Asynchronous Epidemic Algorithms

异步流行病算法

• 批准号: 9820888
• 负责人: James Aspnes
• 金额: $ 13.13万
• 依托单位: Yale University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-09-01 至 2002-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9820888&HistoricalAwards=false
• 关键词: Asynchronous; Epidemic; Algorithms

Epidemic and gossip algorithms attempt to spread information quickly through a network of processors. Traditionally, these algorithms have assumed that most processors and communications links run at approximately the same speed. This assumption is unrealistic for large Wide Area Networks such as the Internet that contain both slow and fast links and both slow and fast machines. The project will design and analyze highly-resilient and scalable mechanisms for propagating information rapidly that extend the epidemic approach to models that more accurately reflect real-world conditions.

流行病和流言算法试图通过处理器网络快速传播信息。 传统上，这些算法假设大多数处理器和通信链路以近似相同的速度运行。 这种假设对于大型广域网是不现实的，例如包含慢速和快速链接以及慢速和快速机器的Internet。 该项目将设计和分析高度弹性和可扩展的机制，用于快速传播信息，将流行病方法扩展到更准确反映现实世界条件的模型。