Empirical evaluation of HTTP adaptive streaming under vehicular mobility

Authors:
Jun Yao;Salil S. Kanhere;Imran Hossain;Mahbub Hassan
Affiliations:
School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia;School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia;School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia;School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia
Venue:
NETWORKING'11 Proceedings of the 10th international IFIP TC 6 conference on Networking - Volume Part I
Year:
2011

Citing 2
Cited 2

An empirical study of bandwidth predictability in mobile computing

Proceedings of the third ACM international workshop on Wireless network testbeds, experimental evaluation and characterization
Rate adaptation for conversational 3G video

INFOCOM'09 Proceedings of the 28th IEEE international conference on Computer Communications Workshops

An evaluation of dynamic adaptive streaming over HTTP in vehicular environments

Proceedings of the 4th Workshop on Mobile Video
Adaptive Transmission Control Protocol-trunking flow control mechanism for supporting proxy-assisted video on demand system

International Journal of Communication Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

Adaptive streaming is a promising technique for delivering a high-quality video streaming experience. In this technique, the streaming bit-rate is constantly adjusted in accordance to the variations in the underlying network bandwidth conditions. A popular instantiation of this approach is to extend traditional HTTP-based streaming. While several such implementations are widely available, it is unclear how they perform under a typical high-speed vehicular environment, wherein the wireless bandwidth varies significantly and rapidly. In this paper, we seek to provide some insights on this issue through empirical experiments driven by real-world wireless bandwidth traces collected from moving vehicles. Our results suggest that, with appropriate parameter configurations, HTTP adaptive streaming is an effective solution for delivering a high-quality smooth streaming experience even under high-speed vehicular mobility.