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Scalable application-aware data freshening

机译:可扩展的应用程序感知数据刷新

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摘要

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.
机译:分布式数据库和其他网络信息系统使用副本或镜像来减少延迟并提高可用性。副本需要刷新。在松散耦合的系统中,复制站点通常负责同步其自己的副本。这涉及轮询,如果不按规定方式进行,可能会非常昂贵。我们将在已知更新频率和有限带宽的情况下探讨如何确定刷新计划的主题。这里的重点是如何使用有关每个副本中用户社区的总体兴趣的附加信息,以使副本的感知新鲜度最大化。我们针对小情况开发了模型和最佳解决方案,提出了适用于大情况的几种启发式算法,然后探讨了对象大小对刷新计划的影响。它还提供了实验证据,证明我们的算法性能很好。

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