Cyber Systems: Adaptive Distributed Systems Based on Cooperative and Combination Strategies

网络系统：基于合作和组合策略的自适应分布式系统

• 批准号: 0601266
• 负责人: Ali Sayed
• 金额: --
• 依托单位: University of California-Los Angeles
• 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=0601266&HistoricalAwards=false
• 关键词: Cyber; Systems; Adaptive; Distributed; Based

Adaptive Distributed Systems Based on Cooperative and Combination StrategiesScope and Intellectual Merit. The objective of this research is to develop processing algorithms that endow distributed networks with real-time adaptation and learning abilities. The distributed algorithms should be able to exploit the spatial diversity of the distributed nodes, as well as the temporal dimension of the data, in order to deliver improved levels of performance through cooperation between neighboring nodes. The approach is based on exploiting incremental and combination strategies and allows for real-time flow of information across the network. The purpose is to develop adaptive distributed strategies that require limited local communications and computation and that are robust to topology changes.Broader Benefits. The driving force for such adaptive networks is the realization that distributed systems linking PCs, laptops, cell phones, sensors and actuators will form the backbone of future data and communication networks. Applications will include sensor networks, precision agriculture, environment monitoring, target localization, disaster relief management, and medical examinations. The purpose of distributed processing is to combine the data captured locally at the distributed nodes in order to deliver good performance globally. The processing needs to be done adaptively and in real-time because not only the environmental conditions vary with time and space, but the network topology may also vary. The proposed research shows how to combine tools from across disciplines in order to develop adaptive distributed networks. Progress in this work will impact the information technology infrastructure and will contribute to the training of students in an area of fundamental relevance to future communications and networking systems.

基于协作与组合的适应性分布式系统.本研究的目的是开发处理算法，赋予分布式网络的实时适应和学习能力。分布式算法应该能够利用分布式节点的空间多样性以及数据的时间维度，以便通过相邻节点之间的合作来提供更高的性能水平。该方法基于利用增量和组合策略，并允许跨网络的实时信息流。其目的是开发自适应分布式策略，这些策略需要有限的本地通信和计算，并且对拓扑变化具有鲁棒性。这种自适应网络的驱动力是认识到连接PC、笔记本电脑、手机、传感器和执行器的分布式系统将构成未来数据和通信网络的骨干。应用将包括传感器网络、精准农业、环境监测、目标定位、救灾管理和医疗检查。分布式处理的目的是联合收割机组合在分布式节点本地捕获的数据，以便在全局上提供良好的性能。处理需要自适应和实时地进行，因为不仅环境条件随时间和空间而变化，而且网络拓扑也可能变化。拟议的研究表明，如何联合收割机工具，从跨学科，以开发自适应分布式网络。这项工作的进展将影响到信息技术基础设施，并将有助于在与未来通信和联网系统具有根本关系的领域对学生进行培训。