论文标题
零散的ARE：大对象的动态存储
Fragmented ARES: Dynamic Storage for Large Objects
论文作者
论文摘要
数据可用性是通过数据复制使分布式存储系统中最重要的功能之一。如今，数据的生成迅速，开发高效，可扩展和可靠的存储系统的目标已成为高性能计算的主要挑战之一。在这项工作中，我们开发了一种适用于处理大型对象的动态，健壮且非常一致的分布式存储实现（例如文件）。我们通过集成一种自适应，可重构的，可重新配置的原子存储框架，称为ARES，用分布式文件系统（称为COBFS），该框架依赖于块碎片技术来处理大型对象。随着ARES的添加，我们还启用了擦除编码算法的使用来进一步分类我们的数据并有可能提高复制服务器和操作延迟的存储效率。为了使我们的结果实用，我们对Emulab和AWS EC2测试台进行了深入的实验评估，说明了我们方法的好处以及其他有趣的折衷。
Data availability is one of the most important features in distributed storage systems, made possible by data replication. Nowadays data are generated rapidly and the goal to develop efficient, scalable and reliable storage systems has become one of the major challenges for high performance computing. In this work, we develop a dynamic, robust and strongly consistent distributed storage implementation suitable for handling large objects (such as files). We do so by integrating an Adaptive, Reconfigurable, Atomic Storage framework, called ARES, with a distributed file system, called COBFS, which relies on a block fragmentation technique to handle large objects. With the addition of ARES, we also enable the use of an erasure-coded algorithm to further split our data and to potentially improve storage efficiency at the replica servers and operation latency. To put the practicality of our outcomes at test, we conduct an in-depth experimental evaluation on the Emulab and AWS EC2 testbeds, illustrating the benefits of our approaches, as well as other interesting tradeoffs.
