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: 1563742
• 负责人: Venkatesan Guruswami
• 金额: $ 40万
• 依托单位: Carnegie-Mellon University
• 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 2021-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1563742&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.

云存储系统日益成为支撑日常生活的软件服务的支柱，为大量企业提供服务并形成经济的重要支柱。鉴于这些分布式系统内的交互量巨大，在构建、维护和增强它们时会出现许多问题。其中最突出的挑战是这些庞大系统中存储的数据的可靠性、可用性、一致性、机密性和隐私性。拟议的研究预计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，以实现从故障中有效恢复，同时增强此类系统提供的整体数据可用性和隐私性。这项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，并将这些进步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展活动紧密结合，让代表性不足的少数族裔、研究生和本科生直接参与。重点是有效维护具有一系列理想品质的数据，包括简化数据编码、可访问性、更新、除了隐私之外，这项工作的主要目标包括（i）开发编码方案，其中可以从其本地邻居处以更高的修复效率重新生成故障元素，（ii）结合本地可解码性和本地可修复性的优点进入一种编码解决方案，(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) 开发能够抵御不同规模/模式故障的代码，(v) 开发利用以下优势的编码机制：现有系统的实施方面，以及（vi）开发编码方案，使用户能够以私密方式访问其数据。这项工作利用编码理论、信息论、通信以及组合和离散数学等学科的工具组合来解决这些挑战。