CSR: SHF: SMALL: Efficient, Low-Latency Networked Storage

从键值存储到分布式文件系统再到分布式数据库，网络存储支撑着现代Internet服务。网络存储允许程序员分离逻辑和数据，支持高吞吐量向外扩展，并利用日益快速的数据中心网络。然而，在大数据时代，网络存储面临着新的挑战：每个用户请求访问的数据量快速增长；超过处理器速度和DRAM容量。用户感知到的响应时间越来越多地由最慢的存储访问主导，即第99个百分位数的尾部。网络存储的响应时间长是出了名的。我们正在开发网络存储系统，这种系统1)速度快，2)性价比高。一个关键的方法是理解并有选择地使用复制来实现可预测性（或克隆）。在这种方法中，客户端对独立的硬件资源发出冗余存储访问。第一个响应提供结果。可预测性的复制减少了客户感知的可变性，从而导致始终快速的响应时间。我们的实现在规模上尤其具有成本效益。为了降低成本，我们研究了响应时间慢的根本原因，通过关注常见原因来节省资源。我们也交易质量——例如：，搜索引擎结果略有下降——在适当的时候降低硬件成本。为了产生更广泛的影响，PI将努力将技术转让给国家和地方公司。

From key-value stores to distributed file systems to distributed databases, networked storage underpins modern Internet services. Networked storage allows programmers to separate logic and data, enables high throughput scale out, and takes advantage of increasingly fast datacenter networks. However, in the big data era, networked storage faces a new challenge: The amount of data accessed per user request is growing rapidly; outpacing processor speeds and DRAM capacity. Increasingly, user-perceived response times are dominated by the slowest storage accesses, i.e., the 99th percentile tails. Networked storage is notorious for fat tailed response times.We are developing networked storage systems that are 1) always fast and 2) cost efficient. A key approach is to understand and selectively use replication for predictability (or cloning). In this approach, clients issue redundant storage accesses against independent hardware resources. The first to respond provides the result. Replication for predictability reduces client-perceived variability, leading to always fast response times. Our implementations are especially cost effective at scale. To lower costs, we study the root causes of slow response times, saving resources by focusing on common causes. We also trade quality---e.g., slightly degraded search engine results--- for lower hardware costs when appropriate. For broader impact, the PI will work to transfer the technology to national and local companies.