CIF: Small: Network Information Theory Meets Network Optimization: Optimal Linear Network Coding for Packet Erasure Networks

CIF：小型：网络信息理论与网络优化的结合：数据包擦除网络的最优线性网络编码

基本信息

批准号：
1422997
负责人：
Chih-Chun Wang
金额：
$ 49.31万
依托单位：
Purdue University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2014
资助国家：
美国
起止时间：
2014-11-01 至 2019-10-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1422997&HistoricalAwards=false
关键词：
CIF Small Network Information Theory

项目摘要

The development of high-rate, more efficient, and ubiquitous communication networks is a critical backbone infrastructure requirement of the 21st century. A fundamental query in studying network is thus how much information one can reliably send and how to design a scheme that attains the optimal network throughput. Presently, almost all network information theory results consist of two parts: Firstly, devising a clever solution, and then mathematically proving its optimality. Both tasks are highly non-trivial and our understanding of optimal network communications is thus still nascent. This project proposes a fundamentally new methodology, called knowledge space partition, to drastically reduce the size of the design space of network communication schemes. This allows us to use computers to systematically search for the best possible solution and automate the design of high-performance network protocols. The optimality of the resulting scheme is also guaranteed since the computer-aided search is exhaustive in nature. Based on this central idea, this project will (i) Systematically compute the linear network coding capacity for various small packet erasure networks; (ii) Design and implement optimal linear network coding protocols in practice; and (iii) Generalize the results from network-layer processing to physical-layer processing. The new methodology will unify the concepts of stability region and capacity region, with the two concepts that having long separated the networking and information theory communities. The success of this project will also imbue next generation network engineers with back-to-basics information-theoretic thinking with enormously rich network optimization techniques. With realistic settings and implementation-friendly constructions, the optimal theoretic results of this project should spur significant developments in system-level research as well. Preliminary results of this project have shown that the network coding benefits are especially significant for the loosely-coordinated low-cost solutions operated in unlicensed bands, such as Wi-Fi. The findings of this project will thus further bridge both the domestic and global digital divide. Several sub-topics of this project, e.g., using linear algebra to improve network throughput, will be used to attract minorities and women through the Vertically Integrated Projects (VIP) of Purdue, an undergraduate-research course that engages undergraduate students in a team-based hand-on research environment.

发展高速率、更高效、无处不在的通信网络是21世纪骨干基础设施的关键要求。因此，研究网络的一个基本问题是可以可靠地发送多少信息以及如何设计一种实现最佳网络吞吐量的方案。目前，几乎所有的网络信息论成果都由两部分组成：首先设计一个巧妙的解决方案，然后从数学上证明其最优性。这两项任务都非常重要，因此我们对最佳网络通信的理解仍处于初级阶段。该项目提出了一种全新的方法，称为知识空间划分，以大幅减少网络通信方案的设计空间的大小。这使得我们能够使用计算机系统地搜索最佳可能的解决方案并自动化设计高性能网络协议。由于计算机辅助搜索本质上是详尽的，因此也保证了所得方案的最优性。基于这一中心思想，该项目将（i）系统地计算各种小数据包擦除网络的线性网络编码容量； (ii) 在实践中设计和实现最佳线性网络编码协议； (iii) 将网络层处理的结果推广到物理层处理。新的方法将统一稳定区域和容量区域的概念，这两个概念长期以来将网络和信息理论界分开。该项目的成功还将为下一代网络工程师灌输回归基础的信息论思维和极其丰富的网络优化技术。凭借现实的设置和易于实施的结构，该项目的最佳理论结果也将刺激系统级研究的重大发展。该项目的初步结果表明，网络编码优势对于在免许可频段（例如 Wi-Fi）中运行的松散协调的低成本解决方案尤其重要。因此，该项目的研究结果将进一步弥合国内和全球数字鸿沟。该项目的几个子主题，例如，使用线性代数提高网络吞吐量，将用于通过普渡大学的垂直整合项目（VIP）吸引少数族裔和女性，这是一门本科生研究课程，让本科生参与团队 -基于实践的研究环境。