Scalable Enterprise Systems: Scalable Algorithms and Distributed Agent Architectures for Adaptive Enterprises

可扩展的企业系统：自适应企业的可扩展算法和分布式代理架构

• 批准号: 0075572
• 负责人: Vittaldas Prabhu
• 金额: $ 9.88万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-08-15 至 2001-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0075572&HistoricalAwards=false
• 关键词: Scalable; Enterprise; Systems; Algorithms; Distributed

This grant provides funding for building highly scalable distributed algorithms for a new class of adaptive manufacturing enterprises using distributed agent architecture over the Internet. These algorithms will be used for reconfiguring work-in-process inventory levels and production schedules to adapt to changing market demands and supply-chain conditions. Moreover, these algorithms and the necessary information will be embedded in agents geographically distributed throughout the enterprise. The goal is to maintain responsiveness and effectiveness to enable the next generation of scalable enterprises. Scalability will be achieved through (1) distributed algorithms that are predictable and computationally efficient; (2) distributed agent architectures that support growth in size and capability; and (3) distributed clusters that provide rapid access to information using cost effective technologies. Analytical models will be developed to predict the emergent behavior of such systems and stability and convergence properties of their computations. These models will be used for assessing computational complexity, communication requirements, and scalability of the algorithms. Distributed agent architecture will be developed in which clusters of similar agents will be identified based on task decomposition and task similarity. An experimental prototype using a cluster of commodity PCs will be used to benchmark the computational load, communication network requirements, and overall scalability of the algorithms.If successful, the results of this research will lead to effective integration of shop floor with enterprise software which is a critical issue in managing multiple enterprises effectively and optimally. These research activities will involve active collaboration with several industry partners. In the short-term, this work will provide a set of novel distributed algorithms and a suitable distributed agent architecture. In the long-term, this work would provide mathematical and simulation models for designing the next generation of adaptive and reconfigurable enterprises by establishing scientific and technological insights into their scalability.

这笔赠款提供资金，用于为使用互联网上的分布式代理体系结构的新型适应性制造企业构建高度可扩展的分布式算法。这些算法将用于重新配置在制品库存水平和生产计划，以适应不断变化的市场需求和供应链条件。此外，这些算法和必要的信息将嵌入分布在整个企业的地理位置的代理中。我们的目标是保持响应性和有效性，以支持下一代可扩展企业。可伸缩性将通过(1)可预测和计算高效的分布式算法；(2)支持规模和能力增长的分布式代理体系结构；以及(3)使用具有成本效益的技术提供快速信息访问的分布式集群来实现。将开发分析模型来预测这类系统的涌现行为及其计算的稳定性和收敛特性。这些模型将用于评估算法的计算复杂性、通信要求和可伸缩性。将开发分布式代理体系结构，其中将根据任务分解和任务相似度来识别相似代理的集群。使用一台商用PC集群的实验原型将被用来对算法的计算负载、通信网络需求和整体可伸缩性进行基准测试。如果成功，该研究结果将导致车间与企业软件的有效集成，这是有效和优化管理多个企业的关键问题。这些研究活动将涉及与几个行业合作伙伴的积极合作。在短期内，这项工作将提供一套新颖的分布式算法和合适的分布式代理体系结构。从长远来看，这项工作将通过建立对可伸缩性的科学和技术洞察，为设计下一代适应性和可重新配置的企业提供数学和模拟模型。