Joint Optimization of Movie Allocation and Traffic Distribution for an Auto-scaling Cloud-based VoD Data Center

MPhil Thesis Defence


Title: "Joint Optimization of Movie Allocation and Traffic Distribution 
for an Auto-scaling Cloud-based VoD Data Center"

By

Mr. Hongzheng XIONG


Abstract

In an auto-scaling cloud-based video-on-demand (VoD) data center, the 
virtual machines (VMs) can be turned on and off dynamically to serve 
fluctuating user traffic more cost-effectively. In such system, user 
traffic is mapped to one of the "auto-scaling levels" where a certain 
subset of VMs are turned on. These VMs are pre-loaded with movies to save 
the cost of movie replication at level switch. Due to limited storage and 
streaming capacities, the VMs may not serve all the movie requests; in 
which case the requests are directed to a repository as misses. We study, 
for the first time, the joint optimization of allocating movies and 
distributing user traffic among the VMs so as to minimize the misses at 
the repository. We formulate the problem and prove that it is NP-hard. We 
then propose AMTO (Auto-scaling Movie allocation and Traffic Distribution 
Optimization), a novel and efficient algorithm to address the problem. 
AMTO achieves computational efficiency even for large movie pool. 
Extensive simulation shows that it is closely optimal, achieving 
significantly lower miss traffic as compared with state-of-the-art schemes 
(often by more than 50%).


Date:			Wednesday, 24 June 2015

Time:			4:00pm - 6:00pm

Venue:			Room 4483
 			Lifts 25/26

Committee Members:	Prof. Gary Chan (Supervisor)
 			Prof. Qian Zhang (Chairperson)
 			Dr. Brahim Bensaou


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