Probabilistic combinatorics: Properties of large networks

概率组合学：大型网络的属性

• 批准号: DE170100716
• 负责人: Dr Pu Gao
• 金额: $ 10.97万
• 依托单位: Monash University
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Early Career Researcher Award
• 财政年份: 2017
• 资助国家: 澳大利亚
• 起止时间: 2017-06-30 至 2018-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DE170100716
• 关键词: Probabilistic; combinatorics; Properties; large; networks

This project aims to analyse important real-world network properties such as robustness and reliability, investigate the performance of network algorithms such as message propagation, and solve fundamental problems in probabilistic combinatorics. Random graphs are indispensable for modelling and analysing the growing Internet and many social networks, due to their large size and random nature. The intended outcome is improved understanding of properties of real networks, including robustness and message propagation performance. It should provide better knowledge of the evolutionary behaviour of large growing networks, relevant to a world that is influenced greatly by the Internet.

该项目旨在分析重要的现实世界的网络属性，如鲁棒性和可靠性，研究网络算法的性能，如消息传播，并解决概率组合学中的基本问题。随机图是不可或缺的建模和分析不断增长的互联网和许多社交网络，由于其规模大，随机性质。预期的结果是提高对真实的网络属性的理解，包括鲁棒性和消息传播性能。它应该提供更好的知识，大型网络不断增长的演变行为，相关的世界，受到互联网的影响很大。