Best-effort cache synchronization with source cooperation

Abstract

In environments where exact synchronization between source data objects and cached copies is not achievable due to bandwidth or other resource constraints, stale (out-of-date) copies are permitted. It is desirable to minimize the overall divergence between source objects and cached copies by selectively refreshing modified objects. We call the online process of selecting which objects to refresh in order to minimize divergence best-effort synchronization. In most approaches to best-effort synchronization, the cache coordinates the process and selects objects to refresh. In this paper, we propose a best-effort synchronization scheduling policy that exploits cooperation between data sources and the cache. We also propose an implementation of our policy that incurs low communication overhead even in environments with very large numbers of sources. Our algorithm is adaptive to wide fluctuations in available resources and data update rates. Through experimental simulation over synthetic and real-world data, we demonstrate the effectiveness of our algorithm, and we quantify the significant decrease in divergence achievable with source cooperation.