Organisation(s):

Brunel University London – United Kingdom

Department of Physics and Astronomy – University of Catania – Italy

Champion(s):
Mr. Adedeji FABIYI

Other member(s):
Dr. Anastasia ANAGNOSTOU
Dr. Salaheddin DARWISH
Dr. Simon J. E. TAYLOR
Eng. Mario TORRISI
Prof. Roberto BARBERA

Use Case Description

Integration of a Repast-based Infection Model in a Science Gateway
The Repast-based Infection Model is an example of an Agent-Based Simulation Infection Model implemented in the well-known Repast Simphony agent-based simulation toolkit. There are three (3) types of agent to represent, namely: the infected, susceptible and the recovered population. All agents are randomly located in a Grid environment. Susceptible agents try to avoid contact with infected agents. When an infected agent approaches a cell with susceptible agent, it infects one, randomly, selected agent. This susceptible agent then becomes infected and can infect other susceptible agents in turn. The infected, susceptible and recovered agents are the input parameters that the user can modify in order to experiment with different initial conditions. The user can also specify the time (in years) that the simulation will run.


e-Infrastructure Services Exploited

The main outcome of the use case is a JSR 168/286 standard-based “portlet”, which has been integrated in the Africa Grid Science Gateway based on the Catania Science Gateway Framework.

For storing documents, datasets and other products relative to the Repast-based Infection Model, the Sci-GaIA Open Access Repository (OAR) has been adopted. DataCite-issued Digital Object Identifiers (DOIs) are automatically assigned by the OAR to each record to improve its findability, discoverability and reusability. See for example this record.

Current Implementation of the Use Case

Infection Model portlet, Code repositories (sequential version, parallel version)

References

PaperPresentation