Giuseppe Serazzi

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We present the Java Modelling Tools (JMT) suite, an integrated framework of Java tools for performance evaluation of computer systems using queueing models. The suite offers a rich user interface that simplifies the definition of performance models by means of wizard dialogs and of a graphical design workspace. The performance evaluation features of JMT(More)
In this paper we systematically examine various performance issues involved in the coordinated allocation of processor and disk resources in large-scale parallel computer systems. Models are formulated to investigate the I/O and computation behavior of parallel programs and workloads, and to analyze parallel scheduling policies under such workloads. These(More)
This work summarizes our research on the topic of the application of unsupervised learning algorithms to the problem of intrusion detection, and in particular our main research results in network intrusion detection. We proposed a novel, two tier architecture for network intrusion detection, capable of clustering packet payloads and correlating anomalies in(More)
The performance of a system is determined by its characteristics as well as by the composition of the load being processed. Hence, its quantitative description is a fundamental part of all performance evaluation studies. Several methodologies for the construction of workload models, which are functions of the objective of the study, of the architecture of(More)
The Java Modelling Tools (JMT) is an open source suite for performance evaluation, capacity planning and modelling of computer and communication systems. The suite implements numerous state-of-the-art algorithms for the exact, asymptotic and simulative analysis of queueing network models, either with or without product-form solution. Models can be described(More)
It is known that the resources that limit the overall performance of a system are the congested ones, referred to as bottlenecks. From knowledge of bottleneck stations, it is possible, with limited computational effort, to derive asymptotic values of several performance indices. While identifying the bottleneck stations is a well-established practice under(More)
Queuing network models of modern computing systems must consider a large number of components (e.g., Web servers, DB servers, application servers, firewall, routers, networks) and hundreds of customers with very different resource requirements. The complexity of such models makes the application of exact solution techniques prohibitively expensive,(More)