research Article

QoE Prediction for Radio Resource Management

Download

626 downloads

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.1007/978-3-642-17851-1_47,
    author={M. Hirth and B. Staehle and F. Wamser and R. Pries and D. Staehle},
    title={QoE Prediction for Radio Resource Management},
    proceedings={Testbeds and Research Infrastructures. Development of Networks and Communities. 6th International ICST Conference, TridentCom 2010, Berlin, Germany, May 18-20, 2010, Revised Selected Papers},
    proceedings_a={TRIDENTCOM},
    year={2012},
    month={10},
    keywords={QoE radio resource management wireless},
    doi={10.1007/978-3-642-17851-1_47}
}

M. Hirth
B. Staehle
F. Wamser
R. Pries
D. Staehle
Year: 2012
QoE Prediction for Radio Resource Management
TRIDENTCOM
Springer
DOI: 10.1007/978-3-642-17851-1_47

M. Hirth¹^,*, B. Staehle¹^,*, F. Wamser¹^,*, R. Pries¹^,*, D. Staehle¹^,*

1: University of Würzburg

*Contact email: hirth@informatik.uni-wuerzburg.de, bstaehle@informatik.uni-wuerzburg.de, wamser@informatik.uni-wuerzburg.de, pries@informatik.uni-wuerzburg.de, dstaehle@informatik.uni-wuerzburg.de

Abstract

In this paper, we introduce a monitoring tool which measures application-specific parameters. These parameters are used to predict the QoE and to perform resource management based on QoE thresholds. We demonstrate the tool for YouTube traffic in an IEEE 802.11 mesh network. Thereby, the QoE is based on the player video buffer size and the resource management can include rerouting, throttling of best effort traffic, or a gateway handover.

Keywords: QoE radio resource management wireless

Published: 2012-10-10

: http://dx.doi.org/10.1007/978-3-642-17851-1_47