Categorization-based video streaming for traffic mitigation in content delivery services

Categorization-based video streaming for traffic mitigation in content delivery services This paper presents a categorization-based video streaming approach (CVS) to mitigate the Internet traffic in content delivery services. The CVS uses the statistical information related to the users’ view patterns (i.e., the average view duration in accordance with the playback time of the content) to adjust the request period of content chunks. Therefore, it can reduce the amount of Internet traffic by reducing unnecessary chunk requests and content chunks. The operation of the CVS is based on the average view duration provided by the content provider (CP). However, even if the CP does not provide the average view duration of the content, the CVS can properly predict the average view duration by using the content categorization and adjust the request period of content chunks. The simulation results show that the CVS achieves better performance in terms of the average waste ratio of network resources, the amount of network traffic, and the number of chunk requests. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Multimedia Tools and Applications Springer Journals

Categorization-based video streaming for traffic mitigation in content delivery services

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Publisher
Springer US
Copyright
Copyright © 2017 by Springer Science+Business Media New York
Subject
Computer Science; Multimedia Information Systems; Computer Communication Networks; Data Structures, Cryptology and Information Theory; Special Purpose and Application-Based Systems
ISSN
1380-7501
eISSN
1573-7721
D.O.I.
10.1007/s11042-017-4770-2
Publisher site
See Article on Publisher Site

Abstract

This paper presents a categorization-based video streaming approach (CVS) to mitigate the Internet traffic in content delivery services. The CVS uses the statistical information related to the users’ view patterns (i.e., the average view duration in accordance with the playback time of the content) to adjust the request period of content chunks. Therefore, it can reduce the amount of Internet traffic by reducing unnecessary chunk requests and content chunks. The operation of the CVS is based on the average view duration provided by the content provider (CP). However, even if the CP does not provide the average view duration of the content, the CVS can properly predict the average view duration by using the content categorization and adjust the request period of content chunks. The simulation results show that the CVS achieves better performance in terms of the average waste ratio of network resources, the amount of network traffic, and the number of chunk requests.

Journal

Multimedia Tools and ApplicationsSpringer Journals

Published: May 24, 2017

References

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