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The purpose of this paper is to examine how a middle school science teacher, new to programming, supports students in learning to debug physical computing systems consisting of programmable sensors and data displays.

This case study draws on data collected during an inquiry-oriented instructional unit in which students learn to collect, display and interpret data from their surrounding environment by wiring and programming a physical computing system. Using interaction analysis, the authors analyzed video recordings of one teacher’s (Gabrielle) pedagogical moves as she supported students in debugging their systems as they drew upon a variety of embodied, material and social resources.

This study presents Gabrielle’s debugging interactional grammar, highlighting the pedagogical possibilities for supporting students in systematic ways, providing affective support (e.g. showing them care and encouragement) and positioning herself as a learner with the students. Gabrielle’s practice, and therefore her pedagogy, has the potential to support students in becoming better debuggers on their own in the future.

While much of the prior work on learning to debug focuses on learner actions and possible errors, this case focuses on an educator’s debugging pedagogy centered on the educator debugging with the learners. This case study illustrates the need for educators to exhibit deft facilitation, vulnerability and orchestration skills to support student development of their own process for and agency in debugging.

Cloud computing gives several on-demand infrastructural services by dynamically pooling heterogeneous resources to cater to users’ applications. The task scheduling needs to be done optimally to achieve proficient results in a cloud computing environment. While satisfying the user’s requirements in a cloud environment, scheduling has been proven an NP-hard problem. Therefore, it leaves scope to develop new allocation models for the problem. The aim of the study is to develop load balancing method to maximize the resource utilization in cloud environment.

In this paper, the parallelized task allocation with load balancing (PTAL) hybrid heuristic is proposed for jobs coming from various users. These jobs are allocated on the resources one by one in a parallelized manner as they arrive in the cloud system. The novel algorithm works in three phases: parallelization, task allocation and task reallocation. The proposed model is designed for efficient task allocation, reallocation of resources and adequate load balancing to achieve better quality of service (QoS) results.

The acquired empirical results show that PTAL performs better than other scheduling strategies under various cases for different QoS parameters under study.

The outcome has been examined for the real data set to evaluate it with different state-of-the-art heuristics having comparable objective parameters.

Alongside the remarkable evolution of cellular communication to 5G networks, significant security and privacy challenges have risen which can affect the widespread adoption of advanced communication technologies. In this context, the purpose of this paper is to examine research within security and privacy for 5G-based systems highlighting contributions made by the research community and identify research trends within different subdomains of 5G security where open issues still exist.

This paper uses a bibliographic approach to review the state-of-the-art in the field of 5G security and is the pioneering effort to investigate 5G security research using this methodology. Specifically, the paper presents a quantitative description of the existing contributions in terms of authors, organizations, and countries. It then presents detailed keyword and co-citation analysis that shows the quantity and pattern of research work in different subfields. Finally, 5G security areas are identified having open challenges for future research work.

The study shows that China leads the world in terms of published research in the field of 5G security with USA and India ranked second and third respectively. Xidian University, China is ranked highest for number of publications and h-index followed by University Oulu and AALTO University Finland. IEEE Access, Sensors and IEEE Internet of Things Journal are the top publication venues in the field of 5G security. Using VOSViewer aided analysis with respect to productivity, research areas and keywords, the authors have identified research trends in 5G security among scientific community whilst highlighting specific challenges which require further efforts.

Existing studies have focused on surveys covering state-of-the art research in secure 5G network (Zhang et al. 2019), physical layer security (Wu et al., 2018), security and privacy of 5G technologies (Khan et al., 2020) and security and privacy challenges when 5G is used in IoT (Sicari et al. 2020). However, our research has revealed no existing bibliometric studies in this area and therefore, to our best knowledge, this paper represents pioneering such effort for security within 5G.

Cyber physical system (CPS) has attracted much attention from industry, government and academia due to its dramatic impact on society, economy and people’s daily lives. Scholars have conducted a number of studies on CPS. However, despite of the dynamic nature of this research area, a systematic and extensive review of recent research on CPS is unavailable. Accordingly, this paper conducts an intensive literature review on CPS and presents an overview of existing research on CPS. The purpose of this paper is to identify the challenges of studying CPS as well as the directions for future studies on CPS.

