NetSE: Medium: Modeling and Analysis of Network Dynamics

NetSE：媒介：网络动态建模与分析

• 批准号: 1065133
• 负责人: Donald Towsley
• 金额: $ 78.02万
• 依托单位: University of Massachusetts Amherst
• 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: 2011-06-01 至 2015-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1065133&HistoricalAwards=false
• 关键词: NetSE; Medium; Modeling; Analysis; Network

There has been a rapid increase in the number and types of digital networks over the last 2 decades beginning, of course with the Internet, its constituent networks, and the World Wide Web. We now have a wide range of on-line social networks (OSNs) such as Facebook, Twitter, mobile ad hoc networks (MANETs) and delay tolerant networks (DTNs). These networks pervade all aspects of our lives and provide a growing range of services in commerce, business, communications, and connectivity. Many of these networks are continually in a dynamic state of flux and/or extremely large. For example, the topology of a MANET or a DTN is constantly changing, and that of an OSN such as Facebook is rapidly growing and evolving. The modeling, analysis, and measurement of such networks are challenging, due to their dynamism and sizes. As a consequence, traditional mathematical techniques are not suitable and fundamentally new techniques are needed.This research will focus on three interrelated problems. The first is to develop useful and accurate models that capture the dynamics of today?s social and technological networks. The second is to develop and study a class of techniques for characterizing and searching such networks. These techniques are based on a very simple mechanism, namely to let an agent explore the network by randomly choosing where to go. This is known as a random walk in the mathematics literature and has been shown to exhibit desirable search and characterization properties in static networks that shows promise in dynamic networks. Last, many static networks exhibit what is known as a power law, namely that the distribution for the number of neighbors of a node roughly decays as k−a where k is the number of neighbors and a is a positive constant greater than one. The third problem is to understand what constitutes a power law in a dynamic network, how this power law comes to be, and what implications there might be regarding the health of the network.Broader Impact. The work will positively impact society by providing a deeper understanding of and a set of tools for managing and monitoring digital networks such as MANETs and OSNs. The project includes a comprehensive dissemination plan including public release of tools for network characterization. The education plan includes cross-specialty seminars, undergraduate involvement in research through a REU site, and international outreach to South America.

在过去的20年里，数字网络的数量和类型迅速增加，当然是从互联网、其组成网络和万维网开始的。我们现在有广泛的在线社交网络（OSN），如Facebook，Twitter，移动的ad hoc网络（MANN）和延迟容忍网络（DTN）。这些网络渗透到我们生活的各个方面，并在商业、通信和连接方面提供越来越多的服务。这些网络中的许多网络持续处于动态的流动状态和/或非常大。例如，MANET或DTN的拓扑结构不断变化，而OSN（如Facebook）的拓扑结构正在快速增长和发展。由于这些网络的动态性和规模，其建模、分析和测量具有挑战性。因此，传统的数学方法已不适用，需要从根本上的新技术。第一个是开发有用和准确的模型，捕捉今天的动态？的社会和技术网络。第二是开发和研究一类用于表征和搜索此类网络的技术。这些技术基于一个非常简单的机制，即让代理通过随机选择去哪里来探索网络。这在数学文献中被称为随机游走，并已被证明在静态网络中表现出理想的搜索和表征特性，在动态网络中表现出希望。最后，许多静态网络表现出所谓的幂律，即节点的邻居数量的分布大致衰减为k a，其中k是邻居的数量，a是大于1的正常数。第三个问题是要理解动态网络中的幂律是什么，幂律是如何形成的，以及它对网络的健康状况有什么影响。这项工作将对社会产生积极的影响，提供更深入的理解和一套工具来管理和监控数字网络，如MANN和OSN。该项目包括一个全面的传播计划，包括公开发布网络特征描述工具。教育计划包括跨专业研讨会，本科生通过REU网站参与研究，以及对南美洲的国际推广。