Proposing a Layer to Integrate the Sub-classification of Monitoring Operations Based on AI and Big Data to Improve Efficiency of Information Technology Supervision

IF 0.5 Q4 COMPUTER SCIENCE, THEORY & METHODS Applied Computer Systems Pub Date : 2022-06-01 DOI:10.2478/acss-2022-0005
Ahmed Yassine Chakor, Azmani Monir, Azmani Abdellah
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引用次数: 2

Abstract

Abstract Intelligent monitoring of a computer network provides a clear understanding of its behaviour at various times and in various situations. It also provides relief to support teams that spend most of their time troubleshooting problems caused by hardware or software failures. This type of monitoring ensures the accuracy and efficiency of the network to meet the expectations of its users. However, to ensure intelligent monitoring, it is necessary to start by automating this process, which often leads to long and costly interventions. The success of such automation implies the establishment of predictive maintenance as a prerequisite for good preventive maintenance governance. However, even when it is practiced effectively, preventive maintenance requires a great deal of time and the mobilization of several full-time resources, especially for large IT structures. This paper gives an overview of the monitoring of a computer network and explains its process and the problems encountered. It also proposes a method based on machine learning to allow for prediction and support decision making to proactively anticipate interventions.
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提出一层整合基于人工智能和大数据的监控业务分类,提高信息化监管效率
计算机网络的智能监控提供了对其在不同时间和不同情况下的行为的清晰理解。它还为那些花费大部分时间排除由硬件或软件故障引起的问题的支持团队提供了帮助。这种类型的监控保证了网络的准确性和效率,以满足其用户的期望。然而,为了确保智能监控,有必要从自动化这个过程开始,这通常会导致长期和昂贵的干预。这种自动化的成功意味着建立预测性维护,作为良好预防性维护治理的先决条件。然而,即使有效地实施了预防性维护,也需要大量的时间和几个全职资源的动员,特别是对于大型it结构。本文介绍了计算机网络监控的概况,阐述了计算机网络监控的过程和遇到的问题。它还提出了一种基于机器学习的方法,允许预测和支持决策,以主动预测干预措施。
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来源期刊
Applied Computer Systems
Applied Computer Systems COMPUTER SCIENCE, THEORY & METHODS-
自引率
10.00%
发文量
9
审稿时长
30 weeks
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