计算机应用 ›› 2010, Vol. 30 ›› Issue (06): 1642-1644.

• 软件过程技术与中文信息处理 • 上一篇    下一篇

基于软件再生理论的分布式自适应性能监控系统设计

游静1,徐康宁2,王洪元3,杨亚南3,高晋树3   

  1. 1. 江苏工业学院
    2.
    3. 江苏工业学院 信息科学与工程学院
  • 收稿日期:2009-12-25 修回日期:2010-02-10 发布日期:2010-06-01 出版日期:2010-06-01
  • 通讯作者: 游静
  • 基金资助:
    江苏省自然科学基金项目;江苏省高校自然科学基础研究项目

Design of distributed and self-adaptive performance monitoring system based on software rejuvenation

  • Received:2009-12-25 Revised:2010-02-10 Online:2010-06-01 Published:2010-06-01
  • Supported by:
    ;the Natural Science Fundamental Research Program of Higher Education of Jiangsu Province

摘要: 软件再生理论认为,计算系统运行过程中的系统资源损耗是影响系统性能的主要因素。设计一个性能监控系统,通过采集和分析资源使用情况,适时释放被损耗的资源可以有效保证系统的持续高性能。监控系统采用C/S模式以减轻监控端的负载,保证监控端的轻量级,同时实现对监控端的异步监控;基于自组织映射网络对数据的分析,实现对监控端监控参数的自适应调节;提供多种数学模型对系统性能变化进行分析和预测;设计了简单有效的决策方法支持系统的重启控制;最后通过实验证明自适应采集策略有效减少了数据采集和传输量,保证了监控端的轻量级、低负载,尽可能地降低了监控系统本身对被监控系统的影响。

关键词: 性能监控系统, 软件再生, 自组织映射, 自适应分析

Abstract: According to the theory of software rejuvenation, the system resources wastage is the major factor of the degradation of computing system. It is useful for the maintenance of system performance to design a performance monitoring system. The monitoring system releases the resources wasted at the appropriate time by collecting and analyzing the run-time system resources data. C/S mode was used in the monitoring system to reduce the load of monitored system, to ensure the lightweight of monitor-side, to achieve asynchronous monitoring of monitored system. The self-adaptive adjustment of monitoring system parameters was implemented based on self-organization map net. Several models were provided to analyze and forecast the performance of system. A simple decision-making method was designed to support the control of reboot. At last the experiments demonstrate that the self-adaptive collection strategy is effective to reduce the data collected and transmitted, to ensure the lightweight and low-load of monitor-side, to minimize the impact of monitoring system on monitored system.

Key words: performance monitoring system, software rejuvenation, self-organization map net, adaptive analysis