Journal of Simulation
Special Issue Call for Papers:
Modeling and Simulation
in the Cloud Computing era
Submission Deadline: January 15th, 2021
Click here to submit
Modelling and Simulation (M&S) is one of the most important and effective methods for designing and studying complex systems in a variety of industrial and scientific domains such as transport, energy and aerospace. M&S methods, tools, and techniques allow the effective analysis and evaluation of different design alternatives by avoiding risks, costs and failures associated with extensive field experimentation; this is crucial when one cannot perform exhaustive tests on the real world because they are too expensive in terms of cost or time.
Cloud computing has received considerable interest by the scientific and industrial community because, thanks to advances in Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS), it allows the implementation of solutions to exploit computing and data storage capacity, network resources, and scalability rapidly. In this context, Cloud, Edge and Fog computing can offer suitable services to share and collaborate on M&S and perform complex simulation experiments faster and more efficiently using Modelling and Simulation as a Service (MSAAS). While MSAAS offers an ever-expanding number of possibilities, it also entails a considerable number of challenges. One of the key challenges is related to the fact that cloud infrastructures are massive at all scales, therefore developing MSAAS solutions is difficult without an adequate knowledge of the involved platforms and technologies.
The aim of this special issue is to provide a comprehensive guide on current ideas and results in M&S for Cloud computing and vice versa. Specifically, the issue aims at: (i) presenting the current state-of-the-art about M&S environments and frameworks based on open standards, recent extensions, and innovations related to Cloud computing technologies; and, (ii) identifying potential research directions and technologies that will drive innovations in M&S on Cloud Computing Infrastructures. Additionally, the special issue will also look for submissions employing Complex Systems related methodologies, toolkits, and frameworks such as involving Complex Social Networks, and Agent-based Modelling, among others.
Nowadays, there is research aiming at investigating the impact of Cloud computing on M&S techniques and methodologies. We believe that a journal special issue on “Modeling and Simulation in the Cloud Computing era” will be a timely contribution to a field that is gaining considerable research interest and is expected to be of increasing interest to commercial developers in a wide range of application domains. Moreover, we believe that the methodological and technological trends in the convergence of Cloud Computing and M&S disciplines need to be explored more in order to provide an exclusive research roadmap to both Cloud Computing and M&S communities. Furthermore, this special issue involves strongly scientific programming aspects related to mathematical models and quantitative analysis techniques that use heavily cloud computing solutions.
Papers for this special issue are expected to come from the leading experts in research fields such as, High-performance simulation in the Cloud, Modelling and Simulation, System Dependability and Performance Analyses through Big data in the cloud as well as Parallel and Distributed simulation through cloud services, belonging to several industrial and academic research domains. Simulation Optimization approaches levering Cloud Computing are also of interest. This special issue will collect these experts and their work in a comprehensive, coordinated and integrated single resource. It is anticipated that this special issue will establish a pathway for the integrated use of existing methodologies and tools for the development of future-generation of simulators based on Cloud computing services. Thus, the papers of this special issue will not only serve as a snapshot of the state-of-the-art and identify future developments, but will also have an emphasis on covering the fundamentals so that they can be used as references for future research activities.
High-performance simulation in the Cloud, Modelling and Simulation, Systems Design and Analysis, Parallel and Distributed simulation through cloud services, System Dependability and Performance Analyses through Big data in the cloud.
Lead Guest Editor:
Alberto Falcone (firstname.lastname@example.org), Department of Informatics, Modeling, Electronics and Systems Engineering (DIMES), University of Calabria, Italy.
Alfredo Garro (email@example.com), Department of Informatics, Modeling, Electronics and Systems Engineering (DIMES), University of Calabria, Italy.
Navonil Mustafee (firstname.lastname@example.org), Centre for Simulation, Analytics and Modelling (CSAM), University of Exeter Business School, Exeter, United Kingdom.
Muaz A. Niazi (email@example.com), Computer Science Department, COMSATS university, Islamabad, Pakistan.
Gabriel Wainer (firstname.lastname@example.org), Department of Systems and Computer Engineering, Carleton University, Canada.
Peer review of manuscripts submitted to the special issue is conducted according to agreed and ethical peer review standards (https://authorservices.taylorandfrancis.com/ethics-for-authors/) for the publication of articles, so as to ensure the integrity of peer review and assure the quality of published articles.
All authors, peer reviewers, and referees comply with the Publisher's guidelines on the ethics of journal publishing (https://authorservices.taylorandfrancis.com/ethics-for-authors/) and respect the confidentiality of the review process, and that material under review shall be held to be the contributing author's intellectual property unless and until otherwise assigned.
Please indicate that your article is for a special issue during the submission process; both in your cover letter and when asked by the ScholarOne system. You should be able to select the special issue title from a drop-down menu, which will help the Editorial Office and the Editors to correctly allocate your paper for peer review.