Workshop: Reflected Brownian Motions, Stochastic Networks, and their Applications; Minneapolis, Minnesota; June 25-27, 2015

研讨会：反射布朗运动、随机网络及其应用；

• 批准号: 1450358
• 负责人: Jiangang Dai
• 金额: $ 1.2万
• 依托单位: Cornell 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: 2014-09-01 至 2016-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1450358&HistoricalAwards=false
• 关键词: Workshop; Reflected; Brownian; Motions; Stochastic

Stochastic network models are mathematical descriptions of interconnected systems with randomly varying properties. These models provide a critical bridge between the powerful tools of mathematical network theory and the unpredictable real world. Stochastic networks have been used to model manufacturing systems, call centers, health care systems, and a wide variety of electronic communication systems, including the Internet, wireless and wireline networks, and sensor networks. This workshop will bring together mathematicians and applied researchers who share an interest in stochastic network models, and will highlight areas of greatest current activity, providing intellectual guidance to young researchers and to the larger community of applied probabilists. In particular, this workshop will connect mathematicians developing powerful abstract tools with the applications communities that can translate these tools into major improvements in real network performance. The supported activity will allow the organizers to broaden participation in the workshop by partially defraying travel costs.

随机网络模型是具有随机变化属性的互连系统的数学描述。这些模型在数学网络理论的强大工具和不可预测的现实世界之间架起了一座重要的桥梁。随机网络已用于对制造系统、呼叫中心、医疗保健系统以及各种电子通信系统（包括互联网、无线和有线网络以及传感器网络）进行建模。本次研讨会将汇集对随机网络模型感兴趣的数学家和应用研究人员，并将重点关注当前最活跃的领域，为年轻研究人员和更大的应用概率学家社区提供智力指导。特别是，本次研讨会将把开发强大抽象工具的数学家与应用程序社区联系起来，将这些工具转化为实际网络性能的重大改进。支持的活动将使组织者能够通过支付部分差旅费用来扩大研讨会的参与范围。