基于遗传算法的自治计算系统负载分配组合设计模式
Load Distribution Composite Design Pattern for Genetic Algorithm-Based Autonomic Computing Systems
摘要：
当前的自主计算系统是从头开始设计和实现的特设解决方案。在设计软件时，在大多数情况下，两个或多个模式将被组合以解决更大的问题。复合设计模式显示了一种协同作用，使组合不仅仅是其部分的总和，这导致了现成的软件架构。据我们所知，目前还没有关于自主计算领域设计模式组合的研究。在本文中，我们提出了面向模式的软件体系结构，在自主计算系统中使用设计模式组合和多目标进化算法，软件设计师和/或程序员可以利用来驱动他们的工作，以自我优化。该系统的主要目标是通过将人口分布到客户端来减少服务器的负载。我们使用了基于案例的推理，数据库访问和主从设计模式。我们评估我们的架构的有效性与设计模式组成和没有。使用复合设计模式的架构和定量测量。使用一个简单的UML类图来描述体系结构。
英文摘要：
Current autonomic computing systems are ad hoc solutions that are designed and implemented from the scratch. When designing software, in most cases two or more patterns are to be composed to solve a bigger problem. A composite design patterns shows a synergy that makes the composition more than just the sum of its parts which leads to ready-made software architectures. As far as we know, there are no studies on composition of design patterns for autonomic computing domain. In this paper we propose pattern-oriented software architecture for self-optimization in autonomic computing system using design patterns composition and multi objective evolutionary algorithms that software designers and/or programmers can exploit to drive their work. Main objective of the system is to reduce the load in the server by distributing the population to clients. We used Case Based Reasoning, Database Access, and Master Slave design patterns. We evaluate the effectiveness of our architecture with and without design patterns compositions. The use of composite design patterns in the architecture and quantitative measurements are presented. A simple UML class diagram is used to describe the architecture.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
