CIF: Small: Collaborative Research:Synchronization and Deduplication of Distributed Coded Data: Fundamental Limits and Algorithms

CIF：小型：协作研究：分布式编码数据的同步和重复数据删除：基本限制和算法

• 批准号: 1526875
• 负责人: Olgica Milenkovic
• 金额: $ 15万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-01 至 2021-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1526875&HistoricalAwards=false
• 关键词: CIF; Small; Collaborative; Research; Synchronization

Part 1: Coding for distributed storage systems has garnered significant attention in the past few years due to the rapid development of information technologies and the emergence of Big Data formats that need to be stored and disseminated across large-scale networks. As typical distributed systems need to ensure low-latency data access and store a large number of files over a set of nodes connected through a communication network, it is imperative to develop new distributed coding schemes that protect the systems from undesired component failures. The two key functionalities of codes used in distributed systems, namely the reconstruction of files via access to a subset of the nodes and repair of failed nodes, need to be retained when the files are accessed and processed by the users via symbol/block insertion, deletion, or substitution edits. Deletions frequently arise due to system-level data deduplication: when parts of files are deduplicated or edited, the changes in the information content need to be communicated to the redundant storage nodes with minimum communication cost. Current solutions for synchronizing data that underwent edits assume that data is uncoded and they do not fully exploit the distributed nature of information. Furthermore, they mostly ignore the presence of deduplication protocols. This makes distributed storage architectures inefficient in terms of storage, user access times, and error protection. Hence, the goals of the proposed research program are to develop a new set of protocols and coding schemes that will support a new generation of versatile and updatable coded distributed storage systems. Part 2: Building on the preliminary work of the investigators, this proposal aims to set the foundations of the new field of coded synchronization and deduplication, with the goal of deriving fundamental performance limits, developing efficient algorithmic solutions for the two families of problems, and constructing new distributed storage codes that enable synchronization of coded data and coded deduplication. In particular, the proposal addresses the following comprehensive issues: 1) Characterizing the communication rate limits of known and new (un)coded synchronization schemes, trade-offs between deduplication and data repair performance for different structured or encoded data formats and different types of communication channels.2) Introducing and analyzing the communication rate-distortion (CRD) function for approximate synchronization and deduplication of structured/encoded data, with a special focus on delay-sensitive applications.3) Developing dynamically updatable synchronization and deduplication algorithms cognizant of the network topology and of different prioritization needs of the users, as encountered in image and video data coding.

第1部分：由于信息技术的快速发展以及需要在大型网络中存储和传播的大数据格式的出现，在过去几年中，编码分布式存储系统在过去几年中引起了极大的关注。由于典型的分布式系统需要确保低延迟数据访问并在通过通信网络连接的一组节点上存储大量文件，因此必须开发保护系统免受不受欢迎组件故障的新分布式编码方案。分布式系统中使用的代码的两个关键功能，即通过访问节点的子集的重建文件和失败节点的维修，当用户通过符号/块插入，删除或替换编辑访问文件和处理时，需要保留文件。由于系统级数据的重复数据删除，经常出现删除：当文件的部分重复编辑或编辑时，信息内容的更改需要将其传达给具有最低通信成本的冗余存储节点。当前用于同步数据的解决方案假定数据未编码，并且没有完全利用信息的分布性质。此外，它们主要忽略了重复数据删除协议的存在。这使得分布式存储架构在存储，用户访问时间和错误保护方面效率低下。因此，拟议的研究计划的目标是制定一套新的协议和编码方案，这些方案将支持新一代的多功能和可更新的编码分布式存储系统。第2部分：基于调查人员的初步工作，该提案旨在为编码同步和重复数据删除的新领域设定基础，目的是得出基本的性能限制，为问题的两个家族开发有效的算法解决方案，并为两个问题家族开发有效的算法解决方案，并为构建编码数据和编码图的新分布式存储代码，并构建新的分布式存储代码。特别是，该提案解决了以下全面问题：1）表征已知和新的（未编码的）编码同步方案的沟通速率限制，针对不同结构化或编码的数据格式的重复数据修复和数据修复性能之间的权衡以及不同类型的通信通道。2）介绍和分析了通信速率（CRD）的构建和DEDARITY（CRD）的构建和分析，以构建近似构建和DESTIADE（CRD）效应，并在近似构建范围内进行同步的构建范围。 3）如图像和视频数据编码中所遇到的那样，开发动态更新的同步和重复数据删除算法，以及用户的不同优先级需求。