Title
In-network quality optimization for adaptive video streaming services In-network quality optimization for adaptive video streaming services
Author
Faculty/Department
Faculty of Sciences. Mathematics and Computer Science
Publication type
article
Publication
New York ,
Subject
Mass communications
Computer. Automation
Source (journal)
IEEE transactions on multimedia. - New York
Volume/pages
16(2014) :8 , p. 2281-2293
ISSN
1520-9210
ISI
000345571300017
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
HTTP adaptive streaming (HAS) services allow the quality of streaming video to be automatically adapted by the client application in face of network and device dynamics. Due to their advantages compared to traditional techniques, HAS-based protocols are widely used for over-the-top (OTT) video streaming. However, they are yet to be adopted in managed environments, such as ISP networks. A major obstacle is the purely client-driven design of current HAS approaches, which leads to excessive quality oscillations, suboptimal behavior, and the inability to enforce management policies. Moreover, the provider has no control over the quality that is provided, which is essential when offering a managed service. This article tackles these challenges and facilitates the adoption of HAS in managed networks. Specifically, several centralized and distributed algorithms and heuristics are proposed that allow nodes inside the network to steer the HAS client's quality selection process. The algorithms are able to enforce management policies by limiting the set of available qualities for specific clients. Additionally, simulation results show that by coordinating the quality selection process across multiple clients, the proposed algorithms significantly reduce quality oscillations by a factor of five and increase the average delivered video quality by at least 14%.
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