Search

The actions for limiting the climate change are significantly affecting the electrical power system. Indeed, the increase in renewable power sources and the progressive shut off of coal-fired power plants are transitioning the generation from a centralized to a decentralized paradigm. The latter may cause issues in a grid that was originally designed taking as granted the presence of several big power plants to be used as actuators for the system control. Considering voltage control, the actual control architecture is based on a hierarchical structure applied to a given set of rigidly subdivided control areas. Although such architecture is currently capable of maintain voltage control on the grid, the increase in converter interfaced generators (due to renewables exploitation) and the decrease of the buses short circuit powers (due to high power plants shut-off) may decrease its effectiveness in the future. To this aim, in this paper a coordinated decoupling voltage control is proposed, capable of using all the available reactive power sources on the grid as actuators. The issue of controlling a system with a variable number of actuators (due to generators connection and disconnection) is taken into account, proposing a suitable solution for avoiding transients during the switch between controllers having different output dimension. A brief discussion about communication (among actuators and controller) performances required for implementing the proposed control in the power system is also given.

Complex network analysis is a fundamental tool to understand non-trivial aspects of graphs and networks and is widely used in many fields. In this paper, we apply complex network techniques to study port networks, in which nodes are ports and edges are maritime lines between ports. In particular, we study the temporal evolution of several topological features of a network of ports, including connected components, shortest paths, and clustering coefficients. We built the network with three years of Automatic Identification System data from 2017 to 2019. We highlight several interesting trends and behaviors that differentiate long-range vessels from short-range vessels.

Nowadays, innovative digital services are massively spreading both in the public and private sectors. In this work we focus on the digital data regarding the mobility of persons and goods, which are experiencing exponential growth thanks to the significant diffusion of telecommunication infrastructures and inexpensive GPS-equipped devices. The volume, velocity, and heterogeneity of mobility data call for advanced and efficient services to collect and integrate various data sources from different data producers. The MobiDataLab H2020 project aims to deal with these challenges by introducing an efficient and highly interoperable digital framework for mobility data sharing. In particular, the project aims to propose to the mobility stakeholders (i.e., transport organising authorities, operators, industry, governments, and innovators) reproducible methodologies and sustainable tools that can foster the development of a data-sharing culture in Europe and beyond. This paper introduces the key concepts driving the design and definition of a cloud-based data-sharing federation we call the Transport Cloud platform, which represents one of the main pillars of the MobiDataLab project. Such platform aims to ensure transnational access to mobility data in a secure, efficient, and seamless way, and to ensure that FAIR principles (i.e., mobility data should be findable, accessible, interoperable, and reusable) are enforced.

Recent years are witnessing extensions of cyber-infrastructures towards distributed environments. The Edge of the network is gaining a central role in the agenda of both infrastructure and application providers. Following the actual distributed structure of such a computational environment, nowadays, many solutions face resource and application management needs in Cloud/Edge continua. One of the most challenging aspects is ensuring highly available computing and data infrastructures while optimizing the system's energy consumption. In this paper, we describe a decentralized solution that limits the energy consumption by the system without failing to match the users' expectations, defined as the services' Quality of Experience (QoE) when accessing data and leveraging applications at the Edge. Experimental evaluations through simulation conducted with PureEdgeSim demonstrate the effectiveness of the approach.

Federated Learning is a well-known learning paradigm that allows the distributed training of machine learning models. Federated Learning keeps data in the source devices and communicates only the model's coefficients to a centralized server. This paper studies the decentralized flavor of Federated Learning. A peer-to-peer network replaces the centralized server, and nodes exchange model's coefficients directly. In particular, we look for empirical evidence on the effect of different network topologies and communication parameters on the convergence in the training of distributed models. Our observations suggest that small-world networks converge faster for small amounts of nodes, while xx are more suitable for larger setups.

This deliverable is aimed at providing an updated report on state-of-the-art analysis, conceptual design and implementation of the Distributed Computing and Communication platform for CPSoS, that we refer as High-Performance Computing and Communication Infrastructure (HPC2I). After providing an update on the State-of-the-art for some of the related research activities we summarize the overall design and features of the HPC2I. We present a more concrete and detailed design of the conceptual, high-level system architecture previously described at M12. Said infrastructure lays the foundation of the TEACHING platform and supports the execution of project use cases. This deliverable also focuses on the implementation of the different software tools and prototypes that compose the HPC2I, highlighting the relationships they have with the work package activities (tasks). For each of these tools is also provided the rationale and a description of the base technologies on top of which the actual software components are developed.

