Efficient Update Propagation by Speculating Replica Locations on Peer-to-Peer Networks

Abstract

As demand for high fidelity multimedia content has soared, content distribution has emerged as a critical application. Large multimedia files require effective content distribution services such as content distribution networks (CDNs). A recent trend in CDN development is the use of peer-to-peer (P2P) techniques to enhance scalability, fault resilience, and cost-effectiveness. Unfortunately, P2P-based content distribution poses a crucial problem in that update propagation is quite difficult to accomplish. This is because peers cannot obtain a global view of replica locations on the network. In this paper, we propose speculative update, which quickly propagates an update to all replicas in a pure P2P fashion. Each server attempts to determine the directions in which there will be replicas with high probability based on server's local state used for replica repositioning. Then, it relays update messages speculatively in those directions. Simulation results demonstrate that our mechanism propagates an update to all replicas faster than the current pure P2P-based approaches.

The P2P Model Based on the Similarity of Active Peers

“…For P2P network, reducing the time cost of the file searching and file downloading and decreasing the loading of network meanwhile is the key objective [4][5] . In order to accomplish the objective, a lot of architecture schemes for organizing the peers and the files in the P2P network are put forward [6][7][8] .…”