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. We explore 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. We develop 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.

We describe an index hint mechanism for on-demand data broadcast environments, which enables mobile clients to spend less power consumption by reducing their tuning times. We propose approaches to estimate the data broadcast times for a set of data items so that the index mechanism can be applied to on-demand data broadcasts. We also propose how to organize and apply index hints using the estimated broadcast times of data items. Our simulation results show that the proposed index hint mechanism effectively reduces the tuning times of mobile clients, thereby reducing their power consumption.

No abstract available.