计算机与现代化 ›› 2020, Vol. 0 ›› Issue (08): 76-81.doi: 10.3969/j.issn.1006-2475.2020.08.012

• 网络与通信 • 上一篇    下一篇

大规模负载生成客户端影响因素研究

  

  1. (1.南京航空航天大学计算机科学与技术学院,江苏南京210016;
    2.软件新技术与产业化协同创新中心,江苏南京210023)
  • 收稿日期:2019-12-05 出版日期:2020-08-17 发布日期:2020-08-17
  • 作者简介:晋文明(1994-),男,安徽当涂人,硕士研究生,研究方向:软件分析与测试,E-mail: gmnsjxmm@163.com; 颜硕彦(1994-),男,江苏淮安人,硕士研究生,研究方向:软件分析与测试; 钱巨(1981-),男,江苏扬州人,副教授,硕士生导师,博士,研究方向:软件分析与测试。
  • 基金资助:
    总装备部预研项目(170441402030)

Study on Client-side Factors Affecting Large-scale Load Generation

  1. (1. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;
    2. Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing 210023, China)
  • Received:2019-12-05 Online:2020-08-17 Published:2020-08-17

摘要: 为保障大型线上软件系统服务质量的可靠性,有必要对其进行有效的大规模负载测试。然而,现有研究主要关注待测服务端性能表现、客户端负载生成模型、客户端资源分配等方面,很少涉及客户端负载生成能力,客户端负载生成的相关影响因素缺乏深入分析与量化研究,难以指引经济高效地大规模负载生成。鉴于此,本文从负载生成机制和测试集群构建2个方面实验研究影响客户端负载生成的因素,依据能力指标得出一组大规模负载生成的数据结论。本文为测试人员在客户端发起大规模负载提供了数据参考,可帮助降低大规模负载测试的成本。

关键词: 负载测试, 客户端负载生成能力, 负载生成机制, 测试集群, 能力指标

Abstract: For large online software systems, it is often necessary to conduct effective large-scale load testing to ensure the reliability of their services. However, the existing research mainly focuses on the server-side performance, client-side load generation models and client-side resource allocation, little work concerns on the client-side load generation ability. There lack detailed analysis and studies on the factors that may affect client-side load generation to guide large-scale load generation. To this end, this paper experimentally studies the factors affecting client-side load generation from two perspective: load generation mechanism and test cluster construction, comes to a set of data conclusions for large-scale load generation based on capability indicators. This paper provides data reference for testers to generate large-scale load on the client, which may help reduce the cost of large-scale load testing.

Key words: load testing, client load generation capability, load generation mechanism, test cluster, capability indicator

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