Path-aware peer-assisted web content delivery against network failures
Popularly used to distribute a variety of multimedia contents in today's Internet, HTTP-based web content delivery still suffers from failures occurring both in the network and at the servers. Limited by the deployment of edge servers, it is hard for a CDN to successfully deliver contents to all users under these network failures. Different from conventional peer-assisted approaches for web content delivery, which mainly focus on alleviating the CDN servers' bandwidth load, we study how to use a browser-based peer-assisted scheme to resolve content delivery failures. Based on large-scale measurement studies on how users access and view webpages, we observe the challenges (e.g., peers stay on a webpage extremely short) that cannot be directly solved by conventional P2P strategies, and some important webpage viewing patterns. Due to these unique characteristics, WebRTC peers give us a novel way to deliver web content, coming with the problem of how to utilize the dynamic resources efficiently. We formulate the peer selection as an optimization problem, and design a heuristic algorithm based on the measurement insights to strategically select the most appropriate peer. Our prototype implementation on Tencent QZone and simulation experiments further demonstrate the effectiveness of our design: compared with non-peer-assisted strategy and random peer selection strategy, our design significantly improves the successful relay ratio of web contents under network failures, e.g., our design achieves a successful content download ratio of 60% even when users located in a particular region are not able to connect to the CDN servers.