EAGER: Self-Organization Based Control for New Generation Networks

EAGER：新一代网络的基于自组织的控制

• 批准号: 1032207
• 负责人: Douglas Sicker
• 金额: $ 25万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-05-01 至 2013-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1032207&HistoricalAwards=false
• 关键词: EAGER; Self; Organization; Based; Control

Existing Biologically Inspired Algorithm (BIA) approaches to Self-Organized (SO) networks lack a theoretical foundation and analysis. This work develops a framework to describe the types of problems that BIA can address in network control. First, this work establishes a theory of BIA network control. Here the PIs: a) broadly review the literature for BIAs that have been applied to solving control theory problems and develop a categorization of the methods; b) categorize the common problems in network control and the complexity of these problems; c) analytically demonstrate the potential of these BIAs in solving various network control problems; and d) formally describe BIA for control of wireless networks. Second, this work analyzes mutual interaction among layers in a BIA-based network. The PIs carry out an analysis of mutual interaction among layers in BIA-based networks. This includes a) analysis of interaction among layered SO-based control and b) establishment of a fundamental theory of layered architecture. Third, this work analyzes BIA-based control in wireless networks. Here the PIs conduct analyses of BIA-based control on wireless networks, to a) determine implementation issues of BIA-based control on real systems and b) perform a practical evaluation and analysis of BIA-based control through simulation and testbed implementation. This work is significant in that it provides a framing of BIA and provides a means for others to assess new approaches beyond wireless applications. The results of this work will be made available in conference and journal publications and through web sources.

现有的生物启发算法（BIA）的自组织（SO）网络的方法缺乏理论基础和分析。这项工作开发了一个框架来描述BIA在网络控制中可以解决的问题类型。首先，本文建立了BIA网络控制理论。 这里的PI：a）广泛地回顾已经应用于解决控制理论问题的BIA的文献，并开发方法的分类; B）对网络控制中的常见问题和这些问题的复杂性进行分类; c）分析地证明这些BIA在解决各种网络控制问题中的潜力;以及d）正式地描述用于无线网络控制的BIA。其次，本文分析了基于BIA的网络中各层之间的相互作用。 PI对基于BIA的网络中各层之间的相互作用进行分析。这包括a）分析基于SO的分层控制之间的相互作用和B）建立分层体系结构的基本理论。 第三，本文分析了无线网络中基于BIA的控制。在这里，PI对无线网络上基于BIA的控制进行分析，以a）确定基于BIA的控制在真实的系统上的实现问题，以及B）通过仿真和测试床实现对基于BIA的控制进行实际评估和分析。这项工作是重要的，因为它提供了一个框架的BIA，并为其他人提供了一种手段，以评估新的方法超越无线应用。这项工作的结果将在会议和期刊出版物中以及通过网络资源提供。