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 applicationgenerated
 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.