This deliverable describes the implementation and operation of real-life experiments from the virtual reality, multiplayermobile gaming and QoE in digital content delivery domains in order to demonstrate how the ACCORDION solution has been applied in real-world environments. It provides a report on the progress of the operational experiments' specification; the preparation of the datasets and experimentation environment to be exploited in each pilot prototype; and the indicators to be measured in order to validate both the operational (business) and technical performance of the ACCORDION platform, according to the ACCORDION pilot plans and experimentation protocol. Furthermore, this deliverable provides the guidelines for the execution and evaluation of pilots, in order to serve as proof of concept for the effectiveness of ACCORDION offerings. This is the first out of two implementation cycles that will validate the promised impact delivery.

This document covers the implementation activities put in place in the ACCORDION consortium to enable a smooth integration of the distributed ACCORDION platform. The first part of the document describes the three core components of the platform, while the second part describes the first integration testing performed on such components.

This Project Quality Plan shows how quality aspects are considered in a variety of processes and activities within the ACCORDION project. The interrelated quality processes - planning, assurance and control - have impact on the project work from its start to its end. o Quality planning refers to quality policies like meetings, deliverables or publication policies, the definition of responsibilities as well as to manage the processes, in conjunction with the tasks dealing with the impact maximization activities, for the creation of a project visual identity including a project logo, project-like designed templates, website etc. In order to communicate adequately within the project as well as to project external persons, several collaborative tools, such as project policies including meetings, minutes, deliverables and the publication process of scientific papers, are established and explained in this document. o Quality assurance involves the establishment of Interim Management Reports, clear responsibilities and regular, clearly guided teleconferences. A well-defined internal review process further supports the quality assurance of deliverables. The plan is effective throughout the lifetime of the project but is open to revision if necessary. Responsibilities for quality planning, assurance and control are shared between all partners, which allow various views on quality issues in order to reach the optimal outcome.

The present document is the result of the collaborative effort of all ACCORDION partners participating to Task 2.2. The document offers a review of the state of the art for a series of topics strictly related to the work performed in the ACCORDION project. There is actually a strict correlation between the topics analyzed in this document and the Tasks that are part of the three research Work Packages of ACCORDION (WP3, WP4, and WP5). The main part of this document is section 2, in which all the state of the art analysis results have been reported. Section 2 has a subsection for each of the topics researched in the project, which includes: a description of the objectives, a list of outcomes expected from the research work, and an analysis of the state of the art. Section 2.1 (Resource monitoring & characterization) reports on monitoring, characterization and classification of Edge resources, identifying Prometheus, TOSCA and the automatic creation of taxonomies, respectively, as the best solutions for each of the three fields. Section 2.2 (Resource indexing & discovery) focuses on discussing solutions and data structures for organizing data in Resource Discovery Services. Section 2.3 (Edge storage, availability, reliability and performance) presents the advantages and disadvantages of both block and object storage, and then discusses some solutions, identifying OpenStack and MinIO as the most promising ones, even if not completely suitable. Some open research issues are also summarized. Section 2.4 (Pooling Edge resources), after listing some orchestration challenges typical of Edge computing and the techniques to cope with them, reports on several solutions to be considered as possible baselines for the ACCORDION Minicloud. Section 2.5 (??-based network orchestration) first lists the main machine learning techniques, then explores both Federated Learning techniques and further evolutions such as Meta-Learning Framework and Multi-Agent Reinforcement Learning. Section 2.6 (Resilience policies & mechanisms over heterogeneous edge resources) starts by discriminating between reactive and proactive protection strategies and describing some of them. Then other Fault Tolerance approaches are explored both reported in the literature and adopted in common distributed computing frameworks (Openstack, Cloudstack, Kubernetes, Openshift, and Mesos). Finally techniques for movement behaviour and resource utilization prediction are analysed, with a particular focus on the the LSTM model for Neural Networks. The conclusion is that the most promising solution to efficiently adapt the deep learning topologies for the fault tolerance needs is the hyper parameter optimization approach. Section 2.7 (Techniques for secure Edge application development & deployment) offers an analysis of the most common types of security attacks (Distributed Denial-of-Service, Malware Injection, and Authentication-based attacks) and their related countermeasures, along with some threat modelling methods, while DevSecOps methods and tools are also described. Section 2.8 (Privacy preserving mechanisms) starts by analysing Machine Learning techniques with a focus on privacy preserving ones, and then lists a number of works analysing how cookie synchronization techniques adopted for web advertising can expose users to privacy leaks. Section 2.9 (Application model for automatic deployment / migration of components) looks for application description models suitable for ACCORDION, i.e. with a machine-processable syntax, able to represent resource capacity requirements, containerization, and recovery policies. Three available solutions, TOSCA, Juju charms and CAMP, are compared along with the projects that are using them. Furthermore, tools supporting the three above solutions are described, and works researching the interoperability among the solutions are also analysed. Section 2.10 (Modelling and assessing QoE for NextGen applications) reports on different types of objective models that can be used to estimate the Quality of Experience (QoE) perceived by users of multimedia applications, and about the latest ITU-T Recommendations on QoE models and methodologies that can be applied to Next Generation Applications. For the ACCORDION project it has been decided to follow the standardized approach to build models for QoE assessment of ACCORDION applications. Section 2.11 (DevOps tools to automate Edge applications' deployment) sets the context and reports the starting points for the evaluation of Continuous Integration and Continuous Deployment tools. The identified state-of-the art solutions are Jenkins for the CI/CD pipeline and Kubernetes as the runtime deployment environment. Section 2.12 (Collaborative VR), starting from the general requirements for Virtual Reality applications, reports considerations about the still limited power of the available HMDs and discusses the trade-offs conditioning the possibility to offload computation from the end devices to the Edge. Finally Section 2.13 (Resource federation models) describes the main features of the federation model proposed by the H2020 5GeX project and lists the additional constraints and issues raised by an Edge providers' federation, which have to be further investigated. Not all project's research Tasks have a related section in this document about their main topics, yet. Monitoring the State of the Art is an ongoing activity in ACCORDION, and the next version of this document foreseen in M22 will improve the State of the Art analysis by adding further details, covering more topics and reporting on possible new approaches that appeared in the meantime.

