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Related Experiment Video

Updated: May 27, 2026

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem

Published on: February 3, 2021

An efficient approach to the deployment of complex open source information systems.

Truong Van Chi Cong¹, Eildert Groeneveld

¹Institute of Farm Animal Genetics (FLI), Höltystrasse 10, 31535 Neustadt/Mariensee, Germany.

|November 22, 2011

Summary

Deploying complex component-based software across platforms like Linux and Windows is challenging due to dependencies. Virtualization technology offers an efficient, low-cost solution for deploying information systems, benefiting developers and users.

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Last Updated: May 27, 2026

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem

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Area of Science:

Computer Science
Software Engineering
Bioinformatics

Background:

Complex open source information systems often rely on third-party components, leading to intricate dependency management.
Deploying these systems across diverse operating systems (e.g., Linux, Windows) presents significant installation and configuration challenges.

Purpose of the Study:

To propose and discuss an efficient approach for deploying component-based information systems on multiple platforms.
To leverage virtualization technology to simplify the deployment process and resolve cross-platform dependencies.

Main Methods:

Utilizing virtualization technology to create a unified deployment environment.
Implementing a web-based integrated information system for molecular genetics laboratories as a case study.

Main Results:

Successfully deployed a complex information system on different platforms using the proposed virtualization approach.
Demonstrated a simplified and efficient deployment process, reducing complexity for end-users and developers.

Conclusions:

Virtualization technology provides a cost-effective and efficient solution for deploying component-based information systems across various platforms.
The approach enhances usability and accessibility of complex software in research environments like molecular genetics labs.