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: $ 0.67万
• 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: 2007
• 资助国家: 加拿大
• 起止时间: 2007-01-01 至 2008-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=361019
• 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.

面向自治的计算（AOC）是一种自底向上的计算范式，用于解决计算困难的问题和表征复杂系统。借鉴我们以前关于AOC的工作（Liu等人，2002，2004，2005），本研究旨在系统地建模和开发面向自治的自组织系统，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）中的能力和鲁棒性。在这样做的过程中，我们将正式描述的基本AOC元素，他们的本地相互作用和自组织过程，然后获得一个深入了解的AOC性能的角度来看，系统优化和基于拓扑的计算复杂性研究。 这项研究将对几个重要的系统应用产生直接影响：（1）（兆级）电子转换的发展（例如，电子学习）解决方案，其中服务相关的问题是大规模的，高度分布的性质，可以很容易地制定，解决和评估使用AOC方法;（2）（微尺度）发展自主导向的传感器网络，执行集体空间测绘任务（或世界建模），同时满足其资源和能源约束;（三）（纳米级）设计和开发非晶计算设备，如纳米机器和蜂窝计算机，其中，用于从大量不可靠的部分（称为“计算粒子”，无论是芯片上的微制造粒子还是用于组装纳米级结构的工程细胞）产生相干行为的计算或编程装置是必不可少的，其是局部相互作用的、不规则放置的和异步的。