Distributed Interactive Real-time Multimedia Applications: A Sampling and Analysis Framework

Abstract

The advancements in distributed computing have driven the emergence of service-based infrastructures that allow for on-demand provision of IT assets. However, the complexity of characterizing an application’s behavior, and as a result the potential offered level of Quality of Service (QoS), introduces a number of challenges in the data collection and analysis process on the Service Providers’ side, especially for real time applications. The aforementioned complexity is increased due to additional factors that influence the application’s behavior, such as real time scheduling decisions, percentage of a node assigned to the application or application-generated workload. In this paper, we present a framework developed under the IRMOS EU-funded project that enables the sampling and gathering of the necessary dataset in order to analyze an application’s behavior. Processing of the resulting dataset is also conducted in order to extract useful conclusions regarding CPU allocation and scheduling decisions effect on the QoS. We demonstrate the operation of the proposed framework and evaluate its performance and effectiveness using an interactive real-time multimedia application, namely a webbased eLearning scenario.

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