Demand for using cloud object storage has been increasing in order to efficiently manage a large number of binary large objects (BLOBs), including videos, photos and documents. Although many companies and institutions are currently trying to utilize public cloud object storage services such as AWS Simple Storage Service (S3), most of existing encoding systems for safe storage of data have not been optimized for current cloud object storage architecture. In this article, we propose a novel dynamic extreme erasure encoding algorithm, namely DexEncoding aiming to maximize the utility of clients where the encoding locations in the cloud storage architecture are dynamically optimized between gateway and storage servers with respect to the time-varying cloud environment. Here, the utility captures the satisfaction of clients for the speed of data storage and fairness among clients. DexEncoding efficiently resolves resource bottlenecks by adapting to the dynamic network, processing and storage resource availability and storage request. Real measurement-driven simulations demonstrate that the proposed DexEncoding algorithm drastically outperforms that applied in the state-of-the-art object storage systems in a perspective of clients’ satisfaction.

中文翻译：

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云存储系统中存储加速的动态多资源优化


为了有效管理大量二进制大型对象 (BLOB)，包括视频、照片和文档，对使用云对象存储的需求不断增加。尽管目前许多公司和机构正在尝试利用AWS简单存储服务（S3）等公共云对象存储服务，但大多数现有的用于安全存储数据的编码系统尚未针对当前的云对象存储架构进行优化。在本文中，我们提出了一种新颖的动态极端擦除编码算法，即DexEncoding，旨在最大化客户端的效用，其中云存储架构中的编码位置在网关和存储服务器之间针对时变的云环境进行动态优化。在这里，该实用程序捕获客户对数据存储速度和客户之间公平性的满意度。 DexEncoding通过适应动态网络、处理和存储资源可用性以及存储请求，有效解决资源瓶颈。真实的测量驱动模拟表明，从客户满意度的角度来看，所提出的 DexEncoding 算法远远优于最先进的对象存储系统中应用的算法。