CIF: Small: Collaborative Research: A Software Toolbox for Computing and Exploring the Fundamental Limits of Information Systems

CIF：小型：协作研究：用于计算和探索信息系统基本限制的软件工具箱

• 批准号: 1816546
• 负责人: Chao Tian
• 金额: $ 31.92万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-10-01 至 2021-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1816546&HistoricalAwards=false
• 关键词: CIF; Small; Collaborative; Research; Software

This project aims to build an open-source software toolbox under the GNU-GPL license to facilitate the investigation of information systems (e.g., data storage systems, streaming data structures, and content delivery systems) using information theoretical methods, more precisely, to facilitate the derivation of outer bounds and identifying novel code constructions. By building modern software tools which are able to take advantage of the advance in computer hardware and software, this effort can help the community more efficiently incorporate computational intelligence into information theoretic research. The main theoretical foundation for the approach is the entropy linear programming framework, and techniques based on symmetry and implication relations that can reduce the complexity of such programs. The core components of the toolbox are various software tools to perform information theoretic analysis and exploration of information systems in a computational manner. The completion of such a toolbox can enable researchers to build, with minimal programming efforts, computer software which takes in a description of the information system of interest, processes the relation among its components, formulates an appropriate optimization problem, and invokes a computational optimization solver to produce meaningful results regarding the fundamental limits and code constructions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目旨在在 GNU-GPL 许可下构建一个开源软件工具箱，以促进使用信息论方法对信息系统（例如数据存储系统、流数据结构和内容交付系统）进行研究，更准确地说，促进外界的推导和识别新颖的代码结构。 通过构建能够利用计算机硬件和软件进步的现代软件工具，这项工作可以帮助社区更有效地将计算智能纳入信息论研究。该方法的主要理论基础是熵线性规划框架，以及基于对称性和蕴涵关系的技术，可以降低此类程序的复杂性。该工具箱的核心组件是各种软件工具，用于以计算方式对信息系统进行信息论分析和探索。完成这样一个工具箱可以使研究人员以最少的编程工作来构建计算机软件，该软件接受感兴趣的信息系统的描述，处理其组件之间的关系，制定适当的优化问题，并调用计算优化求解器来产生有关基本限制和代码构造的有意义的结果。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力评估进行评估，被认为值得支持。 优点和更广泛的影响审查标准。

项目成果

Weakly Secure Symmetric Multilevel Diversity Coding

• DOI: 10.1109/tit.2020.3004482
• 发表时间: 2020-06
• 期刊: IEEE Transactions on Information Theory
• 影响因子: 2.5
• 作者: Tao Guo;C. Tian;Tie Liu;R. Yeung

New Results on the Storage-Retrieval Tradeoff in Private Information Retrieval Systems

• DOI: 10.1109/jsait.2021.3053217
• 发表时间: 2020-08
• 期刊: IEEE Journal on Selected Areas in Information Theory
• 作者: Tao Guo;Ruida Zhou;C. Tian

Weakly Private Information Retrieval Under the Maximal Leakage Metric

最大泄漏指标下的弱隐私信息检索

• DOI: 10.1109/isit44484.2020.9174334
• 发表时间: 2020
• 期刊: 2020 IEEE International Symposium on Information Theory (ISIT
• 作者: Zhou, Ruida;Guo, Tao;Tian, Chao
• 通讯作者: Tian, Chao

A New Approach to Compute Information Theoretic Outer Bounds and Its Application to Regenerating Codes

计算信息论外界的新方法及其在重新生成代码中的应用

• DOI: 10.1109/isit50566.2022.9834469
• 发表时间: 2022
• 期刊: 2022 IEEE International Symposium on Information Theory (ISIT
• 作者: Chen, Wenjing;Tian, Chao
• 通讯作者: Tian, Chao

A Shannon-Theoretic Approach to the Storage–Retrieval Trade-Off in PIR Systems

PIR 系统中存储与检索权衡的香农理论方法

• DOI: 10.3390/info14010044
• 发表时间: 2023
• 期刊: Information
• 影响因子: 3.1
• 作者: Tian, Chao;Sun, Hua;Chen, Jun
• 通讯作者: Chen, Jun