SHF: Small: ASF: An Adaptive Scaling Framework for High Scalability of XOR-Based RAID Systems

SHF：小型：ASF：基于 XOR 的 RAID 系统的高可扩展性的自适应扩展框架

• 批准号: 1320349
• 负责人: Xubin He
• 金额: $ 31.8万
• 依托单位: Virginia Commonwealth University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-02-01 至 2016-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1320349&HistoricalAwards=false
• 关键词: SHF; Small; ASF; Adaptive; Scaling

Explosive growth in data volume, heterogeneity, and complexity imposes unprecedented challenges in data analysis and organization in data centers. RAID particularly XOR-based RAID plays an important role to provide both reliability and high performance storage services for these data centers. However, they suffer from problems on the scalability issue due to multi-folded factors, including: heterogeneous RAID layouts and various erasure codes, high overhead of existing scaling process to significantly downgrade the storage performance, and lack of bidirectional scaling support. The objective of this project is to address the scalability challenge for storage systems in large data centers. This project designs novel techniques to exploit XOR-based parity codes to achieve efficient scaling, develops a series of scalable XOR-based erasure codes to bridge the relations among heterogeneous RAID forms for interoperability, and integrates various erasure codes in a framework to provide a unified user interface for RAID scaling. The research will facilitate the storage systems to effectively tackle the scalability challenge in large data centers. It cohesively investigates how to utilize and integrate proper RAID scaling technologies to improve the scalability of storage systems. This project will yield fundamental contributions to research on efficient big data management in high-performance data centers, and greatly contribute to enabling high-performance computing systems to stay on track of their historic scaling, and hence benefit numerous real-life data-intensive applications such as biology, chemistry, earth science, health care, and so on.

数据量、异构性和复杂性的爆炸式增长给数据中心的数据分析和组织带来了前所未有的挑战。 RAID（尤其是基于XOR的RAID）在为这些数据中心提供可靠性和高性能存储服务方面发挥着重要作用。然而，由于多重因素，它们在可扩展性问题上存在问题，包括：异构RAID布局和各种擦除码，现有扩展过程的高开销显着降低存储性能，以及缺乏双向扩展支持。该项目的目标是解决大型数据中心存储系统的可扩展性挑战。本计画设计新颖的技术，利用异或的奇偶校验码来达成有效的扩充，发展一系列可扩充的异或擦除码来桥接异构RAID形式之间的关系，以达到互操作性，并整合各种擦除码于一个架构中，以提供一个统一的RAID扩充使用者介面。该研究将有助于存储系统有效地应对大型数据中心的可扩展性挑战。它集中研究如何利用和集成适当的RAID扩展技术，以提高存储系统的可扩展性。该项目将为高性能数据中心的高效大数据管理研究做出基础性贡献，并为使高性能计算系统保持其历史规模做出巨大贡献，从而使许多现实生活中的数据密集型应用受益，如生物学，化学，地球科学，医疗保健等。