云监测平台的海量测量数据分析技术研究与实现

发布时间：2019-02-09 20:03

【摘要】：21世纪是信息的时代,信息交换已经成为人类生活最重要的组成之一。网络作为信息交换的主要载体,已经成为社会最重要的基础设施。移动互联网、物联网和车联网等概念的兴起,证明网络已经成为社会生活的核心；教育学术、商业经济和娱乐文化等方方面面都离不开网络的支撑。随着人们对网络越来越依赖,网络的规模也越来越庞大,人们对网络性能的要求也越来越高。如何保证规模庞大的网络的有效性、可靠性和稳定性,如何科学高效的管理网络,以及如何在当前网络技术上演进出更加先进的网络技术已经成为众多学者和研究机构的研究热点。而这些问题的解决依赖对网络进行有效的测量,并通过计算测量数据来分析网络性能。本文将论述云监测平台的海量测量数据分析技术,旨在通过分析大规模网络测量得到的海量测量数据来评价当前被测量网络性能。本文论述的测量数据分析技术分为测量数据分析算法和测量数据分析系统两部分。测量数据分析算法提供一种海量测量数据处理方法,通过对海量的测量数据进行运算来分析被测量网络的性能状态。测量数据分析系统是对测量数据分析算法的系统实现。测量数据分析系统采用云计算编程模型对分析算法进行实现,旨在依托云计算强大的存储和计算能力,向网络管理人员提供一种快速处理海量测量数据的工具。本文首先介绍云监测平台的海量测量数据分析技术的研究背景和研究意义,并对当前的研究技术进行介绍,其中包括了现有的网络测量方法和性能评价方法。其次,本文将讨论测量数据分析系统的设计需求和系统需求,确定测量数据分析系统的设计目标、实现原则、功能需求和性能需求。然后,本文将着重介绍测量数据分析算法,其中包括通过计算海量测量数据分析路径性能的综合指标法和能够准确分析网络性能的低耦合网络性能分析法。之后,本文将讨论测量数据分析系统整体结构和各部分结构,从系统实现角度介绍测量数据分析系统。最后,本文采用几组实验来介绍云监测平台的海量测量数据分析技术在实际场景中的应用,以实例证明其在实际应用中的价值。
[Abstract]:The 21st century is the era of information, information exchange has become one of the most important components of human life. As the main carrier of information exchange, network has become the most important infrastructure of society. The rise of the concepts of mobile Internet, Internet of things and car networking proves that the network has become the core of social life; the education, academic, business economy and entertainment culture can not be separated from the support of the network. As people rely more and more on the network, the scale of the network is becoming larger and larger, and the demand for network performance is becoming higher and higher. How to ensure the effectiveness, reliability and stability of the large-scale network, how to manage the network scientifically and efficiently, And how to evolve more advanced network technology in the current network technology has become the research hotspot of many scholars and research institutions. The solution of these problems depends on the effective measurement of the network and the analysis of the network performance by calculating the measurement data. This paper will discuss the massive measurement data analysis technology of cloud monitoring platform, which aims to evaluate the performance of the measured network by analyzing the massive measurement data obtained from the large-scale network measurement. The technique of measuring data analysis is divided into two parts: measurement data analysis algorithm and measurement data analysis system. The measurement data analysis algorithm provides a massive measurement data processing method to analyze the performance state of the measured network through the operation of the massive measurement data. The measurement data analysis system is the system realization of the measurement data analysis algorithm. The measurement data analysis system uses the cloud computing programming model to implement the analysis algorithm, which aims to provide network managers with a tool to deal with massive measurement data quickly, relying on the powerful storage and computing capabilities of cloud computing. This paper first introduces the research background and significance of cloud monitoring platform mass measurement data analysis technology, and introduces the current research technology, including the existing network measurement methods and performance evaluation methods. Secondly, this paper will discuss the design requirements and system requirements of the measurement data analysis system, and determine the design objectives, realization principles, function requirements and performance requirements of the measurement data analysis system. Then, this paper will focus on the measurement data analysis algorithm, including the comprehensive index method to analyze the path performance of mass measurement data and the low-coupling network performance analysis method which can accurately analyze the network performance. After that, this paper will discuss the whole structure and each part structure of the measurement data analysis system, and introduce the measurement data analysis system from the point of view of the system implementation. Finally, this paper uses several experiments to introduce the application of cloud monitoring platform's massive measurement data analysis technology in the actual scene, and proves its value in practical application by an example.
【学位授予单位】：北京邮电大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP393.0

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