A. Falcone, A. Garro, N. Mustafee, M. Niazi, Gabriel A. Wainer
{"title":"社论:云计算时代的建模与仿真特刊","authors":"A. Falcone, A. Garro, N. Mustafee, M. Niazi, Gabriel A. Wainer","doi":"10.1080/17477778.2022.2080009","DOIUrl":null,"url":null,"abstract":"Modelling and Simulation (M&S) represents one of the fundamental methods to design and study complex systems in many industrial and scientific domains such as transport, energy, and aerospace. M&S techniques enable the analysis and evaluation of many design alternatives while avoiding risks, costs, and failures that come with experimentations on the real system; this opportunity becomes crucial, when realworld tests are too costly to conduct in terms of safety, time, and other resources (Fujimoto et al., 2017). Cloud Computing has captured the interest of the scientific and industrial communities because of the benefits provided by its service models, i.e., Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). These services allow developers to rapidly implement solutions that exploit computing and data storage capacity, network resources, and scalability, without having to deal with common issues related to the configuration of the Cloud infrastructure that is automatically managed by a specific service. Cloud Computing can be defined as a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., servers, storage, and services) that can be rapidly provisioned and released with minimal effort in management (Mell & Grance, 2011). In this context, Cloud, Fog, and Edge computing allow organisations to exploit data processing and storage resources efficiently through the definition of a hierarchical data processing architecture. Fog and Edge computing are both extensions of the Cloud network, where at the lowest level there is the Edge, followed by the Fog level, and finally the Cloud level. The Edge layer allows reducing network traffic as data processing occurs locally on the devices. The Fog layer of the Cloud network architecture pushes intelligence down to the LAN layer, where data are processed in a gateway; thus, the Fog nodes are placed near devices with which it is communicating. Cloud, Fog, and Edge computing can offer suitable services to share and collaborate on M&S projects and perform complex simulation experiments faster and more efficiently through the Modelling and Simulation as a Service (MSaaS) model. While MSaaS provides an everincreasing number of opportunities, it also poses a significant number of pitfalls. One of the major pitfalls is that Cloud infrastructures are massive at all scales; as a consequence, the definition of MSaaS solutions is difficult without a deep knowledge of the involved infrastructures and technologies (Cayirci, 2013). The focus of this special issue is to provide current research results in M&S for Cloud Computing and vice versa. Specifically, the special issue aims at (i) presenting the current state-of-the-art about M&S solutions based on open standards, recent extensions, and innovations related to Cloud Computing technologies; (ii) identifying research directions and technologies that will drive innovations in M&S based on Cloud Computing Infrastructures, and (iii) adopts M&S techniques to formalise and study Cloud Computing environments and services. The application of Cloud-based M&S has increased since 2010 (Mansouri et al., 2020) however, studies, particularly on methodological and technological aspects in the convergence of Cloud Computing and M&S disciplines, continue to be few (Hannay et al., 2021; Tolk, 2020; Zhou et al., 2022). To fill this gap in the literature, we invited researchers and practitioners to submit contributions on conceptual, methodological, and technical advances in High-performance simulation in the Cloud, System Dependability, and Performance Analysis through Big data in the Cloud, Parallel and Distributed simulation through the Cloud services. The resulting contributions deal with a wide range of topics ranging from methodological aspects and development frameworks in adopting M&S in the Cloud Computing environment and vice versa, i.e., how Cloud Computing can support the definition of new M&S methods, models, and techniques. This special issue contains four papers, each of which is briefly described in the following. The paper titled “Mobile Experimentation using Modeling and Simulation in the Fog/Cloud” (by Khaldoon Al-Zoubi and Gabriel Wainer) proposes a method and some algorithms to define Fog nodes as private services in which different middleware run on different Virtual Machines to expose services (AlZoubi & Wainer, 2021). The focus of the research is on the mobility of clients that perform experiments through mobile devices. The proposed method and algorithms take into consideration the position of clients to identify available services that are nearby the Fog zone. To increase mobility assistance, the paper delineates the concept of “mobile simulation experiment”, in which experiments move with the device as it moves away from a specified Fog zone. JOURNAL OF SIMULATION 2022, VOL. 16, NO. 6, 547–549 https://doi.org/10.1080/17477778.2022.2080009","PeriodicalId":51296,"journal":{"name":"Journal of Simulation","volume":"16 1","pages":"547 - 549"},"PeriodicalIF":1.3000,"publicationDate":"2022-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Editorial: