CIF: NeTS: Medium: Collaborative Research: Unifying Data Synchronization

CIF：NetTS：媒介：协作研究：统一数据同步

• 批准号: 1563710
• 负责人: Michael Mitzenmacher
• 金额: $ 40万
• 依托单位: Harvard 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: 2016-07-01 至 2022-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1563710&HistoricalAwards=false
• 关键词: CIF; NeTS; Medium; Collaborative; Research

This project addresses the technical means of maintaining and sharing the huge amounts of diverse data that are being generated from the computing devices that increasingly envelop everyday lives, specifically by improving synchronization technology. The goal is to synthesize various approaches that have been developed, often in an ad hoc manner and in various fields, into a general, holistic solution that includes benefits from new analyses and solutions. The approach is fundamental in nature, and its effectiveness shows promise for impact on a diverse set of technologies, including mobile and cloud computing, digital currency, security, and biological sequencing. Part of the work involves outreach to younger students, such as initial efforts at setting up a novel computing-based summer program for high school students.The project focuses on four research thrusts. The first involves an analysis, comparison, and improvement (where possible) of core point-to-point synchronization primitives from the existing literature. The second thrust generalizes these primitives to higher-dimensional data, such as files, images, video, databases, and graphs. The third research thrust involves developing approaches for synchronizing data from many synchronizing parties communicating through a variety of channels. Finally, the project aims to implement a general data synchronization engine based on the research results, together with an evaluation of various applications.

该项目探讨了维护和共享从越来越多地包围日常生活的计算设备生成的大量不同数据的技术手段，特别是通过改善同步技术。 目的是将经常以临时方式和各个领域开发的各种方法综合为一种一般的整体解决方案，其中包括新的分析和解决方案。 这种方法本质上是基本的，其有效性显示出对各种技术的影响，包括移动和云计算，数字货币，安全和生物测序的有望。 这项工作的一部分涉及向年轻学生推广，例如为高中生建立基于计算机的新型夏季计划而进行的最初努力。该项目重点介绍了四个研究推力。 第一个涉及对现有文献的核心点对点同步基原始人的分析，比较和改进（如果可能的情况）。 第二个推力将这些原语概括为更高维数据，例如文件，图像，视频，数据库和图形。 第三项研究推力涉及开发通过各种渠道通信的许多同步各方的数据同步数据的方法。 最后，该项目旨在根据研究结果实施一般数据同步引擎，并对各种应用程序进行评估。

项目成果

Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix

• 发表时间: 2021-06
• 作者: Maximilian Lam;Gu-Yeon Wei;D. Brooks;V. Reddi;M. Mitzenmacher

Queues with Small Advice

带有小建议的队列

• 发表时间: 2021
• 期刊: SIAM Conference on Applied and Computational Discrete Algorithms
• 作者: Mitzenmacher, Michael