The unfolding climate crisis has resulted in a rising interest for increasing sustainability awareness and achieving energy savings worldwide. Several interventions within educational environments have been aimed at mobilizing younger audiences toward such goals. However, most of the interventions carried out so far are based on a subset of possible tools (e.g., IoT monitoring and gamification) and offer “all or nothing” approaches, which do not cope well with the uniqueness of schools and the need to adapt interventions to specific contexts (e.g. school size, building, curriculum, and teacher involvement). We present a large-scale intervention in 25 school buildings in Europe over the course of two school years. Our intervention was based on the installation of a relatively low-cost IoT infrastructure in schools, that produced real-time energy-related data from the school buildings involved, and the application of a strategy combining, in a flexible and customizable way, educational activities, monitoring tools, gamification, and competition to motivate behavior change and achieve energy savings. Overall, 2983 students and 204 educators were directly involved to a variable degree of participation. Our results indicate a positive overall result in terms of short-term energy savings in most schools involved, with an average reduction of 20%–25% in the energy that could be affected by end-users, as well as a 32.9% increase after the intervention in students self-reporting good or very good sustainability awareness. These findings suggest that such interventions can be a valuable step toward educating young students regarding sustainability and toward sustainable schools, if designed and implemented properly.

The Network Function Virtualisation (NFV) paradigm has revolutionised the way networks are designed, deployed, operated and managed by leveraging the flexibility, scalability and cost efficiencies of the cloud. The emergence of the Cloud-Edge Continuum allows network services, or parts of them, to be delivered close to the end user, especially when latency and throughput requirements are stringent. However, this perspective also poses several resource orchestration challenges, such as the need to cope with rapid changes in the infrastructure status, network and computing resource shortage, and diverse service requirements. In a previous paper, we demonstrated through simulations that a more flexible matching of network service requests with available resources can be enabled by the concept of multi-flavoured network services, i.e. services whose specifications include a full-fledged version and possibly alternative, less demanding versions (with less stringent resource requirements and/or fewer offered features). Since the VNF chain placement problem is known to be NP-hard, we propose a genetic algorithm-based metaheuristic to efficiently solve this variant of the VNF chain placement problem. Simulation results suggest that our genetic algorithm can achieve a profit improvement over a greedy solution of up to 8% in a 28-node topology and up to 6.6% in a 50-node topology.

This paper proposes a continuum-aware programming model enabling the execution of application workflows across the compute continuum: cloud, fog and edge resources. It simplifies the management of heterogeneous nodes while alleviating the burden of programmers and unleashing innovation. This model optimizes the continuum through advanced development experiences by transforming workflows into autonomous service collaborations. It reduces complexity in positioning/interconnecting services across the continuum. A meta-model introduces high-level workflow descriptions as service networks with defined contracts and quality of service, thus enabling the deployment/management of workflows as first-class entities. It also provides automation based on policies, monitoring and heuristics. Tailored mechanisms orchestrate/manage services across the continuum, optimizing performance, cost, data protection and sustainability while managing risks. This model facilitates incremental development with visibility of design impacts and seamless evolution of applications and infrastructures. In this work, we explore this new computing paradigm showing how it can trigger the development of a new generation of tools to support the compute continuum progress.

In the context of a 5G and beyond network operating in a smart city, in which the fixed network infrastructure is supported by a flock of unmanned aerial vehicles (UAV) operating as carriers of Virtual Network Functions (VNF), we propose a Mixed Integer Linear Programming (MILP) model to place chains of VNFs on a hybrid UAV-terrestrial infrastructure so to maximize the UAV lifetime while considering resource constraints and by taking into account the network traffic originated by crowds of people assembling in the city at given hotpoints. We formalize the UAV deployment problem and we test our solution with a practical scenario based on DoS detection system. The experimental results assess the deployment in a practical scenario of a DoS detection system and show that the proposed solution can effectively enhance the capability of the system to process the input flows under a DoS attack.