Special issue on modelling and simulation in the cloud computing era\",\"authors\":\"A. Falcone, A. Garro, N. Mustafee, M. Niazi, Gabriel A. Wainer\",\"doi\":\"10.1080/17477778.2022.2080009\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Modelling and Simulation (M&S) represents one of the fundamental methods to design and study complex systems in many industrial and scientific domains such as transport, energy, and aerospace. M&S techniques enable the analysis and evaluation of many design alternatives while avoiding risks, costs, and failures that come with experimentations on the real system; this opportunity becomes crucial, when realworld tests are too costly to conduct in terms of safety, time, and other resources (Fujimoto et al., 2017). Cloud Computing has captured the interest of the scientific and industrial communities because of the benefits provided by its service models, i.e., Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). These services allow developers to rapidly implement solutions that exploit computing and data storage capacity, network resources, and scalability, without having to deal with common issues related to the configuration of the Cloud infrastructure that is automatically managed by a specific service. Cloud Computing can be defined as a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., servers, storage, and services) that can be rapidly provisioned and released with minimal effort in management (Mell & Grance, 2011). In this context, Cloud, Fog, and Edge computing allow organisations to exploit data processing and storage resources efficiently through the definition of a hierarchical data processing architecture. Fog and Edge computing are both extensions of the Cloud network, where at the lowest level there is the Edge, followed by the Fog level, and finally the Cloud level. The Edge layer allows reducing network traffic as data processing occurs locally on the devices. The Fog layer of the Cloud network architecture pushes intelligence down to the LAN layer, where data are processed in a gateway; thus, the Fog nodes are placed near devices with which it is communicating. Cloud, Fog, and Edge computing can offer suitable services to share and collaborate on M&S projects and perform complex simulation experiments faster and more efficiently through the Modelling and Simulation as a Service (MSaaS) model. While MSaaS provides an everincreasing number of opportunities, it also poses a significant number of pitfalls. One of the major pitfalls is that Cloud infrastructures are massive at all scales; as a consequence, the definition of MSaaS solutions is difficult without a deep knowledge of the involved infrastructures and technologies (Cayirci, 2013). The focus of this special issue is to provide current research results in M&S for Cloud Computing and vice versa. Specifically, the special issue aims at (i) presenting the current state-of-the-art about M&S solutions based on open standards, recent extensions, and innovations related to Cloud Computing technologies; (ii) identifying research directions and technologies that will drive innovations in M&S based on Cloud Computing Infrastructures, and (iii) adopts M&S techniques to formalise and study Cloud Computing environments and services. The application of Cloud-based M&S has increased since 2010 (Mansouri et al., 2020) however, studies, particularly on methodological and technological aspects in the convergence of Cloud Computing and M&S disciplines, continue to be few (Hannay et al., 2021; Tolk, 2020; Zhou et al., 2022). To fill this gap in the literature, we invited researchers and practitioners to submit contributions on conceptual, methodological, and technical advances in High-performance simulation in the Cloud, System Dependability, and Performance Analysis through Big data in the Cloud, Parallel and Distributed simulation through the Cloud services. The resulting contributions deal with a wide range of topics ranging from methodological aspects and development frameworks in adopting M&S in the Cloud Computing environment and vice versa, i.e., how Cloud Computing can support the definition of new M&S methods, models, and techniques. This special issue contains four papers, each of which is briefly described in the following. The paper titled “Mobile Experimentation using Modeling and Simulation in the Fog/Cloud” (by Khaldoon Al-Zoubi and Gabriel Wainer) proposes a method and some algorithms to define Fog nodes as private services in which different middleware run on different Virtual Machines to expose services (AlZoubi & Wainer, 2021). The focus of the research is on the mobility of clients that perform experiments through mobile devices. The proposed method and algorithms take into consideration the position of clients to identify available services that are nearby the Fog zone. To increase mobility assistance, the paper delineates the concept of “mobile simulation experiment”, in which experiments move with the device as it moves away from a specified Fog zone. 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Editorial: Special issue on modelling and simulation in the cloud computing era
