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Optimising Data Access with an Adaptive Geo-Replication Strategy

机译：使用自适应地理复制策略优化数据访问

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The amount of data being processed in Data Centres (DCs) keeps growing at an enormous rate so that full replication may start being impractical. One way to increase data availability can be accomplished using replication between DCs so data may be accessed locally, if possible, which allows to recover in the presence of site failures and reduce access costs. This means that replicating the data only in some of the DCs is becoming more critical to reduce the costs of keeping the data consistent or eventually consistent and still maintaining a high availability (scalability) and low access costs. The data locations overall the DCs must be determined dynamically giving the changing patterns of read and write requests for the data to be replicated. Given that the problem of finding an optimal replication schema in a general network has been shown to be NP-complete for the static case, it is unlikely to be able to generate a general algorithm to find efficient solutions to the dynamic problem. An adaptive bio-inspired replication strategy is presented here, which is completely decentralised, adaptive, inspired on the Ant Colony algorithm, and event-driven. Also, the replication protocol is independent of the strategy implemented but it is guided by the strategy.
机译：数据中心（DC）中正在处理的数据量一直以惊人的速度增长，因此完全复制可能开始变得不切实际。增加数据可用性的一种方法可以使用DC之间的复制来实现，因此，如果可能，可以在本地访问数据，这可以在出现站点故障的情况下进行恢复并降低访问成本。这意味着仅在某些DC中复制数据对于降低保持数据一致或最终一致以及仍然保持高可用性（可扩展性）和低访问成本的成本变得越来越重要。必须动态确定整个DC的数据位置，以给出要复制的数据的读写请求的变化模式。考虑到在静态情况下发现在通用网络中找到最佳复制方案的问题已被证明是NP完全的，因此不太可能能够生成通用算法来找到针对动态问题的有效解决方案。此处介绍了一种自适应的，受生物启发的复制策略，该策略是完全分散的，自适应的，受蚁群算法启发和事件驱动的。同样，复制协议独立于所实施的策略，但受策略指导。

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