Osmotic computing is a new paradigm to support the efficient execution of Internet of Things (IoT) services and applications at the network edge. This paradigm is founded on the need for a holistic distributed system abstraction enabling the deployment of lightweight microservices on resource-constrained IoT platforms at the network edge, coupled with more complex microservices running on large-scale datacenters. This paradigm is driven by the significant increase in resource capacity/capability at the network edge, along with support for data transfer protocols that enable such resources to interact more seamlessly with datacenter-based services. This installment of "Blue Skies" discusses osmotic computing features, challenges, and future directions.

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.

The advent of both Cloud computing and Internet of Things (IoT) is changing the way of conceiving information and communication systems. Generally, we talk about IoT Cloud to indicate a new type of distributed system consisting of a set of smart objects, e.g., single board computers running Linux- based operating systems, interconnected with a remote Cloud infrastructure, platform, or software through the Internet and able to provide IoT as a Service (IoTaaS). In this context, container-based virtualization is a lightweight alternative to the hypervisor-based approach that can be adopted on smart objects, for enhancing the IoT Cloud service provisioning. In particular, considering different IoT application scenarios, container-based virtualization allows IoT Cloud providers to deploy and customize in a flexible fashion pieces of software on smart objects. In this paper, we explore the container-based virtualization on smart objects in the perspective of a IoT Cloud scenarios analyzing its advantages and performances.

Monitoring activities detect changes in the environment and can be used for several purpose. To develop new advanced services for smart environments, data gathered during the monitoring need to be stored, processed and correlated to different pieces of information that characterize or influence the environment itself. In this paper we propose a Cloud storage solution able to store huge amount of heterogeneous data, and provide them in a uniform way. To this aim, we adopt an hyrid architecture that couple Document and Object oriented strategies, in order to optimize data storage, querying and retrieval. In this paper, we present the architecture design and discuss some implementation details in the development of the architecture within a specific use case