集群性能评估系统专家决策子系统的设计与实现
发布时间：2019-06-27 15:47
【摘要】：性能分析对构建高效率的计算系统意义重大,但随着云计算的流行,计算系统日益复杂,性能分析工作变得十分困难。而现有的性能分析工具,主要采取用户行为模拟等手段,关注用户体验,监测响应时间、错误率等参数,弱化了分析部分;同时只适用于Web类用户交互应用,无法应用于诸如科学计算等领域。因此,下一代性能分析工具的设计开发工作迫在眉睫。本文基于机器学习算法设计了一种深入挖掘应用各项性能指标内在联系,统筹多指标联合定位应用问题的专家决策系统,解决了现有分析工具定位分析问题能力不足,适用场景有限的问题。本文首先介绍了背景知识及开发实现所涉及的相关技术,并调研和说明了现有分析工具的功能和特点。通过分析专家决策系统在整个性能评估系统中的位置,结合RTC应用分析实例,得出决策系统的工作场景和总体需求。然后,提出了专家决策系统的总体结构,并对、决策系统的关键流程进行了阐述,并给出了决策系统的内外接口。在此基础上,设计了专家决策系统的类图,并针对各个模块中涉及的关键问题,给出了详细的流程设计,完成了决策系统原型的设计和实现工作。随后对专家决策系统进行了功能测试和验证,详细的介绍了关键功能模块的测试用例,测试结果表明功能原型基本符合需求。最后,对专家决策系统的开发设计工作进行了总结,并指出了下一步的几个主要研究方向。
[Abstract]:Performance analysis is of great significance to the construction of high-efficiency computing system, but with the popularity of cloud computing, the computing system is becoming more and more complex, and the performance analysis work becomes very difficult. And the existing performance analysis tool mainly adopts the means of user behavior simulation, so as to pay attention to the parameters such as user experience, monitoring response time, error rate and the like, weaken the analysis part, and can only be applied to the interactive application of the Web user, and can not be applied to the fields such as scientific calculation and the like. Therefore, the design and development of the next-generation performance analysis tool is urgent. This paper, based on the machine learning algorithm, designs an expert decision-making system for deep excavation and application of various performance indexes and integrated multi-index joint positioning and application, and solves the problem that the existing analysis tool's ability to locate and analyze the problem is not enough and the scene is limited. This paper first introduces the background knowledge and the related technology involved in the development, and studies and explains the functions and characteristics of the existing analysis tools. By analyzing the position of the expert decision-making system in the whole performance evaluation system, combined with the analysis example of the RTC application, the working scene and the overall demand of the decision-making system are obtained. Then, the overall structure of the expert decision-making system is put forward, and the key process of the decision-making system is described, and the internal and external interfaces of the decision-making system are given. On this basis, the class diagram of the expert decision-making system is designed, and the detailed process design is given for the key problems involved in each module, and the design and implementation of the prototype of the decision-making system are completed. Then, the function test and verification of the expert decision-making system are carried out, and the test cases of the key function modules are described in detail. The test results show that the functional prototype basically conforms to the requirements. Finally, the development and design of the expert decision-making system are summarized, and the main research directions of the next step are pointed out.
【学位授予单位】：北京邮电大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TP182;TP311.52
本文编号：2506929
[Abstract]:Performance analysis is of great significance to the construction of high-efficiency computing system, but with the popularity of cloud computing, the computing system is becoming more and more complex, and the performance analysis work becomes very difficult. And the existing performance analysis tool mainly adopts the means of user behavior simulation, so as to pay attention to the parameters such as user experience, monitoring response time, error rate and the like, weaken the analysis part, and can only be applied to the interactive application of the Web user, and can not be applied to the fields such as scientific calculation and the like. Therefore, the design and development of the next-generation performance analysis tool is urgent. This paper, based on the machine learning algorithm, designs an expert decision-making system for deep excavation and application of various performance indexes and integrated multi-index joint positioning and application, and solves the problem that the existing analysis tool's ability to locate and analyze the problem is not enough and the scene is limited. This paper first introduces the background knowledge and the related technology involved in the development, and studies and explains the functions and characteristics of the existing analysis tools. By analyzing the position of the expert decision-making system in the whole performance evaluation system, combined with the analysis example of the RTC application, the working scene and the overall demand of the decision-making system are obtained. Then, the overall structure of the expert decision-making system is put forward, and the key process of the decision-making system is described, and the internal and external interfaces of the decision-making system are given. On this basis, the class diagram of the expert decision-making system is designed, and the detailed process design is given for the key problems involved in each module, and the design and implementation of the prototype of the decision-making system are completed. Then, the function test and verification of the expert decision-making system are carried out, and the test cases of the key function modules are described in detail. The test results show that the functional prototype basically conforms to the requirements. Finally, the development and design of the expert decision-making system are summarized, and the main research directions of the next step are pointed out.
【学位授予单位】：北京邮电大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TP182;TP311.52
【参考文献】
相关期刊论文 前1条
1 吴江;黄晟青;蔡骏;;互联网购物网站用户体验设计研究[J];包装工程;2012年08期
，本文编号：2506929
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