This paper examines existing literatures about CPS from 2006 to 2018 in Compendex, presenting its definition, architectures, characteristics and applications.

This study finds that CPS is closely integrated, diversified and large-scale network with complex multiple time scales. It requires dynamic reorganization/reconfiguration, mass computing, and closed, automated and control circuits. Currently, CPS has been applied in smart manufacturing, medical systems, smart city and smart libraries. The main challenges in designing CPS are to develop, to modify, to integrate abstractions and to set predictable timing of openness and physical interconnection of physical devices. Furthermore, security is a key issue in CPS.

This study adds knowledge to the existing literature of CPS by answering what the current level of development on CPS is and what the potential future research directions of CPS are.

The purpose of this paper is to identify the Industry 4.0 barriers to achieve circular economy (CE). The study focuses on exploring the link between Industry 4.0 and CE. This leads to the implementation of integrated Industry 4.0-CE and attainment of sustainable production and consumption through analyzing the technological benefits of Industry 4.0.

Industry 4.0 barriers are identified from literature review and discussions with industry experts. Here, the interpretive structural modeling (ISM) technique is applied to develop the contextual relationship among the barriers and to identify the prominent barriers hindering the CE implementation.

The ISM hierarchical model and Matriced’ impacts croised-multiplication applique’ and classment analysis illustrate that the digitalization process and the semantic interoperability possess high driving power and low dependence. These barriers require keen attention to play a significant role in improving resource efficiency and sustainability, and absence of these barriers may not drive other barriers for CE. Apart from these barriers, cyber-physical systems standards and specifications, sensor technology and design challenges are also the most influential Industry 4.0 barriers for achieving CE.

The findings provide an opportunity for industry practitioners to explore the most driving Industry 4.0 barriers. The study confirms that integrated Industry 4.0-CE will maintain sustainable operations management by optimizing the production and consumption patterns. It will also provide an opportunity of customization where customers and products interact and can monitor the performance of the operations through the Internet of Things sensors.

The study provides integration of Industry 4.0 challenges to implement CE. However, the integration of the two burgeoning fields is still very scarce and lacks in adopting the technological benefits of the integrated Industry 4.0-CE.

The COVID-19 pandemic era has severely hampered the economy over the globe. However, the manufacturing organizations across all the countries have struggled heavily, as they were among the least who worked on online mode. The organizations are adopting various innovative quality methodologies to improve their performance. In this regard, they are adopting the Sustainable Lean Six Sigma (SLSS) concept and Industry 4.0 technologies to develop products at a faster rate. The use of Industry 4.0 technologies may reduce material movement and supply chain disruptions with the help of smart intelligent systems. There is a strong synergy between SLSS and Industry 4.0 technologies, resulting in an integrated approach for adoption. This study aims to develop a framework that practitioners can use to adopt Industry 4.0-SLSS practices effectively.

This study portrays 31 Industry 4.0-SLSS practices and 22 performance metrics identified through a literature review to improve the manufacturing supply chain performance. To compute the weights of these practices, the Robust Best–Worst Method (RBWM) is used. The Pythagorean fuzzy combined compromise solution (PF-CoCoSo) method is used to rank performance metrics.

According to the RBWM results, “Process Development Practices (PDP)” are first among the major criteria, followed by “Organizational Management Practices (OMP)” at second, “Technology Adoption Practices (TAP)” at third, “Strategy Management Practices (SMP)” at fourth and “Executive Management Practices (EMP)” at fifth, whereas the PF-CoCoSo method resulted in the performance metric “On time product delivery” ranking first.

The identified practices have the potential to significantly improve the performance of the manufacturing supply chain. Practices that encourage a sustainable manufacturing supply chain and the usage of emerging technology will benefit organizational effectiveness. Managers can assess performance using prioritized performance metrics.

During the COVID-19 pandemic era, this is one of the unique attempts to provide a framework to improve the manufacturing supply chain performance. This study integrates and identifies Industry 4.0-SLSS practices and performance metrics for enhancing overall performance.