Intent-based Networking (IBN) aims at simplifying network configuration and management by using high-level objectives that express the desired state of the network rather than the details of how to implement it. In this article, we propose a declarative methodology and an associated open-source Prolog prototype (i) to model IBN intents related to the provisioning of Virtual Network Function (VNF) chains, and (ii) to process those intents to assemble and place a VNF chain that fulfils them. Our prototype is assessed over a lifelike motivating scenario.

Monitoring resource availability along Cloud-IoT networks in a lightweight and fault-resilient manner is a challenging research problem due to scarce resource availability, infrastructure dynamics, and platform heterogeneity. In this article, we illustrate a thorough experimental assessment of a self-organising and fault-tolerant monitoring service, FogMon, especially targeting Cloud-IoT settings and capable of probing hardware resource, latency and bandwidth. The assessment is carried out over networks made up of 20 to 40 nodes across two testbeds within the Fed4Fire+ federation. As a result of the assessment, we agilely improved and refined FogMon into FogMon 2, which settles at TRL5 and improves on monitoring accuracy and fault-resiliency. Experimental results show how FogMon 2 can promptly and suitably handle different types of infrastructure failure, with an average relative error of 10% on measurements and limited footprint on hardware and network resources.

Abstract Deploying Internet of Things (IoT)-enabled virtual network function (VNF) chains to Cloud-Edge infrastructures requires determining a placement for each VNF that satisfies all set deployment requirements as well as a software-defined routing of traffic flows between consecutive functions that meets all set communication requirements. In this article, we present a declarative solution, EdgeUsher, to the problem of how to best place VNF chains to Cloud-Edge infrastructures. EdgeUsher can determine all eligible placements for a set of VNF chains to a Cloud-Edge infrastructure so to satisfy all of their hardware, IoT, security, bandwidth, and latency requirements. It exploits probability distributions to model the dynamic variations in the available Cloud-Edge infrastructure and to assess output eligible placements against those variations.

Kubernetes container orchestration technology is beginning to address telco Network Function Virtualization (NFV) deployment needs of: i) multiple data-plane interfaces and one management-plane interface, and ii) support for various protocols/software stacks targeting I/O performance, including software acceleration technologies and software switch architectures. The purpose of this work is to accurately benchmark different network-virtualization architectures (OvS-DPDK, SR-IOV and VPP) in a Kubernetes deployment for telco data plane configurations. By leveraging industry-standard testing methodologies and an open source testing framework (VSPERF) that can control different hardware-based commercial and open source traffic generators, we benchmark the data plane of the telco NFV deployments. We also study the effects of different resource allocation strategies (CPU-Pinning, compute and storage resource variations, NUMA) on the data plane performance.

The adoption of Network Function Virtualization and Software Defined Networking technologies allow network infrastructure operator flexibly orchestrating resources to provide tenants with their own virtual network. However, access to computing and network resource management APIs is typically allowed only within the infrastructure domain and rarely disclosed to tenants for security and performance reasons. This may severely limit tenants capability in coping with demands of application-tailored network services, including Service Function Chaining (SFC). While the literature extensively addressed the challenges of SFC in the infrastructure domain, tenant-side SFC management is quite unexplored yet, although discussed also by a standardization group. This work proposes an SFC platform (called SFCLola) providing tenants with a latency-aware SFC management while minimizing support required from infrastructure operators. The platform encompasses two main levels: an end-to-end chain management level featuring a VNF selection algorithm and a forwarding mechanism that can be programmed and enforced within the tenant network of VMs without requiring access to the switches at the network infrastructure data plane. SFCLola has been implemented as software prototype and experimentally evaluated on a multi-DC infrastructure provided by the 5GINFIRE project.