Modelling and Simulation (M&S) represents one of the fundamental methods to design and study complex systems in many industrial and scientific domains such as transport, energy, and aerospace. M&S techniques enable the analysis and evaluation of many design alternatives while avoiding risks, costs, and failures that come with experimentations on the real system; this opportunity becomes crucial, when realworld tests are too costly to conduct in terms of safety, time, and other resources (Fujimoto et al., 2017). Cloud Computing has captured the interest of the scientific and industrial communities because of the benefits provided by its service models, i.e., Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). These services allow developers to rapidly implement solutions that exploit computing and data storage capacity, network resources, and scalability, without having to deal with common issues related to the configuration of the Cloud infrastructure that is automatically managed by a specific service. Cloud Computing can be defined as a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., servers, storage, and services) that can be rapidly provisioned and released with minimal effort in management (Mell & Grance, 2011). In this context, Cloud, Fog, and Edge computing allow organisations to exploit data processing and storage resources efficiently through the definition of a hierarchical data processing architecture. Fog and Edge computing are both extensions of the Cloud network, where at the lowest level there is the Edge, followed by the Fog level, and finally the Cloud level. The Edge layer allows reducing network traffic as data processing occurs locally on the devices. The Fog layer of the Cloud network architecture pushes intelligence down to the LAN layer, where data are processed in a gateway; thus, the Fog nodes are placed near devices with which it is communicating. Cloud, Fog, and Edge computing can offer suitable services to share and collaborate on M&S projects and perform complex simulation experiments faster and more efficiently through the Modelling and Simulation as a Service (MSaaS) model. While MSaaS provides an everincreasing number of opportunities, it also poses a significant number of pitfalls. One of the major pitfalls is that Cloud infrastructures are massive at all scales; as a consequence, the definition of MSaaS solutions is difficult without a deep knowledge of the involved infrastructures and technologies (Cayirci, 2013). The focus of this special issue is to provide current research results in M&S for Cloud Computing and vice versa. Specifically, the special issue aims at (i) presenting the current state-of-the-art about M&S solutions based on open standards, recent extensions, and innovations related to Cloud Computing technologies; (ii) identifying research directions and technologies that will drive innovations in M&S based on Cloud Computing Infrastructures, and (iii) adopts M&S techniques to formalise and study Cloud Computing environments and services. The application of Cloud-based M&S has increased since 2010 (Mansouri et al., 2020) however, studies, particularly on methodological and technological aspects in the convergence of Cloud Computing and M&S disciplines, continue to be few (Hannay et al., 2021; Tolk, 2020; Zhou et al., 2022). To fill this gap in the literature, we invited researchers and practitioners to submit contributions on conceptual, methodological, and technical advances in High-performance simulation in the Cloud, System Dependability, and Performance Analysis through Big data in the Cloud, Parallel and Distributed simulation through the Cloud services. The resulting contributions deal with a wide range of topics ranging from methodological aspects and development frameworks in adopting M&S in the Cloud Computing environment and vice versa, i.e., how Cloud Computing can support the definition of new M&S methods, models, and techniques. This special issue contains four papers, each of which is briefly described in the following. The paper titled “Mobile Experimentation using Modeling and Simulation in the Fog/Cloud” (by Khaldoon Al-Zoubi and Gabriel Wainer) proposes a method and some algorithms to define Fog nodes as private services in which different middleware run on different Virtual Machines to expose services (AlZoubi & Wainer, 2021). The focus of the research is on the mobility of clients that perform experiments through mobile devices. The proposed method and algorithms take into consideration the position of clients to identify available services that are nearby the Fog zone. To increase mobility assistance, the paper delineates the concept of “mobile simulation experiment”, in which experiments move with the device as it moves away from a specified Fog zone. JOURNAL OF SIMULATION 2022, VOL. 16, NO. 6, 547–549 https://doi.org/10.1080/17477778.2022.2080009
Journal of SimulationCOMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-OPERATIONS RESEARCH & MANAGEMENT SCIENCE
CiteScore
5.70
自引率
16.00%
发文量
42
期刊介绍:
Journal of Simulation (JOS) aims to publish both articles and technical notes from researchers and practitioners active in the field of simulation. In JOS, the field of simulation includes the techniques, tools, methods and technologies of the application and the use of discrete-event simulation, agent-based modelling and system dynamics.