Workshop on Ultra-Large Networks: Challenges and New Research Directions for Modeling and Simulation
Workshop on Ultra-Large Networks: Challenges and New Research Directions for Modeling and Simulation
批准号:
0135530
负责人:
Bernard Zeigler
金额:
$9.49万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2001
资助国家:
美国
项目状态:
已结题
起止时间:
2001-09-01 至 2003-06-30
中文摘要
我们建议于2001年秋季在亚利桑那州图森市举办一次为期两天的研讨会,讨论诸如互联网等新兴的超大型网络。会议由亚利桑那州综合建模与仿真中心主办,将汇集网络领域的一些世界领先的研究人员,与具有网络和系统建模与仿真专业知识的同行会面。研讨会将为这些研究人员提供超大型基因工程未知数的任务,以及可以解决这些未知数的建模和仿真研究的新方向。 互联网的连接性正在不断提高,到2005年将达到10亿个节点,节点能力提供了一个高度互连和计算能力强大的媒介。这样一个遍布全球、无处不在的网络将为新型的教育、商业和娱乐活动提供一个新的前沿。然而,在这样一个大规模、高度分散的交互部件集合的出现中,也出现了许多问题。连接性和能力的增加创造了新的复杂性和动态,我们只是在欣赏的边缘。处理大型软件系统的困难在国家研究理事会最近的一份报告中有详细的记载。适用于小型软件系统的技术在规模增加100万倍时明显失败。基于计算机的建模和仿真(MS)的方法,需要解决这些问题,因为规模远远超出了什么分析工具可以单独处理,并有有限的能力做受控实验上的alwayson互联网。传统的M S方法集中在微观层面的组件,而不是这些组件的宏观层面的集成。然而,随着超大规模系统的出现,如未来的互联网,它是必要的MS方法来理解非常大的互联网络的行为,很少的控制点和许多相互作用和不同的输入和服务需求的来源。 本次研讨会的结果预计将是一组具体的发现差距,我们的知识的thebraffic超大型网络的行为,以及如何处理他们的设计,管理和控制。研究者可以评估目前的方法是否可以发展以应对规模的大幅增加,或者是否需要不同的革命性范式。与会者将讨论建立超大型网络模型和开发研究其行为的模拟环境的新技术和方法的需求。建议借用其他领域的观点,如复杂的自适应系统和建模与仿真的基本理论将受到鼓励。会议记录将被汇编成一种形式,为未来网络基础设施研究的新NSF资助计划提供一个有用的和重要的指南。
英文摘要
We propose to hold a two-day workshop in Tucson, Arizona during fall 2001 on emerging ultra-largenetworks, such as the Internet. Hosted by Arizona Center for Integrative Modeling and Simulation, themeeting will bring together some of the world's leading researchers in the networking area to meet withcounterparts with expertise in modeling and simulation of networks and of systems more generally. Theworkshop will provide these researchers with the task of coming up with the unknowns of ultra-largenetworks and with new directions of research in modeling and simulation that can address these unknowns. The Internet is increasing in connectivity, toward 1 billion nodes in 2005 and node capability providing ahighly interconnected and computationally powerful medium. Such a globally and ubiquitously dispersednetwork will provide a new frontier for new kinds of educational, commerce and entertainment activities.However, there are many issues that arise in the emergence of such a large, highly decentralized, collectionof interaction parts. The increased connectivity and capability creates new complexity and dynamics thatwe are only on the verge of appreciating. Difficulties in dealing with large-scale software systems are welldocumented in a recent report by the National Research Council. Techniques that work for small softwaresystems fail markedly when the scale is increased by one million fold. Computer-based modeling andsimulation (M&S) methodology is required to address these issues since the scale is well beyond whatanalytical tools alone can handle and there is limited ability to do controlled experiments on the alwayson Internet. Traditional M&S approaches have focussed on the micro-level components rather than themacro level integration of these components. However, with the advent of ultra-large scale systems such asthe Internet of the future, it is necessary to develop M&S approaches for understanding the behaviors ofvery large inter-connected networks with very few loci of control and many interacting and varied sourcesof input and services demand. The results of this workshop are expected to be a set of specific finding of gaps in our knowledge of thebehavior of ultra-large networks and how to deal with their design, management, and control. Participantsmay assess whether current approaches can be evolved to deal with the large increases in scale or whetherdifferent, revolutionary paradigms are required. Participants will address the need for new techniques andapproaches for building models of ultra-large networks and developing simulation environments forstudying their behaviors. Suggestions for borrowing points of view form other areas such as complexadaptive systems and from basic theory of modeling and simulation will be encouraged. The proceedingswill be compiled in a form that will provide a useable and significant guide for new NSF funding initiativesfor future network infrastructure research.
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