SIM, a Semantic Instrumentation and Monitoring Solution for Large Scale Reasoning Systems

2011 IEEE Fifth International Conference on Semantic Computing Pub Date : 2011-09-18 DOI:10.1109/ICCP.2011.6047861

I. Toma, Mihai Chezan, R. Brehar, S. Nedevschi, D. Fensel

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引用次数: 3

Abstract

One central task to the idea of Semantic Web is reasoning over semantic descriptions of web pages and information items available on the Web. A flagship project that is advancing the state of the art in reasoning with Web scale data is the Large Knowledge Collider (LarKC). Having a plug gable architecture, LarKC enables the interested users to test their reasoning approaches with very little overhead. In this context, instrumenting and monitoring of the large scale reasoning systems and their components becomes essential for verifying and assuring high performance, adaptability and well functioning. These aspects are in the end vital for any reasoning experiment. We introduce SIM, Semantic Instrumentation and Monitoring, a semantic-based instrumentation and monitoring solution. SIM enables the instrumentation and monitoring of LarKC applications in particular and any large scale reasoning system in general. It offers the means for developers to specify the metrics of interest, to instrument the code, to collect and observe how well the system and its components are performing. We identify a large set of relevant metrics for monitoring and provide ontological models for them. Finally we discuss the architecture and the role of each component and tool which is part of SIM.

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大规模推理系统的语义检测与监控解决方案

语义网思想的一个中心任务是对Web上可用的网页和信息项的语义描述进行推理。大型知识对撞机(LarKC)是一个旗舰项目，它推动了Web规模数据推理技术的发展。LarKC采用了插拔式架构，使感兴趣的用户能够以很少的开销测试他们的推理方法。在这种情况下，大型推理系统及其组成部分的仪器和监测对于验证和确保高性能、适应性和良好运作至关重要。这些方面最终对任何推理实验都是至关重要的。我们介绍了SIM，语义仪表和监控，一个基于语义的仪表和监控解决方案。SIM可以对LarKC应用程序以及任何大型推理系统进行检测和监控。它为开发人员提供了指定感兴趣的度量标准、编写代码、收集和观察系统及其组件的执行情况的方法。我们确定了一组用于监控的相关度量，并为它们提供了本体模型。最后讨论了SIM的体系结构和各个组件和工具的作用。

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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2011 IEEE Fifth International Conference on Semantic Computing

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