Next generation cellular networks will be characterized by a very high density of heterogeneous base stations with strong consequences on operational expenditures and energy costs. In this paper a multiobjective optimization framework is proposed which is aimed at minimizing the power consumption of heterogeneous networks owned by rival mobile network operators: in particular, resource sharing is shown to guarantee the provided quality of service (QoS) and to achieve remarkable energy savings.

The adoption of virtualization technologies in networking is promoting a radical innovation in the way network services are managed and delivered. Indeed, some network services may be provisioned to cope with complex and unpredictable traffic demands by dynamically creating a sequence of Virtual Network Functions (VNFs) and steering traffic flows through them. In this context, the optimized deployment of network services, composed of VNFs that may be instantiated in multiple Data Centers (DCs), is one of the most challenging orchestration target. VNF placement is the problem of choosing the set of optimal locations for a chain of VNFs according to the service request and the current characteristics of available computing resources and network links. With respect to the state of the art, our original contribution reflects a multi-stakeholder perspective (subscriber, service providers, infrastructure providers) in a multi-DC environment. We thus consider the problem of placing VNFs to maximize primarily the number of accepted requests from a set of incoming requests and secondarily the satisfaction of subscribers’ preferences. Our model also allows to differentiate service requests in priority levels and guarantees that Quality of Service objectives for accepted service requests are fulfilled, including also a requirement on network service instantiation time. We provide an integer linear programming formulation of this problem that leverages a layered auxiliary graph built for each request in a set. Experimental evaluation is described in detail and an assessment of the proposed placement approach is performed along three main directions: (i) service acceptance ratio in online and offline placement, (ii) preferences’ satisfaction, and (iii) scalability expressed in terms of computational time. The performance of the approach is also compared to a greedy heuristic.

This paper proposes two virtual functions (VFs) placement approaches in a Fog domain. The considered solutions formulate a matching game with externalities, aiming at minimizing both the worst application completion time and the number of applications in outage, i.e., the number of applications with an overall completion time greater than a given deadline. The first proposed matching game is established between the VFs set and the fog nodes (FNs) set by taking into account the ordered sequence of services (i.e., chain) requested by each application. Conversely, the second proposed method overlooks the applications service chain structure in formulating the VF placement problem, with the aim at lowering the computation complexity without loosing the performance. Furthermore, in order to complete our analysis, the stability of the reached matchings has been theoretically proved for both the proposed solutions. Finally, performance comparisons of the proposed matching theory approaches with different alternatives are provided to highlight the superior performance of the proposed methods.

Network Function Virtualization and Software Defined Networking promise to radically innovate the way network services are provisioned, especially in terms of dynamic and flexible service delivery. Although the problem of NFV/SDN orchestration is recently gaining increasing interest, the problem of how effectively realizing the as-a-service exposure of network functions and services remains essentially uninvestigated. Leveraging service-oriented principles and best practices, in this paper we propose a two-layer service-oriented description model and a logical architecture for network service provisioning distinguishing business and orchestration scopes. Our proposal takes into account ETSI specifications for NFV orchestration and intent-based abstractions for the SDN controller northbound interface. We present a preliminary validation of the proposed approach focusing on the orchestration layer, based on a Proof of Concept development and testing. Finally, we discuss future work.

The adoption of the virtualization paradigm in both computing and networking domains portends a landscape of heterogeneous service capabilities and resources pervasively distributed and interconnected and deeply integrated through the 5G network infrastructure. In this service ecosystem, dynamic service demand can be flexibly and elastically accomplished by composing heterogeneous services provisioned over a distributed and virtualized resource infrastructure. Indeed, with the term Virtual Functions we refer to virtual computing as well as network service capabilities (e.g., routers and middlebox functions provided as Virtual Network Functions). In order to cope with the increasingly resource intensive demand, these virtual functions will be deployed in distributed clusters of small-scale datacenters typically located in current exchanges at the network edge and will supplement those deployed in traditional large cloud datacenters. In this work we formulate the problem of composing, computing and networking Virtual Functions to select those nodes along the path that minimizes the overall latency (i.e. network and processing latency) in the above mentioned scenario. The optimization problem is formulated as a Resource Constrained Shortest Path problem on an auxiliary layered graph accordingly defined. The layered structure of the graph ensures that the order of VFs specified in the request is preserved. Additional constraints can be also taken into account in the graph construction phase. Finally, we provide a use case preliminary evaluation of the proposed model.

