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首页> 外文期刊>International journal of intelligent information and database systems >Logical inventory database integration into alarm correlations discovery environment
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Logical inventory database integration into alarm correlations discovery environment

机译：将逻辑库存数据库集成到警报关联发现环境中

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摘要

Network elements from telecommunications network have capability to generate unsolicited messages known as notifications. In the case of network resource malfunctioning, notification, called alarm, is carrying details about malfunction. When general network problem occurs, it is represented as a sequence of alarms coming from one or more different network elements. Typically, alarms are processed by network operators, requiring response action within reasonable time interval. If network operator is overloaded with huge number of alarms, time needed for network problem recognition may increase. The worst case scenario - problem will be detected after occupation of call centre by customer calls. Hence, it is necessary to recognise critical network problems automatically, reducing and correlating incoming alarms. This paper describes architecture of alarm basic correlation discovery environment (ABCDE). It is aimed for correlation rules discovery for both types of correlations described in paper: low-level ('smart' filtrations) and high-level (recognition of typical alarm sequences) correlations. Potential usage of mathematical Apriori algorithm is presented, together with integration of logical inventory database, used for including network structure knowledge in correlation process. Finally, some experimental results are presented.
机译：来自电信网络的网元具有生成未经请求的消息（称为通知）的能力。在网络资源发生故障的情况下，称为警报的通知会携带有关故障的详细信息。当发生一般网络问题时，它表示为来自一个或多个不同网络元素的一系列警报。通常，警报由网络运营商处理，要求在合理的时间间隔内采取响应措施。如果网络操作员的警报数量过多，则网络问题识别所需的时间可能会增加。最坏的情况是-客户呼叫占用呼叫中心后，将检测到问题。因此，有必要自动识别关键的网络问题，以减少并关联传入的警报。本文介绍了警报基本相关发现环境（ABCDE）的体系结构。它旨在针对论文中描述的两种类型的相关性进行相关性规则发现：低级（“智能”过滤）和高级（典型警报序列的识别）相关性。提出了数学Apriori算法的潜在用途，以及逻辑库存数据库的集成，用于将网络结构知识包括在关联过程中。最后，给出了一些实验结果。

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