Edge computing extends the capabilities of computation, network connection, and storage from the cloud to the edge of the network. It enables the application of business logic between the downstream data of the cloud service and the upstream data of the Internet of Things (IoT). In the field of Industrial IoT, edge computing provides added benefits of agility, real-time processing, and autonomy to create value for intelligent manufacturing. With the focus on the concept of edge computing, this article proposes an architecture of edge computing for IoT-based manufacturing. It also analyzes the role of edge computing from four aspects including edge equipment, network communication, information fusion, and cooperative mechanism with cloud computing. Finally, we give a case study to implement the active maintenance based on a prototype platform. This article aims to provide a technical reference for the deployment of edge computing in the smart factory.

At present, smart manufacturing computing framework has faced many challenges such as the lack of an effective framework of fusing computing historical heritages and resource scheduling strategy to guarantee the low-latency requirement. In this paper, we propose a hybrid computing framework and design an intelligent resource scheduling strategy to fulfill the real-time requirement in smart manufacturing with edge computing support. First, a four-layer computing system in a smart manufacturing environment is provided to support the artificial intelligence task operation with the network perspective. Then, a two-phase algorithm for scheduling the computing resources in the edge layer is designed based on greedy and threshold strategies with latency constraints. Finally, a prototype platform was developed. We conducted experiments on the prototype to evaluate the performance of the proposed framework with a comparison of the traditionally-used methods. The proposed strategies have demonstrated the excellent real-time, satisfaction degree (SD), and energy consumption performance of computing services in smart manufacturing with edge computing.

The near future evolution of the cloud computing can be hypothesized in three subsequent stages: stage 1 "Monolithic" (now), cloud services are based on independent proprietary architectures; stage 2 "Vertical Supply Chain", cloud providers will leverage cloud services from other providers; stage 3 "Horizontal Federation", smaller, medium, and large cloud providers will federate themselves to gain economies of scale and an enlargement of their capabilities. Currently, the major clouds are planning the transition to the stage 2, but how to achieve the stage 3 is unclear because some architectural limitations have to be overcome. In this paper, considering a general cloud architecture, we highlight such limitations and propose some enhancements which add new federation capabilities. In order to address such concerns we propose a solution based on the Cross-Cloud Federation Manager, a new component placeable inside the cloud architectures, allowing a cloud to establish the federation with other clouds according to a three-phase model: discovery, match-making and authentication.

This article discusses the main advantages and challenges of adopting microservices in cloud computing. The microservices architecture allows software developers to build a distributed application as a set of independent components that work together. This model isn't new, but, applied in cloud systems, it increases datacenter scalability and reliability. The authors discuss available technologies for deploying and controlling microservices-based application architectures in the cloud.

The sudden traffic slowdown especially in fast scrolling roads and highways characterised by a scarce visibility is one of the major causes of accidents among motorised vehicles. It can be caused by other accidents, work-in-progress on roads, excessive motorised vehicles especially at peak times and so on. Typically, fixed traffic sensors installed on roads that interact with drivers’ mobile APP through the 4G network can mitigate such a problem, but unfortunately not all roads and highways are equipped with such sensors. In this paper, we discuss a possible alternative solution for addressing such an issue considering mobile traffic sensors directly installed in private and/or public transportation and other volunteer vehicles. In such a scenario a fast real-time processing of big traffic data is fundamental to prevent accidents. In particular, we discuss an IoT Cloud system for traffic monitoring and alert notification based on OpenGTS and MongoDB. Our IoT Cloud system, besides for private drivers, it is very useful for drivers of critical helpful service such as ambulances. Experiments prove that our system provides acceptable response times that allows’ drivers to receive alert message in useful time so as to avoid the risk of possible accidents.

In a pandemic situation such as that we are living at the time of writing of this paper due to the Covid-19 virus, the need of tele-healthcare service becomes dramatically fundamental to reduce the movement of patients, thence reducing the risk of infection. Leveraging the recent Cloud computing and Internet of Things (IoT) technologies, this paper aims at proposing a tele-medical laboratory service where clinical exams are performed on patients directly in a hospital by technicians through IoT medical devices and results are automatically sent via the hospital Cloud to doctors of federated hospitals for validation and/or consultation. In particular, we discuss a distributed scenario where nurses, technicians and medical doctors belonging to different hospitals cooperate through their federated hospital Clouds to form a virtual health team able to carry out a healthcare workflow in secure fashion leveraging the intrinsic security features of the Blockchain technology. In particular, both public and hybrid Blockchain scenarios are discussed and assessed using the Ethereum platform.