DocumentCode :
3744769
Title :
User-level fairness delivered: Network resource allocation for adaptive video streaming
Author :
Mu Mu;Steven Simpson;Arsham Farshad;Qiang Ni;Nicholas Race
Author_Institution :
School of Computing and Communications, Lancaster University, LA1 4WA Lancaster, United Kingdom
fYear :
2015
fDate :
6/1/2015 12:00:00 AM
Firstpage :
85
Lastpage :
94
Abstract :
HTTP adaptive streaming (HAS) technology is becoming a popular vehicle for online video delivery. HAS applications often compete for network resources without any coordination between each other in a shared network. This leads to quality of experience (QoE) fluctuations and unfairness between end users. This paper introduces a user-level fairness model (UF) which exploits video quality, switching impact and cost efficiency as the fairness metrics to achieve user-level fairness in resource allocation. Experimental results demonstrate how this model is a foundation to orchestrate the resource consumption of HAS streams.
Keywords :
"Quality assessment","Video recording","Streaming media","Bit rate","Switches","Adaptation models"
Publisher :
ieee
Conference_Titel :
Quality of Service (IWQoS), 2015 IEEE 23rd International Symposium on
Type :
conf
DOI :
10.1109/IWQoS.2015.7404718
Filename :
7404718
Link To Document :
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