MODELING THE STABILITY OF A COMPUTER SYSTEM

IF 1 4区 计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE International Journal of Uncertainty Fuzziness and Knowledge-Based Systems Pub Date : 2012-07-09 DOI:10.1142/S0218488512400065
V. López, G. Miñana
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引用次数: 3

Abstract

Performance, reliability and safety are relevant factors when analyzing or designing a computer system. Many studies about on performance are based on monitoring and analyzing data from a computer system. One of the most useful pieces of data is the Load Average (LA) that which shows the load average of the system in the last minute, the sequence of in the last five minutes and the sequence of in the last fifteen last minutes. There are a lot ofmany studies of the system performance based on the load average. This is shown by mean means of monitoring the commands of the operative system, but sometimes they are sometimes difficult to understand and far of removed from human intuition. The aim of this paper is to show demonstrate a new procedure that allows us to determine the stability of a computer system from a list of load average sample data. The idea is shown as an algorithm based in statistic analysis, the aggregation of information and its formal specification. The result is an evaluation of the stability of the load and the computer system by monitoring but without adding any overhead to the system. In addition, the procedure can be used as a software monitor for risk prevention of on any vulnerable system.
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模拟计算机系统的稳定性
性能、可靠性和安全性是分析或设计计算机系统时的相关因素。许多关于性能的研究都是基于对计算机系统数据的监测和分析。最有用的数据之一是负载平均值(Load Average, LA),它显示了系统在最后一分钟内的负载平均值、在最后五分钟内的序列和在最后十五分钟内的序列。基于平均负载的系统性能研究有很多。这是通过监控操作系统的命令来显示的,但有时它们有时很难理解,而且与人类的直觉相去甚远。本文的目的是展示一种新的程序,使我们能够从负载平均样本数据列表中确定计算机系统的稳定性。该思想是一种基于统计分析、信息聚合及其形式化规范的算法。结果是通过监测对负载和计算机系统的稳定性进行评估,但不增加系统的任何开销。此外,该程序还可以作为软件监视器用于任何易受攻击系统的风险预防。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.70
自引率
0.00%
发文量
48
审稿时长
13.5 months
期刊介绍: The International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems is a forum for research on various methodologies for the management of imprecise, vague, uncertain or incomplete information. The aim of the journal is to promote theoretical or methodological works dealing with all kinds of methods to represent and manipulate imperfectly described pieces of knowledge, excluding results on pure mathematics or simple applications of existing theoretical results. It is published bimonthly, with worldwide distribution to researchers, engineers, decision-makers, and educators.
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