Optimizing Segment Storage and Retrieval for Distributed Video-on-Demand

MPhil Thesis Defence


Title: "Optimizing Segment Storage and Retrieval for
Distributed Video-on-Demand"

By

Miss Zhuolin Xu


Abstract

In a distributed large-scale video-on-demand (VoD), a content provider 
often deploys local servers close to their users.  A movie is partitioned 
into k segments which the servers collaboratively store and retrieve 
(k<=1). A critical but challenging problem is how to minimize overall 
system deployment cost due to server bandwidth, server storage, and 
network traffic among servers.  In this paper, we address this problem 
through jointly optimizing movie storage and retrieval in the server 
network.

We first formulate the optimization problem and show that it is NP-hard. 
To address the problem, we propose a novel, effective and implementable 
heuristic.  The heuristic, termed LP-SR, decomposes the problem into two 
computationally efficient linear programs (LPs) for segment storage and 
retrieval, respectively. The strength of LP-SR is that it is 
asymptotically optimal in terms of k, and k does not need to be high to 
achieve near optimality (around 5 to 10 in our study). For large movie 
pool, we propose a movie grouping algorithm to further reduce the 
computational complexity without compromising much on the performance. 
Through extensive simulation study, LP-SR is shown to achieve 
significantly the lowest cost as compared with other state-of-the-art and 
traditional schemes, outperforming them by a wide margin (by multiple 
times in many cases). It attains performance very close to the global 
optimum of minimum cost.


Date:			Tuesday, 21 August 2012

Time:			3:00pm – 5:00pm

Venue:			Room 3501
 			Lifts 25/26

Committee Members:	Dr. Gary Chan (Supervisor)
 			Dr. Jogesh Muppala (Chairperson)
 			Dr. Lin Gu


**** ALL are Welcome ****