通过语义处理进行SLA遵从性监控

L. Coppolino, D. Mari, L. Romano, V. Vianello
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引用次数: 4

摘要

对于it服务提供商来说,用户满意度是他们公司成功的关键。服务提供者需要了解其用户的需求,并将其转化为自己的业务目标。服务故障可能会对用户满意度产生负面影响,因此检测和解决业务流程级别的故障已成为任何it公司的关键任务需求。不幸的是,即使在业务级别出现故障,描述此故障的数据也分散到系统的低级组件中,并以任何业务分析人员都无法理解的形式进行存储。在取证分析中,通过采用数据挖掘和数据仓库技术来弥补收集到的数据与业务分析人员的知识之间的语义差距,但这些技术由于其较长的延迟而不适合实时业务流程分析。本文的目的是提供一个框架,允许业务流程分析人员近乎实时地调查业务服务的交付状态。该框架需要第一个设置阶段,在此阶段领域专家定义描述低级概念的本体以及业务事件和收集到系统中的数据之间的映射,然后它为仅了解业务逻辑的业务流程分析师提供一种近乎实时地调查服务交付状态的方法。采用复杂事件处理(CEP)引擎等新兴技术,能够实时处理海量数据,保证了该框架近实时处理数据的能力。此外,本文还展示了一个来自电信行业的案例研究,旨在证明该框架在实际场景中的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SLA compliance monitoring through semantic processing
For IT-services providers, user satisfaction is the key for their company's success. Service providers need to understand the requirements of their users and translate them into their own business goals. Service malfunctions could have negative impact on user satisfaction, therefore to detect and resolve failures of the business process level has become a mission critical requirement for any IT-company. Unfortunately, even if a failure manifests itself at the business level, the data describing this failure are scattered into low level components of the system and stored with a formalism incomprehensible to any business analyst. In forensic analysis, the semantic gap between collected data and business analysts' knowledge is closed by the adoption of data-mining and data-warehousing techniques, but such techniques are unsuitable for real-time business process analysis due to their long latencies. The purpose of this paper is to present a framework that allows business process analysts investigating the delivery status of business services in near real-time. The framework requires a first set up phase where domain specialists define ontologies describing low level concepts and the mapping among business events and data gathered into the system, and then it provides business process analysts, aware only of business logics, with a way to investigate service delivery status in near real time. The capability of the framework of processing data in near real time is ensured by the use of emerging technologies such as complex event processing (CEP) engines, which are able to process in real time huge amount of data. Furthermore in the paper, it is also showed a case study from the telecommunication industry aiming to demonstrate the applicability of the framework in a real word scenario.
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