INFECTION MODEL PORTLET

About

infectionModel-portlet logo

The infection model is an example of an Agent-Based Simulation Infection Model implemented in the well-known Repast Simphony (repast.sourceforge.net) agent-based simulation toolkit. Agent-based simulation is a highly useful technique that allows individuals and their behaviours to be represented as they interact over time. This means, with appropriate data, agent-based simulation can be used to study various socio-medical phenomena such as the spread of disease and infection in a population.

The aim of this demonstration model is to show how a science gateway could support the study of the spread of disease or infection in a population. As well as having direct healthcare application, it can also be used in the field of health economics to study the cost effectiveness of various infection preventive strategies.

Within the science gateway, the Repast Infection Model has been deployed in a portlet named infectionModel-portlet. This has been developed to enable users to submit experiments with different input parameters and to obtain results. As well as the results output file, the application also has a demonstration graph tool that allows users to see the graphical visualisation of the results.

This shows that science gateways can be developed to support online complex simulations in an extremely easy to use manner. See the Sci-GaIA project web pages and the educational modules to get information on how to implement these applications as well as how science gateways and data repositories can be used to support Open Science.

Installation

This section explains how to deploy and configure the infectionModel-portlet into a Science gateway to submit some preconfigures experitments towards Distributed Computing infrastructures.

1. Move into your Liferay plugin SDK portlets folder and clone the infectionModel-portlet source through the following git command:

git clone https://github.com/csgf/infectionModel-portlet.git

2. Now, move into the just created infectionModel-portlet directory and execute the deploy command:

ant deploy

When the previous command has completed, verify that the portlet is “Successfully autodeployed”, look for a string like this in the Liferay log file under $LIFERAY_HOME/glassfish-3.1.2/domains/domain1/logs/server.log.

3. Then, open your browser and point at your Science Gateway instance and form there click Add > More in the Brunel University category, click on Add button to add this new portlet. Following picture shows the correctly result:

infectionModel-portlet view

As soon as the portlet has been successfully deployed you have to configure:

  1. the list of e-Infrastructures where the application can be executed;
  2. some additional application settings.

To configure the e-Infrastructure, go to the portlet preferences and provide the the right values for the following parameters:

  • Enable infrastructure: A yes/no flag which enables or disable the generic e-Infrastructure;
  • Infrastructure name: A label representing the e-Infrastructure;
  • Infrastructure acronym: The acronym to reference the e-Infrastructure;
  • BDII: The Top BDII for this e-Infrastructure;
  • WMS Hosts: A separated ; list of WMS endpoint for this e-Infrastructure;
  • Proxy Robot host server: The eTokenServer for this e-Infrastructure;
  • Proxy Robot host port: The eTokenServer port for this e-Infrastructure;
  • Proxy Robot secure connection: A true/false flag if the eTokenServer require a secure connection;
  • Proxy Robot Identifier: The MD5SUM of the robot certificate to be used for this e-Infrastructure;
  • Proxy Robot Virtual Organization: The VO for this e-Infrastructure;
  • Proxy Robot VO Role: The VO role for this e-Infrastructure;
  • Proxy Robot Renewal Flag: A true/false Flag to require proxy renewal before it expires;
  • Local Proxy: The path to the proxy if you are using a local proxy;
  • Software Tags: The list of software tags requested by the application.

The following figure shown how the portlet has been configured to run simulation on a cloud based system.

infectionModel-portlet preference

Another important step to have infectionModel-portlet ready to be used is: to create a new entry in GridOperations table of the UsersTracking database, as shown below.

INSERT INTO GridOperation VALUES ('<portal name>' ,'Infection Model portlet');

-- portal name: is a label representing the portal name, you can get the
-- right value from your Science Gateway istance.

Usage

The infectionModel-portlet, has been developed in the contest of the Sci-GaIA project, and it is curretly available on the Africa Grid Science Gateway. You can read more information on how to use this application, after sign in, on its dedicated run page.

As soon as your submitted interaction complete its execution you can exploit the Visualize infection Model result portlet, to see the simulation outputs in a graphical way, like shown in the picture below.

When an authorised user successfully log on, they are presented with the portlet, i.e the infection model portlet, where they can specify all the necessary input parameters of the infection model. After a user has finished specifying the parameters and clicked on the submit button, the jobs can then be submitted to the different Distributed Computing Infrastructures. However, due to limitation of resources, this portlet presents a verson where a number of experiments have been fixed and users can only choose from within a predefined set of expereiments. After submitting a job, users would be notified that their jobs have been successfully submitted and then advised to check the MyJobs portlet, a dedicated portlet where the status of all running jobs can be found. A done job status would be represented by a small folder icon and users can download the output of the infection model for analysis.

The analysis of the infection model result output file, using the visualize portlet, can be seen below:

infectionModel-portlet preference

Contributor(s)

If you have any questions or comments, please feel free to contact us using the Sci-GaIA project dicussion forum (discourse.sci-gaia.eu)

Authors:

Roberto BARBERA - University of Catania (DFA),

Adedeji FABIYI - Brunel University London (BRUNEL),

Simon TAYLOR - Brunel University London (BRUNEL),

Mario TORRISI - University of Catania (DFA)