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The key feature of SaaS application is that it addresses the needs of many different customers using only one software, rather than multiple developments and versions, a concept known as multi-tenancy. However, it typically results in a one-size-fits-all approach and the application only fulfills the requirements that are generic to all tenants. Th...
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To meet the required functional and nonfunctional requirements of different enterprise applications it is important to model the possible design so that a feasible alternative can be defined. We observed SaaS developed application by multi-tenancy to provide flexible customization and introduced many issues in software scalability and dynamic testi...
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As a software delivery model, Software as a Service (SaaS) has attracted considerable attention from software providers and users. Most traditional companies are shifting their businesses to an SaaS model. SaaS development is a very complicated process and its success depends on architectural design and development. A Manufacturing Execution System (MES) was used at the expense of licensing fees for features not used in the On-Premise environment, although the features used vary depending on the manufacturing environment. In an SaaS environment, MES is applied with a function-specific container approach through a Microservice Architecture (MSA) to select and employ only the necessary functions. Furthermore, as the number of customers of virtualized applications increases in SaaS-based services, complexity and operating costs increase; thus, Multi-tenancy Architecture (MTA) technology, which serves all customers through a single instance of the application is crucial. Thus, in this study, we investigate the MTA approach and propose a suitable MTA for the manufacturing execution system. Real-time response is crucial to achieving a cyber-physical system of digital manufacturing in SaaS-based MES. Furthermore, SaaS-based big data analytics and decision-making cannot meet the needs of numerous applications in real-time sensitive workplaces. In this study, we propose an SaaS-based MSA/MTA model for real-time control of Internet of Things (IoT) Edge in digital manufacturing (SaaMES), an architecture of SaaS-based MES with MSA and MTA to meet vulnerable workplaces and real-time responses in Cloud environments. The analysis is used by applying the Autoencoder and Generic Adversarial Networks analysis model to IoT Edge for the connection between the Cloud environment and work site to enable real-time response and decision-making through communication using OPC-UA and small-scale analysis.
Software as a Service (SaaS) is widely used and depended on by a wide range of applications. Considering this, SaaS should capacitate itself to offer service to a large number of customers having their own specific requirements, without encountering software quality problems. Therefore, several researchers delved into SaaS customization, and many customization solutions have been proposed. However, heretofore no analysis or study explicitly classifies these proposals using different criteria, e.g., the kind of change required, the component of the software requiring changes, and the quality attributes of SaaS considered in each proposed solution. This study adopts the systematic mapping approach to methodically investigate the solutions recommended for SaaS customization problems. These solutions are classified into various categories to create a classification scheme based on the customization types (personalization, configuration, composition, modification, integration, and extension), customization layer (user interfaces, workflows, services, and data), and quality attributes. Our study identified 81 primary studies reporting SaaS customization solutions. Results show that the configuration, composition, and extension received the highest consideration in the proposed solutions. Additionally, majority of the proposed solutions for SaaS customization are connected with the workflow and service layers. Furthermore, the attributes: multi-tenancy, security, functionality, scalability, availability, and efficiency are considered much more often than other attributes. Classification of the proposed solutions for SaaS customization and results of this study can play an important role in creating a framework for SaaS customization assessment.
