NeTS: Small: Collaborative Research: Large Scale Networks and Information Flow: From Emergent Behavior to Algorithm Design

NeTS：小型：协作研究：大规模网络和信息流：从涌现行为到算法设计

• 批准号: 1234410
• 负责人: Edmund Yeh
• 金额: $ 14.32万
• 依托单位: Northeastern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-07-01 至 2014-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1234410&HistoricalAwards=false
• 关键词: NeTS; Small; Collaborative; Research; Large

This project studies the performance of complex large-scale spatial networks that use distributed communication algorithms by applying different random network models. While much of the previous work on random spatial networks has focused on topological aspects and on centralized algorithm design, the emphasis of this project is on developing distributed algorithms and on characterizing desired invariant network properties that such networks must satisfy to allow for the efficient implementation of distributed algorithms. Expected results from the project include (1) decentralized algorithms for efficient path navigation, (2) decentralized algorithms for information flow in random networks, (3) decentralized algorithms for information dissemination, (4) distributed energy management in random networks, and (5) distributed topology control for maintaining percolation-based connectivity. This project will (1) increase the understanding of complex information systems upon which society increasingly depends, (2) lead to design guidelines for practical network architectures and protocols, (3) disseminate the scientific and technological findings through publications, (4) further the development of related disciplines such as mathematics (probability) and statistical physics, (5) impact undergraduate and graduate education through a planned joint course on random networks, and a summer lecture series, (6) enhance research experiences for undergraduates through summer research projects, and (7) encourage the participation of women and minorities in networking research.

该项目通过应用不同的随机网络模型来研究使用分布式通信算法的复杂大规模空间网络的性能。虽然以前关于随机空间网络的大部分工作都集中在拓扑方面和集中式算法设计上，但本项目的重点是开发分布式算法和刻画这样的网络必须满足的期望的不变网络性质，以允许有效地实现分布式算法。该项目的预期结果包括：(1)有效路径导航的分散式算法；(2)随机网络中的信息分散式算法；(3)信息传播的分散式算法；(4)随机网络中的分布式能量管理；以及(5)保持基于渗流的连通性的分布式拓扑控制。该项目将(1)提高对社会日益依赖的复杂信息系统的了解，(2)为实用的网络架构和协议提供设计准则，(3)通过出版物传播科技成果，(4)进一步发展相关学科，如数学(概率)和统计物理，(5)通过计划的随机网络联合课程和暑期系列讲座影响本科生和研究生教育，(6)通过暑期研究项目增进本科生的研究经验，以及(7)鼓励妇女和少数群体参与网络研究。