The work reflects about the importance of trust in data exchanges in the context of ever-increasing distributed computing ecosystems. It proposes the utilisation of an open-source technology that implements a direct acyclic graph incorporating peer nodes to validate messages in a decentralised network. The tool, IOTA, promises to solve the hindrances of blockchain solutions in highly heterogeneous, IoT-assimilable scenarios, adopting a more lightweight approach, removing the need of mining. The article explores the functioning of IOTA in distributed computing continuum cases, understanding the figures and mechanisms that govern the process. The authors link those reflections to the direct transfer into a research project, aerOS, that uses such a tool as intrinsic part of an IoT-Edge-Cloud continuum framework, enabling the immutability and non-repudiation of key messages in such environments. Also, the authors conclude analysing which next steps might follow to evolve from a not-fully decentralised implementation with the next releases of the tool, and the adaptations for the studied application.

There is great potential in leveraging Artificial Intelligence (AI) systems to optimize complex infrastructures, automate difficult tasks, or support autonomy and coordination between networked devices. However, advances in state-of-the-art AI often neglect features and/or requirements that businesses care deeply about, namely traceability and explainability. While majority of research concerning Explainable AI remains focused on weight modelling and timid gray-box approaches, the state-of-the-art has not explored much the deployment of semi-physical architectures combining fuzzy rule-based systems with more opaque models to improve explainability. This contribution aims to explore and make the case for a middle ground of mixed AI architectures that combine the performance of black-box AI models with a more explainable overall architecture, enabling operators to use them, while still retaining the core aspects of explainability, when compared to full black-box AI systems. This work contextualizes a potential application of such approach to the problem of Service Level Agreement compliance, in a case of microservice allocation decision over cloud (and cloud-like) infrastructures.

[EN] Digital Twins are software technologies that enable the modelling of real-world phenomena in digitised environments, representing and monitoring the reality of various processes, including IoT deployments. Since 2017, the use of Digital Twins has been increasing. However, in the road transport and logistics realm, the adoption rate remains low, primarily due to the costs of processing and validating data in centralised scenarios, among other factors. On the other hand, Blockchain technologies were created to provide immutable and decentralised data storage in diverse scenarios, adding a layer of isolation and reliability in heterogeneous solutions. This paper presents a case study proposing a Digital Twin based on open-source Blockchain technologies, such as FIWARE Canis Major. The primary goal is to design and implement a robust and efficient open-source architecture that allows for the control and optimisation of vehicle fleet allocations in logistics/transport companies within supply chain management. This case study aims to showcase the practical application of the proposed solution in a real-world context, providing insights into its eco-friendly and low-cost attributes while opening the door to a large number of additional applications.

The aim of this contribution is to analyse practical aspects of the use of REST APIs and gRPC to realize communication tasks in applications in microservice-based ecosystems. On the basis of performed experiments, classes of communication tasks, for which given technology performs data transfer more efficiently, have been established. This, in turn, allows formulation of criteria for the selection of appropriate communication methods for communication tasks to be performed in an application using microservices-based architecture.

New requirements, posed by the Next Generation IoT, demand design of novel reference architectures, providing foundation for implementation of Internet of Things (IoT) ecosystems. Building on cloud-native concepts (e.g. microservices, virtualisation, and containerization), a flexible architecture that answers requirements present in recent IoT deployments is introduced. A general description of components of the architecture (grouped in horizontal planes and vertical capabilities) is provided, together with formal definition of architectural views. Moreover, ground is laid for upcoming validation in real-world-anchored scenarios. Functional, node, deployment and data views are presented, each of them addressing concerns of different stakeholder groups, typically involved in an IoT deployments.