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Researchers and companies are making great efforts to create new ways of interaction with a increasing number and types of electronic devices, with particular attention to the conversational interface, whether spoken or written. The cultural heritage domain can bring many benefits from the great effort in this field, as a smart conversational system can provide both room/hotel/apartment information and information related to the area, natural or cultural points of interest, tourist routes, social events, history etc. The paper’s main goal is to present a quick and effective service to the tourists visiting a city for the first time. Learning the cultural preferences of the users can enhance customer satisfaction, since a smart system can propose them customised tours in order to reach point of interests according to the expressed preferences. The interaction with the user is simplified by a conversational interface (chatbot). © Springer Nature Switzerland AG 2021.

The past few years have witnessed many software companies refactoring their monolithic applications into microservices to take advantage of containers in Cloud-native and DevOps-driven environments. Modern Cloud environments achieve high levels of scalability, flexibility, availability and business agility by combining two different kinds of virtualization: virtual machines and containers. The deployment of complex applications in such environments should be done by taking into account the interactions that may arise from the overlapping of these two different levels of virtualization. In this paper, we first describe a preliminary evaluation of a containerized application that has been obtained by refactoring a monolithic application into microservices. The application was deployed in a private Cloud system that relies on Kubernetes, which is a cluster management software for Docker containers that have been deployed on top of OpenStack-managed KVM virtual machines. Subsequently, in order to systematically investigate the possible interactions that can be produced when multiple containers running different kinds of workloads are activated on top of virtual machines, we present and analyze the results obtained by running different benchmarks in a testbed setup. From the analysis of the benchmark results, we derive some guidelines that should be taken into account by container schedulers when container orchestration platforms, such as Kubernetes, are deployed on top of a virtualized IaaS layer.

Artificial Intelligence application are becoming increasingly complex and sophisticated in order to shorten the gap between the users and digital systems. Nowadays, researchers and companies are making a big effort to develop new forms of interactions with a growing number and kinds of electronic devices, with a particular attention on the conversational interface, spoken or written. A chatbot is software that simulates and processes human conversations, allowing users to interact with digital devices as if they were communicating with a real person. In this paper we introduce a Chatbot for the cultural heritage domain [1], able to respond to a simple single-line query or to suggest users, as a digital assistants, by providing increasing levels of customisation through the collection and the processing of users’ conversations. © 2020, Springer Nature Switzerland AG.

Distribution of live multimedia streams to a high number of end users through an ISP network may be efficiently implemented through IP multicasting. Multicast traffic engineering with traditional decentralized approaches, however, is still a challenging problem for network operators. In this article we present a centralized approach to management of source-specific multicast traffic flows relying on software defined networking. Our approach is suitable for hybrid IP/SDN networks, where network nodes behave as traditional IP routers by default, but whose packet forwarding behavior may be customized for specific flows thanks to an OpenFlow-enabled control plane. We also describe a traffic management system that we implemented as a proof of concept, which can be used by an ISP to compute multicast distribution trees for a given set of channels to be distributed to their customers.

ETCS is an European system for high speed trains control and protection within ERTMS, the European standard for rail traffic management system. ERTMS/ETCS implementations use GSM-R for communications. As GSM-R is becoming obsolete, the adoption of more advanced technologies is investigated for next generation trains. New communication systems for railway infrastructures are expected to overcome the limitations of GSM-R, providing enhanced performance and reliability, as well as safety and security functionality to meet the requirements of the future signalling systems, control and users’ applications. While 4G technologies (LTE and LTE-A) are currently tested in a few field trials, railway operators should consider that fifth generation (5G) mobile communications technologies will soon be available. One of the foundational aspects of the 5G architecture is control-plane programmability, achieved through the SDN paradigm. Being aware that in a railway scenario this opportunity can be exploited to dynamically reconfigure the network behavior to better match the communication flows produced by moving trains, we aim at defining a framework, integrating formal modeling and analysis tools and techniques into a network emulator, to evaluate the impact on ERTMS/ETCS safety and security deriving from the adoption of an SDN model in the communication infrastructure. In this paper we describe a first step towards this objective, by presenting a first proof-of-concept implementation of the framework and its use to reproduce a simple railway infrastructure. In our current implementation, Finite State Machines are used to model communication protocols between ERTMS/ETCS entities and to automatically produce code and Promela models. Generated code is directly used to control the network behavior while the Promela model allows to generate and verify a network configuration by model checking.

In the last few years, there has been a remarkable growth in the number of data centers, which represent one of the leading sources of increased business data traffic on the Internet. An effect of the growing scale and the wide use of data centers is the dramatic increase of power consumption, with significant consequences both in terms of environmental and operational costs. Hence, energy awareness has become one of the major design constraints for Cloud infrastructures. In order to face these challenges, a new generation of energy-efficient and ecosustainable network infrastructures is needed. In this work, a novel energy-aware resource orchestration framework for distributed Cloud infrastructures is introduced, in order to manage both network and IT resources in a typical optical backbone. A high-level overview of the system architecture is provided by focusing on the definition of the different layers of the whole infrastructure, and introducing the Path Computation Element, which is the key component of the proposed architecture. The aim is to explain how both network and IT resources can be managed while, at the same time, the overall power consumption is being minimized and QoS requirements are satisfied. Finally, a green migration plan that is obtained by applying Virtual Machine relocation algorithms is discussed, in order to dynamically react to the fluctuating resource requirements of the VMs.