Multimedia QoE optimized management using prediction and statistical learning
2010 (English)In: 35th Annual IEEE Conference on Local Computer Networks: LCN 2010, Piscataway, NJ: IEEE Communications Society, 2010, 328-331 p.Conference paper (Refereed)
In this paper, we present a scheme for flow management with heterogeneous access technologies available indoors and in a campus network such as 3G and Wi-Fi. Statistical learning is used as a key for optimizing a target variable namely video quality of experience (QoE). First we analyze the data using passive measurements to determine relationships between parameters and their impact on the main performance indicator, namely the video QoE value. The derived weights are used for performing prediction in every discrete time interval of our designed autonomic control loop to know approximately the QoE in the next time interval and be able to perform a switch to another access technology if it yields a better QoE level. This user-perspective performance optimization is in line with operator and service provider goals. QoE performance models for slow vehicular and pedestrian speeds for Wi-Fi and 3G are derived and compared as well.
Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Communications Society, 2010. 328-331 p.
, Conference on Local Computer Networks. Proceedings, ISSN 0742-1303 ; 35
Research subject Mobile and Pervasive Computing
IdentifiersURN: urn:nbn:se:ltu:diva-31660DOI: 10.1109/LCN.2010.5735733ScopusID: 79955048515Local ID: 5e8d0a50-89bd-11df-8806-000ea68e967bISBN: 978-1-4244-8388-4OAI: oai:DiVA.org:ltu-31660DiVA: diva2:1004894
IEEE Conference on Local Computer Networks : 11/10/2010 - 14/10/2010
Validerad; 2010; 20100707 (elkotob)2016-09-302016-09-30Bibliographically approved