Mobile crowd sensing (MCS) is a new paradigm enabled by Internet of Things (IoT) in which sensor-rich ubiquitous devices collect and share the data over a large geography. Human behaviour attributes (perception, comprehension and projection) play a key role in the decision-making process for sharing and processing the data. This study aims to understand how situation awareness plays an important role in MCS in an IoT ecosystem.

A systematic literature review was conducted by following a rigorous search protocol that identified a total of 470 peer-reviewed research papers. These papers were further filtered and finally 31 relevant papers were selected.

The major issues and concerns arising due to human participation in the MCS system were identified. Further, probable strategies were explored to deal with the challenges resulting due to certain human behaviour attributes.

This study provides the recommendations to address the major challenges related to the MCS system, which in turn may enhance the adoption of emerging smart technology-driven services.

The study is original and is based on the existing literature and its interpretation.

The purpose of this paper is to review and explore the evolution, advances and future trends of cloud manufacturing, placing the focus on the quality of services. Moreover, moving toward the new trend of cyber-physical systems (CPS), a cloud-based cyber-physical system (CBCPS) is proposed combining the key enabling techniques of this decade, namely Internet of Things (IoT), cloud computing, Big Data analytics and CPS.

First, an extensive review is made on cloud computing and its applications in manufacturing sectors, namely product development, manufacturing processes and manufacturing systems management. Second, a conceptual CBCPS which combines key enabling techniques including cloud computing, CPS and IoT is proposed. Finally, a review on the quality of the services (QoS) presented in the second step, along with the main security issues of cloud manufacturing, is conducted.

The findings of this review indicate that the combination of the key enabling techniques presented in the CBCPS will lead to a new manufacturing paradigm capable of facing the new challenges and trends. The opportunities, as well as the challenges and barriers of the proposed framework are presented, concluding that the transition into this whole new era of networked computing and manufacturing has a valuable impact, but also generates several security and quality issues.

The paper is the first to specifically study the QoS as a factor in the proposed manufacturing paradigm.

Virtual machines (VMs) are suggested by the providers of cloud services as the services for the users over the internet. The consolidation of VM is the tactic of the competent and smart utilization of resources from cloud data centers. Placement of a VM is one of the significant issues in cloud computing (CC). Physical machines in a cloud environment are aware of the way of the VM placement (VMP) as the mapping VMs. The basic target of placement of VM issue is to reduce the physical machines' items that are running or the hosts in cloud data centers. The VMP methods have an important role in the CC. However, there is no systematic and complete way to discuss and analyze the algorithms. The purpose of this paper is to present a systematic survey of VMP techniques. Also, the benefits and weaknesses connected with selected VMP techniques have been debated, and the significant issues of these techniques are addressed to develop the more efficient VMP technique for the future.

Because of the importance of VMP in the cloud environments, in this paper, the articles and important mechanisms in this domain have been investigated systematically. The VMP mechanisms have been categorized into two major groups, including static and dynamic mechanisms.

The results have indicated that an appropriate VMP has the capacity to decrease the resource consumption rate, energy consumption and carbon emission rate. VMP approaches in computing environment still need improvements in terms of reducing related overhead, consolidation of the cloud environment to become an extremely on-demand mechanism, balancing the load between physical machines, power consumption and refining performance.

This study aimed to be comprehensive, but there were some limitations. Some perfect work may be eliminated because of applying some filters to choose the original articles. Surveying all the papers on the topic of VMP is impossible, too. Nevertheless, the authors are trying to present a complete survey over the VMP.

The consequences of this research will be valuable for academicians, and it can provide good ideas for future research in this domain. By providing comparative information and analyzing the contemporary developments in this area, this research will directly support academics and working professionals for better knowing the growth in the VMP area.

The gathered information in this paper helps to inform the researchers with the state of the art in the VMP area. Totally, the VMP's principal intention, current challenges, open issues, strategies and mechanisms in cloud systems are summarized by explaining the answers.

The purpose of this paper is to present a component framework for building visual interfaces for pervasive computing systems.

The proposed framework enables end‐users to build visual interfaces for their systems by using document‐editing manner.

The building and operating visual interfaces are useful for managing pervasive computing systems.

The framework is designed based on Java but programming language‐independent version is needed.

A component framework was implemented for building visual interfaces for pervasive computing.

A framework for visual interfaces for pervasive computing is unique.