Towards Network-Failure-Tolerant Web Content Delivery: A Path-Aware Peer-Assisted Approach

Abstract

Popularly used to distribute a variety of multimedia content items in today's Internet, HTTP-based web content delivery still suffers from various content delivery failures, including server failures [1], network failures [2] and routing failures [3]. Hindered by the expensive deployment cost, the conventional CDN can not deploy as many edge servers as possible to successfully deliver content items to all users under these delivery failures. In this paper, we propose a joint CDN and peer-assisted web content delivery framework to address the delivery failure problem. 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, namely WebRTC, to resolve content delivery failures. To this end, we carry out large-scale measurement studies on how users access and view webpages. Our measurement results demonstrate the challenges (e.g., peers stay on a webpage extremely short) that can not be directly solved by conventional P2P strategies, and some important webpage viewing patterns (e.g., predictability of users' webpage viewing time). Due to these unique characteristics, WebRTC peers open up new possibilities for helping the web content delivery, coming with the problem of how to utilize the dynamic resources efficiently. We formulate the peer selection that is the critical strategy in our framework, as an optimization problem, and design a heuristic algorithm based on the mea- surement insights to solve it. Our simulation experiments driven by the traces from Tencent QZone, one of the most popular social service platforms in China, 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 content items under network failures, e.g., our design improves the content download ratio up to 60% even when users located in a particular region (e.g., city) where none can connect to the regional CDN server.