Semantic-Oriented Performance Monitoring of Distributed Applications

Monitoring services are an essential component of large-scale computing infrastructures due to providing information which can be used by humans as well as applications to closely follow the progress of computations, to evaluate the performance of ongoing computing, etc. However, the users are usually left alone with performance measurements as to the interpreting and detecting of execution flaws. In this paper we present an approach to the performance monitoring of distributed applications based on semantic information about the monitored objects involved in the application execution. This allows to automate the guidance on what to measure further to come to a source of performance flaws as well to enable reacting on interesting events, e.g. on exceeding SLA parameters. Our research comprises the implementation of a robust system with semantics, which is not biased to an underlying ``physical'' monitoring system, giving the end user the power of intelligent monitoring functionality as well as the independence of the heterogeneity of distributed infrastructures.

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