NeTS-NBD: Characterizing Large-Scale, Dynamic Peer-to-Peer Networks: New Sampling and Modeling Approaches

NeTS-NBD：表征大规模动态点对点网络：新的采样和建模方法

• 批准号: 0627202
• 负责人: Reza Rejaie
• 金额: $ 30万
• 依托单位: University of Oregon Eugene
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-01 至 2010-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0627202&HistoricalAwards=false
• 关键词: NeTS; NBD; Characterizing; Large; Scale

Despite the importance of the peer-to-peer (P2P) communication paradigm and the far reaching impact of P2P applications on the Internet, fundamental properties concerning the dynamics of large scale P2P applications are not well understood. The fundamental challenge in deriving these characteristics is to capture a representative (i.e. unbiased) view of large scale P2P systems as they evolve over time. This project investigates and develops new measurement and modeling methodologies to understand and accurately characterize properties of the dynamics of large scale P2P systems. For example, the PIs identify the topological and temporal sources of bias in estimating peer connectivity and peer properties. The PIs also examine the idea of sampling dynamic graphs as a novel approach to capture representative measurements in large and dynamic P2P systems. An innovative combination of empirical and modeling efforts (along with simulation) is leveraged to accurately derive key characteristics of P2P systems, identify their underlying causes, and study their implications for the design and evaluations of future P2P systems.Broader Impact:The resources contributed by this project have far-reaching implications on the research and development of P2P systems and include (i) a set of new high-fidelity measurement methodologies and tools, (ii) a novel class of evolutionary models that account for the dynamic properties of existing P2P systems, (iii) a publicly available archive of measurements of actual P2P systems, and (iv) a new modular session-level P2P simulator. The resulting measurement methodologies, models and tools will be incorporated into newly developed courses at the undergraduate and graduate levels at the University of Oregon.

尽管对等（P2P）通信模式的重要性和P2P应用程序在互联网上的深远影响，有关大规模P2P应用程序的动态的基本属性还没有得到很好的理解。 在获得这些特征的根本挑战是捕捉一个代表性的（即无偏见的）大规模P2P系统的观点，因为它们随着时间的推移而演变。该项目研究和开发新的测量和建模方法，以理解和准确表征大规模P2P系统的动态特性。例如，PI识别在估计对等连接和对等属性时的拓扑和时间偏差源。PI还研究了采样动态图的想法，作为一种新的方法来捕捉大型动态P2P系统中的代表性测量。经验和建模工作的创新结合（沿着仿真）被用来准确地得出P2P系统的关键特征，识别其根本原因，并研究其对未来P2P系统的设计和评估的影响。该项目所提供的资源对P2P系统的研究和开发具有深远的影响，包括（i）一套新的高保真测量方法和工具，（ii）一类新的进化模型，占现有的P2P系统的动态特性，（iii）一个公开的档案测量实际P2P系统，及（iv）一个新的模块化会话级P2P模拟器。由此产生的测量方法、模型和工具将被纳入俄勒冈州大学本科生和研究生新开发的课程。