Service Computing for Industry 4.0: State of the Art, Challenges, and Research Opportunities

Recent advances in the large-scale adoption of information and communication technologies in manufacturing processes, known as Industry 4.0 or Smart Manufacturing, provide us a window into how the manufacturing sector will evolve in the coming decades. As a result of these initiatives, manufacturing firms have started to integrate a series of emerging technologies into their processes that will change the way products are designed, manufactured, and consumed. This article provides a comprehensive review of how service-oriented computing is being employed to develop the required software infrastructure for Industry 4.0 and identifies the major challenges and research opportunities that ensue. Particular attention is paid to the microservices architecture, which is increasingly recognized as offering a promising approach for developing innovative industrial applications. This literature review is based on the current state of the art on service computing for Industry 4.0 as described in a large corpus of recently published research papers, which helped us to identify and explore a series of challenges and opportunities for the development of this emerging technology frontier, with the goal of facilitating its widespread adoption.

Building Ant System for Multi-Faceted Test Case Prioritization

This article presents the empirical study of multi-criteria test case prioritization. In this article, a test case prioritization problem with time constraints is being solved by using the ant colony optimization (ACO) approach. The ACO is a meta-heuristic and nature-inspired approach that has been applied for the statement of a coverage-based test case prioritization problem. The proposed approach ranks test cases using statement coverage as a fitness criteria and the execution time as a constraint. The proposed approach is implemented in MatLab and validated on widely used benchmark dataset, freely available on the Software Infrastructure Repository (SIR). The results of experimental study show that the proposed ACO based approach provides near optimal solution to test case prioritization problem.

A web application for visualization, analysis, and processing of agricultural monitoring spatial-temporal data

The paper discusses some features of the client and server implementation of a web application for visualization, analysis, and processing of spatial-temporal data using the react JavaScript library and the organization of a software infrastructure for convenient development using the Redux library. Architectural solutions for building the system are presented. Further development plans are described.

A Blockchain-Supported Framework for Charging Management of Electric Vehicles

Profound changes driven by decarbonization, decentralization, and digitalization are disrupting the energy industry, bringing new challenges to its key stakeholders. In the attempt to address the climate change issue, increasing penetration of renewables and mobility electrification augment the complexity of the electric grid, thus calling for new management approaches to govern energy exchanges while ensuring reliable and secure operations. The emerging blockchain technology is regarded as one of the most promising solutions to respond to the matter in a decentralized, efficient, fast, and secure way. In this work, we propose an Ethereum-based charging management framework for electric vehicles (EVs), tightly interlinked with physical and software infrastructure and implemented in a real-world demonstration site. With a specifically designed solidity-based smart contract governing the charging process, the proposed framework enables secure and reliable accounting of energy exchanges in a network of trustless peers, thus facilitating the EVs’ deployment and encouraging the adoption of blockchain technology for everyday tasks such as EV charging through private and semi-private charging infrastructure. The results of a multi-actor implementation case study in Switzerland demonstrate the feasibility of the proposed blockchain framework and highlight its potential to reduce costs in a typical EV charging business model. Moreover, the study shows that the suggested framework can speed up the charging and billing processes for EV users, simplify the access to energy markets for charging station owners, and facilitate the interaction between the two through specifically designed mobile and web applications. The implementation presented in this paper can be used as a guideline for future blockchain applications for EV charging and other smart grid projects.

A Survey of The Various Techniques for Virtualization in Cloud Computing

Cloud computing is used to describe the delivery of software, infrastructure and storage devices over the internet. After evolution of the internet, Cloud computing is the next stage. Cloud Computing can simply the way in which the business operates, particularly in terms of needs of hardware. One is able to access and connect the same information but it can be done from anywhere and a more streamed technology installation is enjoyed by organization. VCloud Computing involves the concepts of parallel processing and distributed computing in order to provide the shared resources by means of Virtual Machines(VMs) hosted by physical servers. It is a service oriented design that reduces the cost of access to gather the information of the clients offer greater flexibility and demand based services. The benefits of Cloud Computing are far reaching. It is not a technology solution or server stored in another location but it is business enhanced computing that affects the business positively. Apart of its popularity it has some concerns which are becoming huddles for its wider adoption. A survey of cloud computing and virtual migration is presented in this paper. Keywords: Cloud Computing, Virtualization, SaaS, PaaS, IaaS

Mobile Sensing with Smart Wearables of the Physical Context of Distance Learning Students to Consider Its Effects on Learning

