Business models for cloud computing: experiences from developing Modeling &amp; Simulation as a Service applications in industry

Kiss, Tamás; Dagdeviren, Huseyin; Taylor, Simon J. E.; Anagnostou, Anastasia; Fantini, Nicola

doi:10.1109/wsc.2015.7408373

Cited by 6 publications

(5 citation statements)

References 14 publications

(11 reference statements)

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“…It is very important to refer in this context that the previous researches focused on the business models from management side in general without consideration of specific business area especially that are related to the information technology (like as a service paradigm) which need specific background and analysis. Some of the researches that focused on cloud computing as a service paradigm (like [29]) provided business concept for providing Modeling & Simulation (M&S) as a service without to formulize the analytical steps that lead to these concept.…”

Section: Discussionmentioning

confidence: 99%

Three-Phase Approach for Developing Suitable Business Models for Exchanging Federated ERP Components as Web Services

Asfoura¹,

Abdel-Haq²,

Chatti³

2018

ijacsa

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The importance of business models has increased significantly in the last decade, especially in the Internet. The cause of this increase is the effect of Internet and the associated applications and their business processes regarding to the business model. These effects include, for example, the emerging technical and economic aspects of a business model on the Internet, the support and transformation of traditional business models, and the arise of new business ideas based on that technology. One of these new ideas is: how distributed Enterprise Resource Planning (ERP) systems or federated ERP (FERP) systems as web services (WSs) can cover the increasing demands of small and medium sized enterprises (SMEs) for business software covered.This paper aims to provide a derived developing approach with three phases that will lead to three suitable concepts that identify suitable business model for FERP System with different scenarios of value exchanging. The results of this work will be conceptual models that describe the character, role and revenue models that identify FERP exchanging business model.

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Section: Discussionmentioning

confidence: 99%

Three-Phase Approach for Developing Suitable Business Models for Exchanging Federated ERP Components as Web Services

Asfoura¹,

Abdel-Haq²,

Chatti³

2018

ijacsa

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“…For example, Liu, et al [39] (Simulation as a Service (SIM as a service) as well as Modelling as a Service (MaaS), Execution as a Service (EaaS), Analysis as a Service (AaaS), and Simulation Resource as a Service (SRaaS)) and Zehe, et al [40] (Simulation Software as a Service (SSaaS)). Siegfried, et al [41], Cayirci [42], Taylor, et al [43] and Kiss, et al [44] have proposed forms of MSaaS. While useful in advancing the discussion of what cloudbased simulation services could achieve, these contributions tend to be conceptual in nature, discussing the potential of some form of simulation-related service, or focus on one issue (e.g., theoretical architecture, security, business models, grand challenges, etc.…”

Section: Related Work: Cloud-based Distributed Simulationmentioning

confidence: 99%

A Workflow Architecture for Cloud-based Distributed Simulation

Chaudhry

Anagnostou

Taylor

2022

ACM Trans. Model. Comput. Simul.

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Distributed Simulation has still to be adopted significantly by the wider simulation community. Reasons for this might be that distributed simulation applications are difficult to develop and access to multiple computing resources are required. Cloud computing offers low-cost on-demand computing resources. Developing applications that can use cloud computing can be also complex, particularly those that can run on different clouds. Cloud-based Distributed Simulation (CBDS) is potentially attractive, as it may solve the computing resources issue as well as other cloud benefits, such as convenient network access. However, as possibly shown by the lack of sustainable approaches in the literature, the combination of cloud and distributed simulation may be far too complex to develop a general approach. E-Infrastructures have emerged as large-scale distributed systems that support high-performance computing in various scientific fields. Workflow Management Systems (WMS) have been created to simplify the use of these e-Infrastructures. There are many examples of where both technologies have been extended to use cloud computing. This article therefore presents our investigation into the potential of using these technologies for CBDS in the above context and the WORkflow architecture for cLoud-based Distributed Simulation (WORLDS), our contribution to CBDS. We present an implementation of WORLDS using the CloudSME Simulation Platform that combines the WS-PGRADE/gUSE WMS with the CloudBroker Platform as a Service. The approach is demonstrated with a case study using an agent-based distributed simulation of an Emergency Medical Service in REPAST and the Portico HLA RTI on the Amazon EC2 cloud.

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“…Over the past decade, the long-held dream of computing as a utility of Armbrust et al (2010) and Sharif (2010), and its disruptive potential to transform a large part of the IT industry (Buyya et al, 2008;Fox, 2009;Yeo et al, 2009;El Kadiri et al, 2016) have attracted high interest by enterprises. The cloud disruptive business model (Kiss et al, 2015) of making software as a service and forming the way IT hardware is designed and purchased has increased the potentialities to reshape the way enterprises acquire and manage their computing requirements (El-Gazzar, 2014;Alshamaila et al, 2013;Armbrust et al, 2010). In line with the shared services, cloud computing is considered an innovative model for IT sourcing that generates value for adopting enterprises (Schneider and Sunyaev, 2016).…”

Section: Literature Reviewmentioning

confidence: 99%

A cloud-based supply chain management system: effects on supply chain responsiveness

Giannakis

Spanaki

Dubey

2019

JEIM

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Purpose Despite the ongoing calls for the incorporation of the cloud utility model, the effect of the cloud on elements of supply chain performance is still an evolving area of research. The purpose of this paper is to develop the architecture of a cloud-based supply chain management (C-SCM) ecosystem and explore how it enhances supply chain responsiveness (SCR). Design/methodology/approach First, the authors discuss the potential benefits that cloud computing can yield, compared to existing mature SCM information systems and solutions through a comprehensive literature review. The authors conceptualise SCR in terms of the level of visibility in the supply chain, supply chain flexibility and rapid detection and reaction to changes, and then the authors build the detailed architecture of a C-SCM system. The proposed ecosystem introduces a view of SCM and the associated practices when transferred to cloud environments. The potential to enhance SCR through the cloud is explored with scenarios on a case of supply chain operations in fashion retail industry. Findings The findings show that the proposed system can enhance all three dimensions of SCR. Implications for supply chain practice and how companies can migrate to a cloud supply chain are drawn. Originality/value Given that the development, creation and delivery of goods and services are increasingly becoming a joint effort of several parties in a supply chain, the authors contribute to the existing literature by introducing a comprehensive C-SCM system and show how companies can enhance their SCR.

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Business models for cloud computing: experiences from developing Modeling & Simulation as a Service applications in industry

Cited by 6 publications

References 14 publications

Three-Phase Approach for Developing Suitable Business Models for Exchanging Federated ERP Components as Web Services

Three-Phase Approach for Developing Suitable Business Models for Exchanging Federated ERP Components as Web Services

A Workflow Architecture for Cloud-based Distributed Simulation

A cloud-based supply chain management system: effects on supply chain responsiveness

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