The Community for Technology Leaders
Green Image
<p><b>Abstract</b>—Caches have been used extensively to store the most popular/recent requested data to improve the user latency and reduce the network load. Recently, a more systematic approach to caching has been developed within the framework of Content Delivery Networks (CDN). A CDN is the network of caches, where the caches are geographically distributed and serve user requests on behalf of the subscriber Web sites. Users receive the requested information from the caching servers, which are closer to the users and usually much less loaded than the origin server. The objective is to minimize the user latency by intelligently distributing the content and serving the user requests from the most efficient sites. We realistically model the agents in a CDN with selfish self-maximizing behaviors and define the problem as a noncooperative game. We separate the distribution and routing subproblems and use games to solve each. We show that the subproblems have equilibrium solutions and, if the equilibrium of a subproblem is unique, we achieve the global optimum for that subproblem. We also determine that a unique equilibrium is reached if the content providers are not willing to pay high amounts and the cache sizes are sufficiently small. We noticed that the global system optimum requires the content providers to pay very high amounts, which in practice may prohibit the applicability of the distributed method. Thus, we consider an investment strategy for the content providers, which maximizes the publishers' net benefits and leads to a near-optimum system solution. We also show that the joint distribution and routing game has an equilibrium and demonstrate its performance by numerical examples.</p>
Information storage, dissemination, routing, market model, resource allocation, game theory.

?. Er?etin and L. Tassiulas, "Market-Based Resource Allocation for Content Delivery in the Internet," in IEEE Transactions on Computers, vol. 52, no. , pp. 1573-1585, 2003.
81 ms
(Ver 3.3 (11022016))