POPCA: Optimizing Segment Caching for Peer-to-Peer On-Demand Streaming

MPhil Thesis Defence


Title: "POPCA: Optimizing Segment Caching for Peer-to-Peer On-Demand Streaming"

By

Mr. Ho-Shing Tang


Abstract

In peer-to-peer (P2P) on-demand streaming applications, multimedia content
is divided into segments and peers can seek any segments for viewing at
anytime. Since different segments may be of different popularity, random
segment caching would lead to segment popularity-supply mismatch, and
hence uneven workload distribution among peers. Some popular segments may
be far from peers, leading to inefficient search and streaming. In this
paper, we study optimal segment caching for P2P on-demand streaming. We
first formulate the segment caching optimization (SCO) problem, and show
that it is NP-hard. We then propose a centralized heuristic to solve it,
which serves as a benchmark for other algorithms. We propose a distributed
caching algorithm termed POPCA (POPularity-based Caching Algorithm), in
which each peer adaptively and independently replaces segments to minimize
the popularity-supply discrepancy and the segment distance from peers.
POPCA also proactively advertises updated segment availability in a
scalable manner to provide near-instant segment search. Through
simulations and PlanetLab experiments, we show that POPCA achieves
near-optimal performance, and lower popularity-supply discrepancy and
segment distance as compared with random caching and sliding window
caching. Moreover, POPCA has low overhead, and as compared with
Distributed Hash Table (DHT) and biased random walk, achieves lower search
latency and higher hit rate of finding segments in the peer network in the
presence of peer churn. We also present an analytic model which closely
matches with the simulation results. This would help us understand the
dependence of various system parameters to achieve a certain hit rate.


Date:				Tuesday, 19 August 2008

Time:				10:30a.m.-12:30p.m.

Venue:				Room 3401
				Lifts 17-18

Committee Members:		Dr. Gary Chan (Supervisor)
				Dr. Jogesh Muppala (Chairperson)
				Dr. Qiong Luo


**** ALL are Welcome ****