JMT

Author:

Bertoli Marco1,Casale Giuliano2,Serazzi Giuseppe1

Affiliation:

1. Politecnico di Milano, Milano, Italy

2. College of William and Mary, Williamsburg, VA

Abstract

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 span a wide range of state-of-the-art methodologies including discrete-event simulation, mean value analysis of product-form networks, analytical identification of bottleneck resources in multiclass environments, and workload characterization with fuzzy clustering. The discrete-event simulator supports several advanced modeling features such as finite capacity regions, load-dependent service times, bursty processes, fork-and-join nodes, and implements spectral estimation for analysis of simulative results. The suite is open-source, released under the GNU general public license (GPL), and it is available for free download at: http://jmt.sourceforge.net.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Cited by 138 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Performance Modeling of Distributed Data Processing in Microservice Applications;ACM Transactions on Modeling and Performance Evaluation of Computing Systems;2024-08-20

2. Sync-Millibottleneck Attack on Microservices Cloud Architecture;Proceedings of the 19th ACM Asia Conference on Computer and Communications Security;2024-07

3. ChainNet: A Customized Graph Neural Network Model for Loss-Aware Edge AI Service Deployment;2024 54th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN);2024-06-24

4. Approximating Fork-Join Systems via Mixed Model Transformations;Companion of the 15th ACM/SPEC International Conference on Performance Engineering;2024-05-07

5. Neural Density Estimation of Response Times in Layered Software Systems;IEEE Transactions on Software Engineering;2024-03

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