Title
Resource Allocation for Virtual Streaming Media Server Cluster in Cloud-based Multi-version VoD
Abstract
With the rapid development of mobile Internet and smart devices, VoD (video on demand) providers build media cloud to offer multi-bitrate video streaming services to users at a reduced cost, called as cloud-based multi-version VoD. In cloud-based multi-version VoD, we need to solve the problem of allocating appropriate resources for virtual streaming media server cluster with the aim of optimizing the user experience and reducing the service cost. To address this problem, a resource allocation for virtual streaming media server cluster in cloud-based multi-version VoD is proposed in this paper. We firstly analyze the user historical learning logs to mine the user behavior characteristics, including the average user request arrival rate, the video playing time distribution, and the video popularity distribution, etc. Then, based on the user behavior characteristics and the queueing theory, a resource allocation model for the virtual streaming media server cluster is introduced. It predicts the user arrival rate at first and then allocates appropriate resources dynamically to solve the resources allocation irrationality problem. Simulation results have proved the proposed method can allocate appropriate resources for virtual streaming media server cluster, which can ensure the user experience satisfaction and improve the resources utilization.
Year
DOI
Venue
2018
10.1109/CSCWD.2018.8465244
2018 IEEE 22nd International Conference on Computer Supported Cooperative Work in Design ((CSCWD))
Keywords
Field
DocType
resource allocation,multi-version VoD,cloud,virtual streaming media server cluster,queueing theory
Resource management,Transcoding,User experience design,Reduced cost,Computer science,Server,Queueing theory,Resource allocation,Distributed computing,Cloud computing
Conference
ISBN
Citations 
PageRank 
978-1-5386-1483-9
0
0.34
References 
Authors
5
6
Name
Order
Citations
PageRank
Hui Zhao1293.98
Jing Wang2203.79
feng liu318039.13
Quan Wang410521.41
Nan Luo513.05
Weizhan Zhang610118.64