A general framework for searching in distributed data repositories

This paper proposes a general framework for searching large distributed repositories. Examples of such repositories include sites with music/video content, distributed digital libraries, distributed caching systems, etc. The framework is based on the concept of neighborhood; each client keeps a list of the most beneficial sites according to past experience, which are visited first when the client searches for some particular content. Exploration methods continuously update the neighborhoods in order to follow changes in access patterns. Depending on the application, several variations of search and exploration processes are proposed. Experimental evaluation demonstrates the benefits of the framework in different scenarios.