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首页> 外文会议>Symposium on Mass Storage Systems and Technologies >Cooperative Caching with Return on Investment
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Cooperative Caching with Return on Investment

机译：合作缓存投资回报

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摘要

Large scale consolidation of distributed systems introduces data sharing between-consumers which are not centrally managed, but may be physically adjacent. For example, shared global data sets can be jointly used by different services of the same organization, possibly running on different virtual machines in the same data center. Similarly, neighboring CDNs provide fast access to the same content from the Internet. Cooperative caching, in which data are fetched from a neighboring cache instead of from the disk or from the Internet, can significantly improve resource utilization and performance in such scenarios. However, existing cooperative caching approaches fail to address the selfish nature of cache owners and their conflicting objectives. This calls for a new storage model that explicitly considers the cost of cooperation, and provides a framework for calculating the utility each owner derives from its cache and from cooperating with others. We define such a model, and construct four representative cooperation approaches to demonstrate how(and when) cooperative caching can be successfully employed in such large scale systems. We present principal guidelines for cooperative caching derived from our experimental analysis. We show that choosing the best cooperative approach can decrease the system's I/O delay by as much as 87%, while imposing cooperation when unwarranted might increase it by as much as 92%.
机译：分布式系统介绍了数据未集中管理的，但可能是物理相邻消费者之间共享的大规模整合。例如，共享全球数据集可以通过联合同一组织的不同业务中使用，可能在同一个数据中心的不同虚拟机上运行。同样，相邻的CDN提供来自互联网的相同内容的快速访问。合作缓存，其中的数据是从附近一个高速缓存，而不是从磁盘或从互联网上获取的，可以显著改善这样的情况下的资源利用率和性能。但是，现有的协作缓存方法未能解决的缓存业主及其相互冲突的目标的自私的本性。这就需要明确考虑合作的成本，并提供了一个框架，用于计算实用程序从缓存中的每个所有者派生，并与他人合作的一个新的存储模式。我们定义这样一个模型，构建四个具有代表性的合作途径，以说明如何（何时）协作缓存可以在这样的大型系统可以成功地使用。我们目前的主要准则，从我们的实验分析得出的合作缓存。我们发现，选择最好的合作方式可以多达87％降低系统的I / O延迟，而气势合作时横加可能多达92％增加了。

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