Content and Geographical Locality in User-Generated Content Sharing Systems

International audienceUser Generated Content (UGC), such as YouTube videos, accounts for a substantial fraction of the Internet traffic. To optimize their performance, UGC services usually rely on both proactive and reactive approaches that exploit spatial and temporal locality in access patterns. Alternative types of locality are also relevant and hardly ever considered together. In this paper, we show on a large (more than 650,000 videos) YouTube dataset that content locality (induced by the related videos feature) and geographic locality, are in fact correlated. More specifically, we show how the geographic view distribution of a video can be inferred to a large extent from that of its related videos. We leverage these findings to propose a UGC storage system that proactively places videos close to the expected requests. Compared to a caching-based solution, our system decreases by 16% the number of requests served from a different country than that of the requesting user, and even in this case, the distance between the user and the server is 29% shorter on average

On the server placement problem of P2P live media streaming system

Commercial P2P media streaming systems have widely utilized servers or Content Distribution Networks (CDN) service to help alleviating the effect from high peer dynamics. While refocusing on servers becomes a MUST in large-scale commercial P2P streaming systems, it comes to the problem on how to place server nodes in best efficiency so that they can better serve the needs of peers with minimal cost. In line with this, we formulate the Server Placement (SP) problem in P2P streaming system, and propose solution schemes for the sub-problem of server selection and rate assignment. The server selection problem targets at minimizing the end-to-end user round-trip latency, and traffic transmission cost, which was finally reduced to a P-median problem and solved by Greedy Randomized Adaptive Search Procedure (GRASP). Secondly, we formulate the problem of which clients are served by which server at which rate as the rate allocation problem and optimize to minimize the total streaming cost subject to the play rate requirement. As a starting work, this paper aims to attract more researches on this challenging topic. © 2008 Springer