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Cloud computing originated in central data centers that are connected to the backbone of the Internet. The network transport to and from a distant data center incurs long latencies that hinder modern low-latency applications. In order to flexibly support the computing demands of users, cloud computing is evolving toward a continuum of cloud computing resources that are distributed between the end users and a distant data center. The purpose of this review paper is to concisely summarize the state-of-the-art in the evolving cloud computing field and to outline research imperatives.

The authors identify two main dimensions (or axes) of development of cloud computing: the trend toward flexibility of scaling computing resources, which the authors denote as Flex-Cloud, and the trend toward ubiquitous cloud computing, which the authors denote as Ubi-Cloud. Along these two axes of Flex-Cloud and Ubi-Cloud, the authors review the existing research and development and identify pressing open problems.

The authors find that extensive research and development efforts have addressed some Ubi-Cloud and Flex-Cloud challenges resulting in exciting advances to date. However, a wide array of research challenges remains open, thus providing a fertile field for future research and development.

This review paper is the first to define the concept of the Ubi-Flex-Cloud as the two-dimensional research and design space for cloud computing research and development. The Ubi-Flex-Cloud concept can serve as a foundation and reference framework for planning and positioning future cloud computing research and development efforts.

Major public cloud providers, such as AWS, Azure or Google, offer seamless experiences for infrastructure as a service (IaaS), platform as a service (PaaS) and software as a service (SaaS). With the emergence of the public cloud's vast usage, administrators must be able to have a reliable method to provide the seamless experience that a public cloud offers on a smaller scale, such as a private cloud. When a smaller deployment or a private cloud is needed, OpenStack can meet the goals without increasing cost or sacrificing data control.

To demonstrate these enablement goals of resiliency and elasticity in IaaS and PaaS, the authors design a private distributed system cloud platform using OpenStack and its core services of Nova, Swift, Cinder, Neutron, Keystone, Horizon and Glance on a five-node deployment.

Through the demonstration of dynamically adding an IaaS node, pushing the deployment to its physical and logical limits, and eventually crashing the deployment, this paper shows how the PackStack utility facilitates the provisioning of an elastic and resilient OpenStack-based IaaS platform that can be used in production if the deployment is kept within designated boundaries.

The authors adopt the multinode-capable PackStack utility in favor of an all-in-one OpenStack build for a true demonstration of resiliency, elasticity and scalability in a small-scale IaaS. An all-in-one deployment is generally used for proof-of-concept deployments and is not easily scaled in production across multiple nodes. The authors demonstrate that combining PackStack with the multi-node design is suitable for smaller-scale production IaaS and PaaS deployments.

The purpose of this paper is to present a visualization platform to control and monitor wireless sensor networks (WSNs) in manufacturing applications.

To make the platform flexible and versatile, a modular framework is adopted in modeling and visualizing WSNs. The Eclipse programming environment is used to maximize the scalability and adaptability of the platform. A set of the core functional modules have been designed and implemented to support the system operation. The platform is validated through a case study simulation.

The platform is capable of accommodating different operating systems such as Windows and Linux. It allows integrating new plug-ins developed in various languages such as Java, C, C++, and Matlab. The Graphic User Interface has been applied to process and visualize the acquired real-time data from a WSN, and the embodied methodologies can be used to predict the behaviors of objects in the network.

The work has shown the feasibility and potential of the proposed platform in improving the real-time performance of WSN. However, the number of the developed functional modules is limited, and additional effort is required to develop sophisticated functional modules or sub-systems for a customized application.

The platform can be applied to monitor and visualize various WSN applications in manufacturing environments such as automated workcells, transportation systems, logistic, and storage systems.

The work is motivated by the scarce research on the development tools for monitoring and visualization of WSNs in manufacturing applications. The proposed platform serves for both of system developers and users. It is modularized with a set of core functional modules; it can be extended to accommodate new functional modules with a minimal effort for a different application.

The purpose of this study is to investigate the relationships among determinant (ease of use), extrinsic (usefulness) and intrinsic motivations (enjoyment), attachment and usage intention regarding seniors’ use of mobile devices for tourism. In addition, this study examines the moderating role of knowledge in these relationships.

The researchers collected data via online surveys to reach the target population of this study, 55 years and older adults who had used mobile devices for tourism. The researchers used the partial least squares approach for this study.

The results reveal that ease of use has significant effects on extrinsic and intrinsic motivations. The motivations of usefulness and enjoyment significantly affect attachment, which, in turn, influences usage intention. The relationships between ease of use and usefulness, ease of use and enjoyment and enjoyment and attachment were stronger for the high-knowledge group than for the low-knowledge group. The relationship between usefulness and attachment was stronger for the low-knowledge group than for the high-knowledge group.

The findings of this study provide compelling implications for academics and practitioners in the senior tourism field.

The compelling insight of this study is the development of a research model that combines an emergent construct of attachment as a mediator and knowledge of technology as a moderator.

Public policy requires effective identification of the current and emerging issues being faced in industry and beyond. This paper aims to identify a set of key issues currently facing digital communications and reviews their relevance for the strategic provision of infrastructure, particularly within the UK context.

The methodology focusses on taking a horizon-scanning approach to obtaining current information from a range of authoritative decision makers across industry, government and academia. After structuring the issues identified, these areas are explored by a multi-disciplinary research team covering engineering, economics and computer science.

Five key categories were identified including future demand; coverage and capacity; policy and regulation; economics and business models; and technology. The results are reported for both fixed and wireless networks. Shared issues affecting the wider digital ecosystem are also identified including Brexit, connecting remote areas and the degree to which the economics of infrastructure allows for building multiple overlapping infrastructures. The authors find that future demand uncertainty is one of the major issues affecting the digital communications sector driven by rigid willingness-to-pay, weak revenue and an increasing shift from fixed to wireless technologies. Policy must create the market conditions that encourage the entry of new competitors with innovative thinking and disruptive business models.

A limitation of the analysis is that it is quite UK-focussed; hence, further research could broaden this analysis to assessing issues at a continental or global scale.

The value of this paper originates from the breadth of the expert elicitation exercise carried out to gather the initial set of issues, followed by the analysis of this data by a multi-disciplinary team of researchers. The results direct a future research agenda, as many issues are indicative of a lack of existing evidence to support effective decision-making.

Smart grid is an integration between traditional electricity grid and communication systems and networks. Providing reliable services and functions is a critical challenge for the success and diffusion of smart grids that needs to be addressed. The purpose of this study is to determine the critical criteria that affect smart grid reliability from the perspective of users and investigate the role big data plays in smart grid reliability.

This study presents a model to investigate and identify criteria that influence smart grid reliability from the perspective of users. The model consists of 12 sub-criteria covering big data management, communication system and system characteristics aspects. Multi-criteria decision-making approach is applied to analyze data and prioritize the criteria using the fuzzy analytic hierarchy process based on the triangular fuzzy numbers. Data was collected from 16 experts in the fields of smart grid and Internet of things.

The results show that the “Big Data Management” criterion has a significant impact on smart grid reliability followed by the “System Characteristics” criterion. The “Data Analytics” and the “Data Visualization” were ranked as the most influential sub-criteria on smart grid reliability. Moreover, sensitivity analysis has been applied to investigate the stability and robustness of results. The findings of this paper provide useful implications for academicians, engineers, policymakers and many other smart grid stakeholders.

The users are not expected to actively participate in smart grid and its services without understanding their perceptions on smart grid reliability. Very few works have studied smart grid reliability from the perspective of users. This study attempts to fill this considerable gap in literature by proposing a fuzzy model to prioritize smart grid reliability criteria.