DocumentCode
3507068
Title
Link quality prediction for multimedia streaming based on available bandwidth and latency
Author
Lim Su Jin ; Lee Sze Wei ; Lau, Simon ; Karuppiah, Ettikan
Author_Institution
Univ. Tunku Abdul Rahman, Kuala Lumpur, Malaysia
fYear
2013
fDate
21-24 Oct. 2013
Firstpage
1025
Lastpage
1032
Abstract
Network performance metrics such as available bandwidth and latency are essential to achieve good Quality of Service (QoS) in multimedia streaming. There are unique requirements in network performance metrics for media applications, such as audio conferencing, video streaming, video conferencing, and high-definition (HD) video conferencing. In this paper, we focus on conference call type suggestion based on link quality prediction. The link´s quality is classified based on the available bandwidth and latency between two network nodes. We have implemented and compared two of the most popular supervised learning based classification methods, i.e. logistic regression and support vector machine (SVM). We have compared the performance of both methods and their suitability to apply in link quality prediction. The experimental results show that SVM outperforms logistic regression for binary and multiclass classification in terms of accuracy.
Keywords
computer network performance evaluation; media streaming; multimedia communication; pattern classification; quality of service; radio links; regression analysis; SVM; bandwidth availability; binary classification; latency; link quality prediction; logistic regression; media applications; multiclass classification; multimedia streaming; network performance metrics; quality of service; Accuracy; Bandwidth; Kernel; Logistics; Streaming media; Support vector machines; Training; classification; logistic regression; multimedia streaming; support vector machine;
fLanguage
English
Publisher
ieee
Conference_Titel
Local Computer Networks Workshops (LCN Workshops), 2013 IEEE 38th Conference on
Conference_Location
Sydney, NSW
Print_ISBN
978-1-4799-0539-3
Type
conf
DOI
10.1109/LCNW.2013.6758547
Filename
6758547
Link To Document