ITR: A Multiresolution Analysis for the Global Internet

ITR：全球互联网的多分辨率分析

• 批准号: 0085984
• 负责人: Amos Ron
• 金额: $ 260.96万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-09-01 至 2005-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0085984&HistoricalAwards=false
• 关键词: ITR; Multiresolution; Analysis; Global; Internet

An interdisciplinary team, bridging academia and industry, proposes a united effort to study the dynamics of the global Internet, moving beyond the traditional single-timescale, single-network, single-protocol paradigm to a description that compactly incorporates a wide range of time-scales, a broad spectrum of spatial network topology structures, andmultiple protocols interacting with one another and across the different networking layers. Achieving such a global, multi-scale, and multi-layer understanding of complex large-scale networks is imperative for the successful design and development of the next-generation Internet protocols and engineering tools, where issues related to robustness,scalability, and efficiency take center stage. In this united effort, there are three main ingredients. First, the researchers plan to fully exploit a new breed of datasets of network-wide measurements - unprecedented in volume and quality - that are the result of recent exciting networking research projects, such as the National Internet Measurement Infrastructure project (NIMI). Another source of such data will be various Internet Service Providers (ISPs), such as AT&T, employer of one of the PIs, which will also provide supplementary funding if this proposal is accepted. Second, the researchers will rely on a new breed of network simulation tools, such as SSFNET, largely developed by another of our PIs, and capable of simulating internetworks unprecedented in scale and detail. All these new measurements, whether real or virtual, will constitute huge datasets with very high and networking-specific semantic content, creating completely novel challenges for data analysis. This is where the third ingredient comes in: multiscale and multiresolution/wavelet techniques, developed by several of the PIs, will take center stage when it comes to analyzing, visualizing, and uncovering the rich information that is contained in these network measurements. Although the flexibility and the speed of wavelet decompositions have been put to good use in the past in many applications, including the empirical observation of certain types of time-scaling behaviors in measured network traffic, the technology as it is known and used today cannot yet cope with the fascinating new challenges posed by the available and anticipated Internet data. A central objective of this project is to develop Internet-appropriate multiresolution techniques that match the multiscale nature of the underlying Internet structure and can be validated step-by-step against measurements. The researchers expect that tools and theories that have been developed in the context of computer graphics, irregular sampling, and scattered data approximation will be utilized to this end. The ultimate goal of the proposed research effort is to identify interesting patterns that can be extracted from the measured data via fast algorithms, that are linked to physical concepts and are meaningful in the networking context, that characterize different states or behaviors of the network, and that can aid the development of novel network measurement analysis and visualization techniques in support of a new generation of monitoring and engineering tools for future Internet architectures. Given that so much of this area is still uncharted, it may be not realistic to hope to attain this goal in a few years' time. Nevertheless, we are convinced that only an interdisciplinary effort like ours can hope to achieve anything in this direction; we expect that our collaboration will lead to deeper insights and understanding; a first identification of models, patterns, the influences of various external factors and protocols; and an initial glimpse at the underlying "physics of the Internet" - a solid understanding of how basic networking mechanisms and user behaviors contribute to the fascinating dynamic observed in today's Internet.

一个连接学术界和工业界的跨学科团队提出共同努力研究全球互联网的动态，超越传统的单时间尺度、单网络、单协议范式，转而紧凑地结合了广泛的时间尺度、广泛的空间网络拓扑结构以及跨不同网络层相互交互的多种协议。对复杂的大规模网络实现全球性、多尺度、多层次的理解对于下一代互联网协议和工程工具的成功设计和开发至关重要，其中与鲁棒性、可扩展性和效率相关的问题占据中心位置。 在这一共同努力中，有三个主要成分。首先，研究人员计划充分利用新型全网络测量数据集——在数量和质量上都是前所未有的——这是最近令人兴奋的网络研究项目的成果，例如国家互联网测量基础设施项目（NIMI）。此类数据的另一个来源将是各种互联网服务提供商 (ISP)，例如其中一名 PI 的雇主 AT&T，如果该提案被接受，他们也将提供补充资金。其次，研究人员将依赖新型网络模拟工具，例如 SSFNET，它主要由我们的另一位 PI 开发，能够在规模和细节上模拟前所未有的互联网。所有这些新的测量，无论是真实的还是虚拟的，都将构成具有非常高的网络特定语义内容的巨大数据集，为数据分析带来全新的挑战。这就是第三个要素的用武之地：由几位 PI 开发的多尺度和多分辨率/小波技术将在分析、可视化和揭示这些网络测量中包含的丰富信息时占据中心位置。尽管小波分解的灵活性和速度过去在许多应用中得到了很好的利用，包括对测量的网络流量中某些类型的时间缩放行为的经验观察，但当今已知和使用的技术尚无法应对可用和预期的互联网数据所带来的令人着迷的新挑战。该项目的中心目标是开发适合互联网的多分辨率技术，该技术与底层互联网结构的多尺度性质相匹配，并且可以根据测量结果逐步进行验证。研究人员预计，在计算机图形学、不规则采样和分散数据近似的背景下开发的工具和理论将被用于此目的。 拟议研究工作的最终目标是识别可以通过快速算法从测量数据中提取的有趣模式，这些模式与物理概念相关并且在网络环境中有意义，可以表征网络的不同状态或行为，并且可以帮助开发新颖的网络测量分析和可视化技术，以支持未来互联网架构的新一代监控和工程工具。鉴于这一领域的大部分内容仍然未知，希望在几年内实现这一目标可能不现实。尽管如此，我们相信，只有像我们这样的跨学科努力才有希望在这个方向上取得任何成果；我们期望我们的合作能够带来更深入的见解和理解；首次识别模型、模式、各种外部因素和协议的影响；以及对底层“互联网物理”的初步了解——对基本网络机制和用户行为如何促成当今互联网中令人着迷的动态的深入理解。