Ani, Uchenna Daniel, Watson, Jeremy McKendrick, Carr, Madeline, Cook, Al, Nurse, Jason R. C. (2020) A Review of the Use and Utility of Industrial Network-Based Open Source Simulators: Functionality, Security, and Policy Viewpoints. Journal of Defense Modeling and Simulation, . ISSN 1548-5129. E-ISSN 1557-380X. (doi:10.1177/1548512920953499) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:82405)
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Official URL: http://dx.doi.org/10.1177/1548512920953499 |
Abstract
Simulation can provide a useful means to understand issues linked to industrial network operations. For transparent, collaborative, cost-effective solutions development, and to attract the broadest interest base, simulation is critical and Open Source suggested, because it costs less to access, install, and use. This study contributes new insights from security and functionality characteristics metrics to underscore the use and effectiveness of Open Source simulators. Several Open Source simulators span applications in communications and wireless sensor networks, industrial control systems, and Industrial Internet of Things. Some drivers for their use span; supported licence types, programming languages, operating systems platforms, user interface types, documentation and communication types, citations, code commits, and number of contributors. Research in these simulators is built around performance and optimisation relative to flexibility, scalability, mobility, and active user support. No single simulator addresses all these conceivable characteristics. In addition to modelling contexts that match real-world scenarios and issues, an effective Open Source simulator needs to demonstrate credibility, which can be gained partly through actively engaging experts from interdisciplinary teams along with user contributions integrated under tight editorial controls. Government-led policies and regulations are also necessary to support their wider awareness and more productive use for real-world purposes.
Item Type: | Article |
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DOI/Identification number: | 10.1177/1548512920953499 |
Subjects: |
Q Science T Technology |
Divisions: |
Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts |
Depositing User: | Jason Nurse |
Date Deposited: | 10 Aug 2020 13:41 UTC |
Last Modified: | 05 Nov 2024 12:48 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/82405 (The current URI for this page, for reference purposes) |
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