计算机与现代化 ›› 2021, Vol. 0 ›› Issue (03): 1-6.

• 算法设计与分析 •    下一篇

基于Laguerre 前向神经网络的信息服务性能建模方法 

  

  1. (1.华北计算技术研究所,北京100083;2.军事科学院,北京100091)
  • 出版日期:2020-03-30 发布日期:2021-03-24
  • 作者简介:宋鑫(1994—),男,辽宁阜新人,硕士研究生,研究方向:架构仿真,E-mail: sx-hz@163.com; 樊志强(1983—),男,内蒙古呼和浩特人,高级工程师,博士后,研究方向:软件体系结构。

Information Service Performance Modeling Based on Laguerre FNN 

  1. (1. North China Institute of Computing Technology, Beijing 100083, China;  
     2. Academy of Military Sciences, Beijing 100091, China)
  • Online:2020-03-30 Published:2021-03-24

摘要: 系统架构是信息系统的设计和蓝图,系统架构仿真可以预先估计所建设的系统能否满足设计预期,但目前主流的架构仿真方法缺乏在系统生命周期的早期进行服务性能属性准确预测的手段。本文针对此问题,以信息服务性能建模为研究目标,首先按照信息服务的功能对其进行3个层次的分类,并对每个类别的信息服务提供定义和影响该类服务性能属性的因素。进一步,提出基于Laguerre 前向神经网络的信息服务性能建模方法,分析采用Laguerre 前向神经网络的优点和原因。最后,以信息检索服务为例,提出6个影响信息检索服务执行所需机器周期数的因素,采用消融实验和对比实验验证本文提出的信息服务性能建模方法的可行性。 

关键词: 性能建模, 信息服务, 体系结构仿真, Laguerre前向神经网络 

Abstract: System architecture is the design and blueprint of information system. System architecture simulation can estimate in advance whether the built system can meet the design expectation, but the current mainstream architecture simulation method lacks the means to accurately predict the service performance attribute in the early stage of the system life cycle. Aiming at this problem, this paper takes information service performance modeling as the research goal. Firstly, it classifies information service at three levels according to its functions, and provides the factors that define and influence the performance attributes of each type of information service. Furthermore, an information service performance modeling method based on Laguerre forward neural network is proposed, and the advantages and reasons of Laguerre forward neural network are analysised. Finally, taking information retrieval service as an example, six factors affecting the number of machine cycles required for the execution of information retrieval service are proposed. Ablation experiments and comparative experiments are used to verify the feasibility of the information service performance modeling method proposed in this paper. 

Key words: performance modeling, information service, architecture simulation, Laguerre forward neural network