pCDN

Peer-assisted Content Distribution Network

This project employs the peer-to-peer (P2P) computing paradigm in designing large-scale content distribution systems. The P2P paradigm provides: (i) improved scalability by aggregating resource contributions from peers (end user machines) and reducing the reliance on centralized servers, (ii) reduced cost by utilizing already-deployed resources and eliminating the need for expensive infrastructure, and (iii) rapid deployability by performing all processing at the end systems.

Major content distribution networks, such as Akamai, consider the P2P paradigm as a real threat for their content distribution business. This is because the P2P paradigm may achieve similar services with a fraction of the cost. However, there are several research challenges that need to be addressed to enable the P2P paradigm to achieve this potential. In this research, we tackle these research challenges. Our goal is to develop a fully functional and reliable P2P content distribution system, which we call pCDN. Several steps have been made towards that goal. In fact, we already have a beta version of pCDN 1.0.

pCDN will provide high-quality multimedia content, support heterogeneous clients, impose minimal load on the expensive inter-ISP links, provide on-demand as well as live streaming services, ensure data integrity, implement digital rights management, among other features. All features are based on novel algorithms developed by our group. An overview of pCDN and its features can be found in this White Paper. The white paper also summarizes the main differences between pCDN and common P2P file-sharing systems such as BitTorrent and Gnutella.

pCDN is developed in partnership with the Canadian Broadcasting Corporation (CBC). CBC is the largest Internet content provider in Canada with millions of online users consuming a huge amount of bandwidth, which costs CBC millions of dollars each year. The objective of pCDN is to offset some of these costs while providing better streaming services to clients. pCDN 1.0 is currently in the final testing phases by CBC to be released to the public. Testing is being performed on small Internet streaming services, and the system will gradually evolve to larger-scale important services.

Funding for the pCDN project is provided by a research grant from CRD and RTI grants from NSERC, and a few MITACS Research Internships. We appreciate their support.

People

Mohamed Hefeeda

François Conway, (CBC, Senior Director, Technology, Strategy and Planning)

Bernard Jules (CBC, Senior Project Manager, Internet and New Media Technology)

Ahmed Hamza (PhD student)

Patrick Morin (CBC, Technical Support, Internet and New Media Technology)

Patrice Charbonneau (CBC, Technical Support, Internet and New Media Technology)

ChengHsin Hsu (PhD student, Graduated Fall 2009)

Kianoosh Mokhtarian (MSc Student, Graduated Fall 2009)

Vikas Kumar, Graduate (Research Assistant/Software Engineer, May -- July 2008) Progress Report

Nitin Chiluka (Research Assistant/Software Engineer, December 2007 -- May 2008)

Pouya Alagheband (NSERC Undergraduate Research Awards, Summer 2007)

Nicolas Gomez (NSERC Undergraduate Research Awards, Summer 2007)

Osama Saleh (MSc Student, Graduated Fall 2006)

On-going Research Problems

Systems Issues (Login Required)

ISP-Friendly Peer Matching (Login Required)

Comprehensive NAT Traversal (Login Required)

Digital Rights Management (Login Required)

Publications

C. Hsu, N. Chiluka, and M. Hefeeda, ISP-Friendly Peer Matching Algorithms, ACM SIGCOMM'08 Poster, Seattle, WA, August 2008.

Hsu and M. Hefeeda, On the Accuracy and Complexity of Rate-Distortion Models for FGS-encoded Video Sequences, ACM Transactions on Multimedia Computing, Communications, and Applications, 4(2), Article 15, 22 Pages, May 2008.

C. Hsu and M. Hefeeda, Partitioning of Multiple Fine-Grained Scalable Video Sequences Concurrently Streamed to Heterogeneous Clients, IEEE Transactions on Multimedia, 10(3), pp. 457--469, April 2008.

M. Hefeeda and C. Hsu, Rate-Distortion Optimized Streaming of Fine-Grained Scalable Video Sequences, ACM Transactions on Multimedia Computing, Communications, and Applications, 4(1), Article 2, 28 Pages, January 2008.

C. Hsu and M. Hefeeda, Optimal Coding of Multi-layer and Multi-version Video Streams, IEEE Transactions on Multimedia, 10(1), pp. 121--131, January 2008.

B. Jules and M. Hefeeda, pCDN: Peer-assisted Content Distribution Network, CBC/Radio-Canada Technology Review Magazine, Issue 4, pp. 1--14, July 2007. (Invited, also published in French).

Y. Tu, J. Sun, M. Hefeeda, Y. Xia, S. Prabhakar, An Analytical Study of Peer-to-Peer Media Streaming Systems, ACM Transactions on Multimedia Computing, Communications, and Applications, 1(4), pp. 354--376, November 2005.

M. Hefeeda, A. Habib, D. Xu, B. Bhargava, B. Botev, CollectCast: A Peer-to-Peer Service for Media Streaming, ACM/Springer Multimedia Systems Journal, 11(1), pp. 68--81, November 2005.

C. Hsu and M. Hefeeda, Structuring Multi-Layer Scalable Streams to Maximize Client-Perceived Quality, In Proc. of IEEE International Workshop on Quality of Service (IWQoS'07), pp. 182--187, Chicago, IL, June 2007.

C. Hsu and M. Hefeeda, Optimal Partitioning of Fine-Grained Scalable Video Streams, In Proc. of ACM International Workshop on Network and Operating Systems Support for Digital Audio & Video (NOSSDAV'07), pp. 63--68, Urbana-Champion, IL, June 2007.