Research shows that various contextual factors can have an impact on learning. Some of these factors can originate from the physical learning environment (PLE) in this regard. When learning from home, learners have to organize their PLE by themselves. This paper is concerned with identifying, measuring, and collecting factors from the PLE that may affect learning using mobile sensing. More specifically, this paper first investigates which factors from the PLE can affect distance learning. The results identify nine types of factors from the PLE associated with cognitive, physiological, and affective effects on learning. Subsequently, this paper examines which instruments can be used to measure the investigated factors. The results highlight several methods involving smart wearables (SWs) to measure these factors from PLEs successfully. Third, this paper explores how software infrastructure can be designed to measure, collect, and process the identified multimodal data from and about the PLE by utilizing mobile sensing. The design and implementation of the Edutex software infrastructure described in this paper will enable learning analytics stakeholders to use data from and about the learners’ physical contexts. Edutex achieves this by utilizing sensor data from smartphones and smartwatches, in addition to response data from experience samples and questionnaires from learners’ smartwatches. Finally, this paper evaluates to what extent the developed infrastructure can provide relevant information about the learning context in a field study with 10 participants. The evaluation demonstrates how the software infrastructure can contextualize multimodal sensor data, such as lighting, ambient noise, and location, with user responses in a reliable, efficient, and protected manner.

Systematic Literature Review of Software as a Service [SaaS] in view of Security and Multitenancy

In early days of commercial software development, it was very expensive as multiple components were required such as - hardware, software, infrastructure to support mere an application development and implementation. Industry was using it with a note of burden to manage the support services. Visualizing these specific problems ICT took it as a challenge and introduces cost effective solution and bifurcated in Service components. Broadly a) Infrastructure as a Service b) Platform as a Service c) Software as a Service. Industry welcomed the approach and started handing over these services to market players and were able to focus on their key business areas. In recent development of cloud architecture these are becoming BUZZ word in industry and innovating traditional approaches. Keywords: IaaS, PaaS, SaaS, CaaS, Security, Multitenancy, Cloud Architecture

PlanAlyzer

Online experiments are an integral part of the design and evaluation of software infrastructure at Internet firms. To handle the growing scale and complexity of these experiments, firms have developed software frameworks for their design and deployment. Ensuring that the results of experiments in these frameworks are trustworthy---referred to as internal validity ---can be difficult. Currently, verifying internal validity requires manual inspection by someone with substantial expertise in experimental design. We present the first approach for checking the internal validity of online experiments statically, that is, from code alone. We identify well-known problems that arise in experimental design and causal inference, which can take on unusual forms when expressed as computer programs: failures of randomization and treatment assignment, and causal sufficiency errors. Our analyses target PLANOUT, a popular framework that features a domain-specific language (DSL) to specify and run complex experiments. We have built PLANALYZER, a tool that checks PLANOUT programs for threats to internal validity, before automatically generating important data for the statistical analyses of a large class of experimental designs. We demonstrate PLANALYZER'S utility on a corpus of PLANOUT scripts deployed in production at Facebook, and we evaluate its ability to identify threats on a mutated subset of this corpus. PLANALYZER has both precision and recall of 92% on the mutated corpus, and 82% of the contrasts it generates match hand-specified data.

Fourth party logistics firm assessment using a novel neutrosophic MCDM

The fourth party logistics (4PL) is an combiner that designs and implements the holistic supply chain solutions by using skills, knowledge, technology and resources of the service provider and its customer. A 4PL provider is also a technological service provider with eligible intellectual capital and the sufficient computer/software infrastructure. Defining the most appropriate 4PL service provider from the alternatives is not easy for companies, the solution can be addressed within the framework of the Multi-Criteria Decision Making (MCDM) problem, and subjective and uncertain data are required for this solution. “Fuzzy set theory” is a helpful tool for dealing with such subjectivity and uncertainty. In recent times, extensions of fuzzy sets have been evolved to address and describe the subjectivities and uncertainties more widely. Neutrosophic sets are one of the extensions of fuzzy sets, and unlike other extensions, they use the independent indeterminacy-membership function, thereby extracting important information and improving the accuracy of the decision-making process. A neutronophic MCDM method was proposed for the assessment of 4PL providers’ performance. In the application part of the study, neutrosophic language scale was used by three experts to evaluate the performance of 4PL providers. Then the closeness coefficient of each alternative was computed and sequenced in descending order. We also presented a comparative analysis with neutrosphic TOPSIS method. The results determined that the proposed neutrosophic MCDM method could be used in the performance evaluation of 4PL providers and similar problems.