Scalable application-aware data freshening

Distributed databases and other networked information systems use copies or mirrors to reduce latency and to increase availability. Copies need to be refreshed. In a loosely coupled system, the copy sites are typically responsible for synchronizing their own copies. This involves polling and can be quite expensive if not done in a disciplined way. This paper explores the topic of how to determine a refresh schedule given knowledge of the update frequencies and limited bandwidth. The emphasis here is on how to use additional information about the aggregate interest of the user community in each of the copies in order to maximize the perceived freshness of the copies. This paper develops a model and an optimal solution for small cases, presents several heuristic algorithms that work for large cases, then explores the impact of object size on the refresh schedule. It also presents experimental evidence that our algorithms perform quite well.