CIF: Medium: Collaborative Research: Frontiers in coding for cloud storage systems

CIF：媒介：协作研究：云存储系统编码前沿

• 批准号: 1564167
• 负责人: Sriram Vishwanath
• 金额: $ 40万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-03-01 至 2020-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1564167&HistoricalAwards=false
• 关键词: CIF; Medium; Collaborative; Research; Frontiers

Cloud storage systems increasingly form the backbone of software services that underwrite everyday lives, serving a large array of businesses and forming an essential pillar of the economy. Given the sheer volume of interactions within these distributed systems, there arise a multitude of issues in building, maintaining and enhancing them. The most salient of these challenges are in the reliability, availability, consistency, confidentiality and privacy of data stored in these vast systems. The proposed research is expected to have a significant impact on the manner in which cloud storage systems are designed and deployed. In these systems, storage node failures can have a significant impact on the efficiency of the overall system. This project enhances fault tolerant mechanisms to enable efficient recovery from failures, while augmenting the overall data availability and privacy offered by such systems. The research effort will advance the science of cloud computing by developing a new family of algorithms for distributed storage , and connect the advances to the significant industry needs in this topic. The research agenda will also be tightly integrated with education and outreach activities with direct involvement of underrepresented minorities, graduate, and undergraduate students.Focusing on efficient maintenance of data with a range of desirable qualities, including mechanisms that ease data encoding, accessibility, updates, as well as privacy, the main objectives of this effort include (i) to develop coding schemes where a failed element can be regenerated with higher repair efficiencies from its local neighbors, (ii) to bring together the advantages of both local decodability and local repairability into one coding solution, (iii) to design mechanisms that provide low cost data updates in addition to efficient repair, (iv) to develop codes that can be resilient against failures with different scales/modalities, (v) to develop coding mechanisms taking advantage of implementation aspects of existing systems, and (vi) to develop coding schemes that enable users to access their data in a private manner. This effort addresses these challenges using a combination of tools from disciplines spanning coding theory, information theory, communications, as well as combinatorial and discrete mathematics.

云存储系统越来越多地成为软件服务的支柱，这些软件服务为日常生活提供保障，为大量企业提供服务，并成为经济的重要支柱。由于这些分布式系统中的交互量巨大，因此在构建、维护和增强它们时会出现许多问题。这些挑战中最突出的是存储在这些庞大系统中的数据的可靠性、可用性、一致性、机密性和隐私性。预计拟议的研究将对云存储系统的设计和部署方式产生重大影响。在这些系统中，存储节点故障会对整个系统的效率产生重大影响。该项目增强了容错机制，使有效的故障恢复，同时增加了整体数据的可用性和隐私提供了这样的系统。研究工作将通过开发一系列新的分布式存储算法来推进云计算科学，并将这些进展与该主题的重要行业需求联系起来。研究议程还将与教育和外联活动紧密结合，直接参与人数不足的少数民族，研究生和本科生。重点是有效维护具有一系列理想质量的数据，包括简化数据编码，可访问性，更新以及隐私的机制，这项工作的主要目标包括（i）开发编码方案，其中故障元件可以从其本地邻居以更高的修复效率再生，（ii）将局部可解码性和局部可修复性两者的优点结合到一个编码解决方案中，（iii）设计除了有效修复之外还提供低成本数据更新的机制，（iv）开发可以对具有不同尺度/模态的故障具有弹性的编码，（v）利用现有系统的实施方面开发编码机制，以及（vi）开发编码方案，使用户能够以私人方式访问其数据。这项工作解决了这些挑战，使用跨学科的工具组合编码理论，信息论，通信，以及组合和离散数学。