DocumentCode :
589012
Title :
A fast, simple and near-optimal content placement scheme for a large-scale VoD system
Author :
Jun He ; Xiaoming Zhao ; Baohua Zhao
Author_Institution :
Sch. of Comput. Sci. & Technol., Univ. of Sci. & Technol. of China, Hefei, China
fYear :
2012
fDate :
21-23 Nov. 2012
Firstpage :
378
Lastpage :
382
Abstract :
Video-on-Demand(VoD) service providers operate their own networks with large-scale serving nodes, each of which serves users in a certain geographic area. Efficient content placement can dramatically reduce the network latency and improve the user utilization. Content placement is a difficult problem though, due to the explosively increasing video library, the limited disk capacity and high diversity of request patterns. In this paper, we formulate the problem as an integer program, with the simple and practical objective of maximizing the aggregate amount of hitting data. We prove that this problem is NPhard. Jointly considering the size and popularity distributions of the video clips, we propose a fast greedy algorithm to solve it. Numerical results show that our algorithm is near-optimal (within 1-3% of optimal) and more efficient than existing solutions. We also evaluate our assumed distributions of video clips through a case study of the Youtube video data.
Keywords :
greedy algorithms; integer programming; optimisation; social networking (online); video on demand; NP-hard; Youtube video data; fast greedy algorithm; integer program; large scale VoD system; limited disk capacity; near optimal content placement scheme; network latency; request patterns; user utilization; video clips; video library; video on demand service providers; Aggregates; Bandwidth; Greedy algorithms; Libraries; Silicon; Sociology; Statistics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communication Systems (ICCS), 2012 IEEE International Conference on
Conference_Location :
Singapore
ISSN :
Pending
Print_ISBN :
978-1-4673-2052-8
Type :
conf
DOI :
10.1109/ICCS.2012.6406174
Filename :
6406174
Link To Document :
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