Parallel and Distributed Simulation (PADS) Research Group

University of Bologna. Department of Computer Science and Engineering (DISI)

Welcome to the PADS homepage, you can find some information about this research group, the active projects and the related publications.

A lot of our research work is based on a new Parallel and Distributed Simulation (PADS) middleware (ARTÌS). The GAIA framework provides a migration-based approach to the simulation. The ARTÌS middleware and the GAIA framework are available for educational and research purposes.

Please feel free to contact us for any question or comment.

In this paper we perform a systematic literature review of multilevel simulation applied to human mobility and behavior, to identify research trends and contribute towards a better understanding of techniques, methodologies and terminology used within this research area. At the end of our analysis we uncover some recurrent modeling and simulation patterns that appear frequently within specific research areas, and we classify these methodological patterns along several dimensions such as modeling type and level of detail.

For more information follow this link.

In this paper we present a study on the intricate problem of the simulation of large scale complex networks. The complexity of the simulation is due to the need to represent networks with a high number of nodes and links, but even more to the need to model interactions among network nodes. We focus on discrete-event simulation, a simulation methodology that enables both sequential (i.e. monolithic) and parallel/distributed simulation (i.e. PADS) approaches.

For more information follow this link.

A preview version of the LUNES-Blockchain simulator (i.e. agent-based simulation of DLTs and Blockchains) has been published in form of source code in the Download section. LUNES-Blockchain is based on the ARTÌS/GAIA simulators.

In this paper we focus on Internet-based simulation, a form of distributed simulation in which a set of execution units that are physically located around the globe work together to run a simulation model. We simulate a wireless model over a real Internet-based distributed simulation setup, and evaluate the scalability of the simulator with and without the use of adaptive strategies for both communication overhead reduction and load-balancing enhancement.

For more information follow this link.

In this paper, we describe LUNES-Blockchain, an agent-based simulator of blockchains that is able to exploit Parallel and Distributed Simulation (PADS) techniques to offer a high level of scalability.

For more information follow this link.

In this paper we propose two parallel solutions to the DDM problem that can operate effectively on shared-memory multiprocessors.

For more information follow this link.