Cooperative caching with return on investment
Cooperative caching with return on investment
复制标题
具有投资回报的协作缓存
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
A. Schuster
中科院分区：
文献类型：
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作者：
Gala Yadgar;M. Factor;A. Schuster
分布式系统的大规模整合引入了消费者之间的数据共享，这些消费者不是集中管理的，但可能在物理上相邻。例如，共享的全局数据集可以由同一组织的不同服务联合使用，可能在同一数据中心的不同虚拟机上运行。类似地，相邻CDN提供对来自互联网的相同内容的快速访问。在协作缓存中，数据从相邻的缓存中获取，而不是从磁盘或互联网中获取，可以显着提高资源利用率和性能。然而，现有的合作缓存方法无法解决缓存所有者的自私性质和他们的目标冲突。这需要一个新的存储模型，明确考虑合作的成本，并提供了一个框架，用于计算每个所有者从其缓存和与他人合作中获得的效用。我们定义了这样一个模型，并构建了四个有代表性的合作方法来演示如何（以及何时）合作缓存可以成功地在这样的大规模系统。我们提出的合作缓存来自我们的实验分析的主要指导方针。我们发现，选择最佳的合作方法可以减少系统的I/O延迟高达87%，而实施合作时，不必要的可能会增加高达92%。
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%.