Cost optimal resource provisioning for live video forwarding across video data centers

Gao, Yihong, Ma, Huadong, Liu, Wu and Yu, Shui 2016, Cost optimal resource provisioning for live video forwarding across video data centers. In Wang, Yu, Yu, Ge, Zhang, Yanyong, Han, Zhu and Wang, Guoren (ed), , Springer, Cham, Switzerland, pp.27-38, doi: 10.1007/978-3-319-42553-5_3.

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Title Cost optimal resource provisioning for live video forwarding across video data centers
Author(s) Gao, Yihong
Ma, Huadong
Liu, Wu
Yu, ShuiORCID iD for Yu, Shui
Editor(s) Wang, Yu
Yu, Ge
Zhang, Yanyong
Han, Zhu
Wang, Guoren
Publication date 2016
Series Lecture notes in computer science
Chapter number 3
Total chapters 39
Start page 27
End page 38
Total pages 12
Publisher Springer
Place of Publication Cham, Switzerland
Keyword(s) video surveillance as a service
video data center
live video forwarding
resource provisioning
Summary Live video forwarding for IP cameras has become a popular service in video data centers. In the forwarding service, requests of end users from different regions arrive in real-time to gain live video streams of IP cameras from inter-connected video data centers. A fundamental scheduling problem is how to assign resources with the global optimal resource cost and forwarding delay to forward live video streams. We introduce the resource provisioning cost as the combination of media server cost, connection bandwidth cost, and forwarding delay cost. In this paper, a multi-objective resource provisioning (MORP) approach is proposed to deal with the online inter-datacenter resource provisioning problem. The approach aims at minimizing the resource provisioning cost during live video forwarding. It adaptively allocates media servers in appropriate video data centers and connects the chosen media servers together to provide system scalability and connectivity. Different from previous works, MORP takes both resource capacity and diversity (e.g. location and price) into consideration during live video forwarding. Finally, the experimental results show that MORP approach not only cuts the resource provisioning cost of 3% to 10% comparing to the bench mark approach, but also shortens the resource provisioning delay.
ISBN 9783319425528
ISSN 0302-9743
Language eng
DOI 10.1007/978-3-319-42553-5_3
Field of Research 080109 Pattern Recognition and Data Mining
080503 Networking and Communications
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category B1 Book chapter
ERA Research output type B Book chapter
Copyright notice ©2016, Springer
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