Development of autonomy oriented computing (AOC) systems for distributed computational problem solving

开发用于分布式计算问题解决的自主计算（AOC）系统

• 批准号: 329024-2006
• 负责人: Liu, Jiming
• 金额: $ 2.19万
• 依托单位: University of Windsor
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2006
• 资助国家: 加拿大
• 起止时间: 2006-01-01 至 2007-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=338461
• 关键词: Development; autonomy; oriented; computing; AOC

Autonomy oriented computing (AOC) is a bottom-up computing paradigm for solving computationally hard problems and for characterizing complex systems. Drawing on our previous work on AOC (Liu et al., 2002, 2004,2005), in this proposed research program, we aim to systematically model and develop autonomy oriented self-organizing systems as well as to empirically validate the capability and robustness of the AOC systems in solving large-scale computationally hard problems, such as distributed constraint satisfaction and optimization problems. In so doing, we will formally characterize the basic AOC elements, their local interaction and self-organization processes, and thereafter gain an in-depth understanding of the AOC performance from the points of view of systems optimization and topology-based computational complexity studies.   This research will have direct impacts on several important systems applications: (1) ( megascale) The development of e-transformation (e.g., e-learning) solutions, in which the service related problems are large-scale, highly-distributed in nature, and can readily be formulated, solved, and evaluated using the AOC approach; (2) (microscale) The development of autonomy oriented sensor networks that perform the tasks of collective spatial mapping (or world modeling) while satisfying their resource and energy constraints; (3) (nanoscale) The design and development of amorphous computing devices such as nanomachines and cellular computers, in which computational or programming means for generating coherent behaviors from vast numbers of unreliable parts, called "computational particles" (whether microfabricated particles on a chip or engineered cells for assembling nanoscale structures), are essential that are locally-interacting, irregularly-placed, and asynchronous.

面向自主的计算(AOC)是一种自下而上的计算范式，用于解决计算困难的问题和表征复杂系统。借鉴我们在AOC(Liu et al.，2002,2004,2005)的工作，在本研究计划中，我们的目标是系统地建模和开发面向自主的自组织系统，并实证验证AOC系统在解决大规模计算困难问题(如分布式约束满足和优化问题)方面的能力和健壮性。在此过程中，我们将形式化地描述AOC的基本元素及其局部相互作用和自组织过程，然后从系统优化和基于拓扑的计算复杂性研究的角度深入了解AOC的性能。这项研究将对几个重要的系统应用产生直接影响：(1)(兆级)e-Transform(例如，e-Learning)解决方案的开发，其中与服务相关的问题是大规模的、高度分布的，并且可以很容易地使用AOC方法来制定、解决和评估；(2)(微尺度)面向自主的传感器网络的发展，它在满足资源和能源限制的同时执行集体空间映射(或世界建模)的任务；(3)(纳米尺度)非晶态计算设备的设计和开发，其中用于从大量不可靠的部件(无论是芯片上的微型制造颗粒还是用于组装纳米尺度结构的工程细胞)产生相干行为的计算或编程手段是本地相互作用、不规则放置和异步的。