The availability of the large amount of Automatic Identification System (AIS) data has fostered many studies on maritime vessel traffic during the recent years, often representing vessels and ports relationships as graphs. Although the continuous research effort, only a few works explicitly study the evolution of such graphs and often consider coarse-grained time intervals. In this context, our ultimate goal is to fill this gap by providing a systematic study in the graph evolution by considering voyages over time. three years of AIS data from the coastal waters of United States. By mining the arrivals and departures of vessels from ports, we build a graph consisting of vessel voyages between ports.We then provide a study on topological features calculated from such graphs with a strong focus on their temporal evolution. Finally, we discuss the main limitations of our approach and the future perspectives that will spawn from this work.

This deliverable provides a set of requirements of the ACCORDION project. This is a first iteration of the requirements collection process. This document is a fundamental pillar for the development of the whole architecture of the ACCORDION framework and provides requirements from both functional and non- functional sides, that are essential for the design and development of the ACCORDION framework. User requirements are listed in the table that will be the basis for further work. This document can be also considered as a checklist of the items that the consortium has to monitor, implement and evaluate during the project lifetime. In order to improve the quality of the presentation and thus ease the readability of the document, this deliverable summarizes the project's use cases (general summary and approach) and the ACCORDION platform requirements. The requirements are organized in three main categories: o General-purpose requirements: provided by the use case owners, are the key features of the NextGen applications shared by all the three use cases. o Use case related requirements: extracted by analysing the needs of the NextGen applications, filtered through technical and business-related criteria. o Technical/Scientific requirements: extracted from the use case related requirements and from the research goals of the project.

This deliverable is aimed at providing an initial report on state-of-the-art analysis, a preliminary requirements elicitation and conceptual design of the Distributed Computing and Communication platform for CPSoS, that we refer as High-Performance Computing and Communication Infrastructure (HPC2I). That is the infrastructure standing at the basis of TEACHING platform and support the execution of project use cases. The deliverable focuses on the several technical aspects impacting on the definition of the HPC2I. It resorts to the scientific literature and project use cases for the identification and analysis of the relevant research and technical challenges. Such challenges eventually contribute to the elicitation of requirements, that are reported in a formal way with project-wide identifiers. Later in the deliverable is given the definition of a conceptual, high-level system architecture, that is intended to be the basis on which to develop a concrete, full-fledged, architecture that will be presented in deliverable D2.2. Then, this deliverable summarizes some baseline tools and technologies that are suitable candidates to be used for supporting the project activities. Finally are drawn our conclusions.

This deliverable provides an account of the work done for the specification of the ACCORDION ecosystem architecture, which is mainly comprised of two artefacts: the infrastructure to support the cloud-edge continuum and the platform to manage the resources and the applications hosted in that infrastructure. The main outcomes of the work described in this deliverable are: a) the definition of components that comprise the architecture as well as their interactions, and; b) the assignment of the implementation of those components to specific project Tasks and partners. The deliverable describes the process for reaching to those outcomes, starting with the delineation of the scope of the described artefacts and working down to their specifics. The main approach used is the analysis of the platform use case scenarios. In practice, we analyze the scenarios and extract the required functionality. Then we cluster and map this functionality to components. Finally, we schematically present the interactions of those components using block and sequence diagrams. These outcomes are then validated against the use case requirements, especially those linked to the applications operation itself. This is meant to provide a proof-of-concept that the ACCORDION architecture is able to support the ACCORDION applications.