Comparing Centralized and Distributed Approaches for Operational Impact Analysis in Enterprise Systems

Mark Moss
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引用次数: 7

Abstract

Enterprises have become increasingly dependent on information technology capabilities (e.g. secure remote access for mobile users) to support their business objectives. Consequently, determining which users are affected by component failures remains a very important and challenging problem. Analyzing operational impact requires an understanding of how the system components are inter-dependent, and when the components are actually employed by the system users. Our approach collects monitoring data from the end systems. Data mining and analysis are used to infer system dependency topologies and usage patterns. We compare centralized, partially distributed, and fully distributed implementation approaches using computers connected to a campus-wide system. The results show that distributed approaches can be used to minimize the amount of data transmitted between systems, without significantly reducing the overall quality of the impact analysis. These distributed approaches will support efficient and scalable impact assessment in modern enterprise systems.
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比较企业系统中操作影响分析的集中式和分布式方法
企业越来越依赖信息技术能力(例如移动用户的安全远程访问)来支持其业务目标。因此,确定哪些用户受到组件故障的影响仍然是一个非常重要和具有挑战性的问题。分析操作影响需要了解系统组件是如何相互依赖的,以及系统用户实际使用组件的时间。我们的方法是从终端系统收集监测数据。数据挖掘和分析用于推断系统依赖拓扑和使用模式。我们比较集中式、部分分布式和完全分布式的实现方法,使用连接到校园系统的计算机。结果表明,分布式方法可用于最小化系统之间传输的数据量,而不会显著降低影响分析的整体质量。这些分布式方法将支持现代企业系统中高效和可伸缩的影响评估。
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