Parallel and Distribution Simulation Systems
Parallel and Distribution Simulation Systems
Theory of Modelling and Simulation
Theory of Modelling and Simulation
DREAM: A Component Framework for Constructing Resource-Aware, Configurable Middleware
IEEE Distributed Systems Online
Software—Practice & Experience
Simulation Modeling and Analysis (McGraw-Hill Series in Industrial Engineering and Management)
Simulation Modeling and Analysis (McGraw-Hill Series in Industrial Engineering and Management)
Supporting Heterogeneous Architecture Descriptions in an Extensible Toolset
ICSE '07 Proceedings of the 29th international conference on Software Engineering
An overview of the OMNeT++ simulation environment
Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops
Software Architecture Patterns for a Context-Processing Middleware Framework
IEEE Distributed Systems Online
A flexible and scalable experimentation layer
Proceedings of the 40th Conference on Winter Simulation
Scalable processing of context information with COSMOS
DAIS'07 Proceedings of the 7th IFIP WG 6.1 international conference on Distributed applications and interoperable systems
Some desired features for the DEVS architecture description language
Proceedings of the 2011 Symposium on Theory of Modeling & Simulation: DEVS Integrative M&S Symposium
Proceedings of the 2012 Symposium on Theory of Modeling and Simulation - DEVS Integrative M&S Symposium
Traces generation to simulate large-scale distributed applications
Proceedings of the Winter Simulation Conference
An approach for loosely coupled discrete event simulation models and animation components
Proceedings of the Winter Simulation Conference
Building ubiquitous QoC-aware applications through model-driven software engineering
Science of Computer Programming
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In most existing simulators, the outputs of a simulation run consist either in a simulation report generated at the end of the run and summarizing the statistics of interest, or in a (set of) trace file(s) containing raw data samples produced and saved regularly during the run, for later post-processing. In this paper, we address issues related to the management of these data and their on-line processing, such as: (i) the instrumentation code is mixed in the modeling code; (ii) the amount of data to be stored may be enormous, and often, a significant part of these data are useless while their collect may consume a significant amount of the computing resources; and (iii) it is difficult to have confidence in the treatment applied to the data and then make comparisons between studies since each user (model developer) builds its own ad-hoc instrumentation and data processing. In this paper, we propose OSIF, a new component-based instrumentation framework designed to solve the above mentioned issues. OSIF is based on several mature software engineering techniques and frameworks, such as COSMOS, Fractal and its ADL, and AOP.