The recent introduction of full‐mesh virtual private network (VPN) solutions which offer near native performance, coupled with modern encryption algorithms and easy scalability as a result of a central control plane have a strong potential to enable the implementation of a seamless edge‐cloud continuum. To test the performance of existing solutions in this domain, we present a framework consisted of both essential and optional features that full‐mesh VPN solutions need to support before they can be used for interconnecting geographically dispersed compute nodes. We then apply this framework on existing offerings and select three VPN solutions for further tests: Headscale, Netbird, and ZeroTier. We evaluate their features in the context of establishing an underlay network on top of which a Kubernetes overlay network can be created. We test pod‐to‐pod TCP and UDP throughput as well as Kubernetes application programming interface (API) response times, in multiple scenarios, accounting for adverse network conditions such as packet loss or packet delay. Based on the obtained measurement results and through analysis of the underlying strengths and weaknesses of the individual implementations, we draw conclusions on the preferred VPN solution depending on the use‐case at hand, striking a balance between usability and performance.

The adoption of the active learning paradigm presents a series of challenges and uncertainties. However, its adoption may result in better academic results and a more engaging attitude towards learning. In this sense, this paper presents a case scenario in which such a change of paradigm has been deployed, where escape rooms have been introduced as an assessment tool in an active learning context. The way to move through those escape rooms is by taking a series of questionnaires based on the knowledge acquired, such that failing a test keeps the group in the same position and passing it makes them move according to the grades obtained. Surveys and comments offered by students show they were more motivated and engaged after this task, and an improvement in academic performance has been detected.

Novel computing paradigms aim to enable better hardware utilization, allowing a greater number of applications to be executed on the same physical resources. Serverless computing is one example of such an emerging paradigm, enabling faster development, more efficient resource usage, as well as no requirements for infrastructure management by end users. Recently, efforts have been made to utilize serverless computing at the network edge, primarily focusing on supporting Internet of Things (IoT) workloads. This study explores open issues, outlines current progress, and summarizes existing research findings about serverless edge computing for IoT by analyzing 67 relevant papers published between 01.01.2015 and 01.09.2021. We discuss the state-of-the-art research in 8 subject areas relevant to the use of serverless at the network edge, derived through the analysis of the selected articles. Results show that even though there is a noticeable interest for this topic, further work is needed to adapt serverless to the resource constrained environment of the edge.

The Internet of Things (IoT) is an emerging paradigm, even though it does not receive enough attention in many academic plans. In order to introduce our students to IoT, in this paper we present the overall results of a seminar dedicated to encourage them to design basic IoT projects on a software application called Packet Tracer v8.2.1. Such projects were carried out in groups, whereas the evaluation process was performed by means of filling in a peer review construct after the presentation was made by each team. This construct was previously validated by a panel of five experts by applying the Aiken’s V test, where an overall value of 0.907 was obtained. There were nine items within that construct, which were grouped into three dimensions, such as the quality of the prototypes presented, the communication skills during the presentations of the prototypes, and the alignment of the prototypes with SDGs. The average results obtained for all dimensions were all above 8 out of 10, whilst the medians were all 9 and the coefficient of variations were around 0.2. Those results showed high ratings with moderate variation among them. Furthermore, the reliability of the data collected in the evaluation process was assessed by applying the Cronbach’s alpha, accounting for values above 0.9 for each dimension and overall, which means an excellent internal consistency of such data. Likewise, the level of engagement during the activity was also measured by the means of the ISA engagement scale, resulting in an overall value around 6.5, with a median of 7, which proved a high engagement among students.

Data center organization and optimization are increasingly receiving attention due to the ever-growing deployments of edge and fog computing facilities. The main aim is to achieve a topology that processes the traffic flows as fast as possible and that does not only depend on AI-based computing resources, but also on the network interconnection among physical hosts. In this paper, graph theory is introduced, due to its features related to network connectivity and stability, which leads to more resilient and sustainable deployments, where cage graphs may have an advantage over the rest. In this context, the Petersen graph cage is studied as a convenient candidate for small data centers due to its small number of nodes and small network diameter, thus providing an interesting solution for edge and fog data centers.

IoT environments are forecasted to grow exponentially in the coming years thanks to the recent advances in both edge computing and artificial intelligence. In this paper, a model of remote computing scheme is presented, where three layers of computing nodes are put in place in order to optimize the computing and forwarding tasks. In this sense, a generic layout has been designed so as to easily achieve communications among the diverse layers by means of simple arithmetic operations, which may result in saving resources in all nodes involved. Traffic forwarding is undertaken by means of forwarding tables within network devices, which need to be searched upon in order to find the proper destination, and that process may be resource-consuming as the number of entries in such tables grow. However, the arithmetic framework proposed may speed up the traffic forwarding decisions as relaying on integer divisions and modular arithmetic, which may result more straightforward. Furthermore, two diverse approaches have been proposed to formally describe such a design by means of coding with Spin/Promela, or otherwise, by using an algebraic approach with Algebra of Communicating Processes (ACP), resulting in a explosion state for the former and a specified and verified model in the latter.