Special Session on Industry 4.0

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A Method for Interpretively Synthesizing Qualitative Research Findings

In the qualitative research world, one can use a method called meta-synthesis to interpretively assess a compiled body of literature on a specific topic, though it has seen little application in business research let alone in management information systems scholarship. However, because methods for qualitative inquiry have gained more popularity in the information systems discipline, this method holds great promise in supporting efforts toward theoretical generalization for qualitative researchers. Accordingly, in this paper, we present a methodological tutorial on the nature and practice of analytically synthesizing a body of qualitative research for developing and explicating theory

A Framework for Strategic Cloud Migration

This paper presents a novel framework for organisations to carry out a structured feasibility study on Cloud migration and to decide Cloud Migration Strategy. Following the framework helps an organisation to decide whether Cloud migration is a feasible option for them, and if so, the best strategic approach towards Cloud migration. It is a crucial and sensitive part for any organisation to decide whether they should move to Cloud Computing platform. The decision requires strategic approach with proper feasibility study. Several technological, human, security and financial factors are involved in decision making process to move to the Cloud. The proposed framework helps an organisation to carry out a feasibility study to decide whether to move to the Cloud, and if so, what would be the best approach towards Cloud migration. The proposed framework addresses the factors that an organisation must explore to decide on Cloud migration. Cloud Computing has its own pros and cons. A whimsical decision to move to the Cloud may be disastrous for an organisation. Following the proposed framework will help organisations to carry out a structured and integrated feasibility study deal with the decision on Cloud migration

Towards A Comprehensive Cloud Decision Framework with Financial Viability Assessment

Most organizations moving their legacy systems to the cloud base their decisions on the naïve assumption that the public cloud provides cost savings. However, this is not always true. Sometimes the migration complexity of certain applications outweighs the benefits to be had from a public cloud. Moreover, the total cost of ownership does not necessarily decrease by moving to a public cloud. Therefore, there is a need for a disciplined approach for choosing the right cloud platform for application migration. In this paper, we propose a comprehensive cloud decision framework that includes an extensible decision criteria set, associated usage guidelines, a decision model for cloud platform recommendation, and a cost calculator to compute the total cost of ownership (TCO). The decision process works as follows. It begins with the ordering of relevant criteria, either according to industry best practice or the enterprise’s specific requirements and preferences. A technical recommendation is made on the basis of the criteria classification, which is then assessed for financial viability. By providing traceability of the cost items in the public/private TCO calculators to the decision criteria, the framework enables users to iterate through the decision process, determining and eliminating (if possible) the main cost drivers until a right balance is found between the desirable criteria and the available budget. We illustrate the need, benefits and value of our proposed framework through three different real-world use case scenarios

Cloud computing resource scheduling and a survey of its evolutionary approaches

A disruptive technology fundamentally transforming the way that computing services are delivered, cloud computing offers information and communication technology users a new dimension of convenience of resources, as services via the Internet. Because cloud provides a finite pool of virtualized on-demand resources, optimally scheduling them has become an essential and rewarding topic, where a trend of using Evolutionary Computation (EC) algorithms is emerging rapidly. Through analyzing the cloud computing architecture, this survey first presents taxonomy at two levels of scheduling cloud resources. It then paints a landscape of the scheduling problem and solutions. According to the taxonomy, a comprehensive survey of state-of-the-art approaches is presented systematically. Looking forward, challenges and potential future research directions are investigated and invited, including real-time scheduling, adaptive dynamic scheduling, large-scale scheduling, multiobjective scheduling, and distributed and parallel scheduling. At the dawn of Industry 4.0, cloud computing scheduling for cyber-physical integration with the presence of big data is also discussed. Research in this area is only in its infancy, but with the rapid fusion of information and data technology, more exciting and agenda-setting topics are likely to emerge on the horizon

Key Opportunities and Challenges of Data Migration in Cloud: Results from a Multivocal Literature Review

Cloud data migration is the procedure of moving information, localhost applications, services, and data to the distributed cloud computing infrastructure. The success of this data migration process is depending on several aspects like planning and impact analysis of existing enterprise systems. One of the most common operations is moving locally stored data in a public cloud computing environment. This paper, through a multivocal literature review, identifies the key advantages and consequences of migrating data into the cloud. There are five different cloud migration strategies and models prescribed to evaluate the performance, identifying security requirements, choosing a cloud provider, calculating the cost, and making any necessary organizational changes. The results of this research paper can give a road map for the data migration journey and can help decision makers towards a safe and productive migration to a cloud computing environment.publishedVersio

Microservice Transition and its Granularity Problem: A Systematic Mapping Study

Microservices have gained wide recognition and acceptance in software industries as an emerging architectural style for autonomic, scalable, and more reliable computing. The transition to microservices has been highly motivated by the need for better alignment of technical design decisions with improving value potentials of architectures. Despite microservices' popularity, research still lacks disciplined understanding of transition and consensus on the principles and activities underlying "micro-ing" architectures. In this paper, we report on a systematic mapping study that consolidates various views, approaches and activities that commonly assist in the transition to microservices. The study aims to provide a better understanding of the transition; it also contributes a working definition of the transition and technical activities underlying it. We term the transition and technical activities leading to microservice architectures as microservitization. We then shed light on a fundamental problem of microservitization: microservice granularity and reasoning about its adaptation as first-class entities. This study reviews state-of-the-art and -practice related to reasoning about microservice granularity; it reviews modelling approaches, aspects considered, guidelines and processes used to reason about microservice granularity. This study identifies opportunities for future research and development related to reasoning about microservice granularity.Comment: 36 pages including references, 6 figures, and 3 table