Recent advances in network control and management technologies, such as software defined networking (SDN) and network function virtualization (NFV), are expected to make the network effectively able to cope with application service requirements in a more flexible and timely manner. We argue that SDN and NFV capabilities can be exploited in Next Generation Service Overlay Networks (NGSONs) for addressing contex-aware end-to-end data delivery services with adaptive composition of middlebox services when dynamically provisioned as virtual functions. In this paper we present a Service-Oriented SDN controller that allows for the programmable provision of data delivery paths through a dynamically established sequence of virtual middlebox functions, thereby accomplishing the deployment of adaptive network service chains in NGSON. In this way, an extended set of QoS requirements can be addressed that include specifications on processing functions to be traversed by service data while taking advantages from context-awareness and self-adaptation capabilities of NGSON. A use case analyis have been carried out on an experimental testbed about the effectiveness of the proposed approach in differentiating service data processing while optimizing the use of forwarding tables in the switches.

Drug prescription and administration processes strongly impact on the occurrence of risks in medical settings for they can be sources of adverse drug events (ADEs). A properly engineered use of information and communication technologies has proven to be a promising approach to reduce these risks. In this study, we propose PHARMA, a web information system which supports healthcare staff in the secure cooperative execution of drug prescription, transcription and registration tasks. PHARMA allows the easy sharing and management of documents containing drug-related information (i.e., drug prescriptions, medical reports, screening), which is often inconsistent and scattered across different information systems and heterogeneous organization domains (e.g., departments, other hospital facilities). PHARMA enables users to access such information in a consistent and secure way, through the adoption of REST and web-oriented design paradigms and protocols. We describe the implementation of the PHARMA prototype, and we discuss the results of the usability evaluation that we carried out with the staff of a hospital in Florence, Italy.

The rational use and management of energy is a key objective for the evolution towards the smart grid. In particular in the private home domain the adoption of wide-scale energy consumption monitoring techniques can help end users in optimizing energy consumption behaviors. While most existing approaches for load disaggregation and classification requires high-frequency monitoring data, in this paper we propose an approach for detecting and identifying the appliances in use by analysing low-frequency monitoring data gathered by meters (i.e. smart plugs) distributed in the home. Our approach implements a supervised classification algorithm with artificial neural networks and has been tested with a dataset of power traces collected in real-world home settings.

The technological advances in hardware and software communication technologies are speeding up the path towards the actualization of the Internet of Things. Nonetheless, novel requirements are emerging for the effective and efficient usage of the huge amount of available sensor information and functional capabilities. Several approaches have been proposed for leveraging the Web to this purpose (i.e. Web of Things). In this work, we propose an information-centric approach to enable a Web of Sensors. We combine the principles of Linked Data and Representational State Transfer (REST) architectural style to represent sensors as graphs of URI-addressable information nodes, which can be easily combined and reused for developing novel applications and creating software-based sensors (Virtual Sensors). Our approach relies on the adoption of a web-oriented middleware and information model, called InterDataNet.

The automated specification and execution of composite services are important capabilities of service-oriented systems. In practice, service invocation is performed by client components (stubs) that are generated from service descriptions at design time. Several researchers have proposed mechanisms for late binding. They all require an object representation (e.g., Java classes) of the XML data types specified in service descriptions to be generated and meaningfully integrated in the client code at design time. However, the potential of dynamic composition can only be fully exploited if supported in the invocation phase by the capability of dynamically binding to services with previously unknown interfaces. In this work, we address this limitation by proposing a way of specifying and executing composite services, without resorting to previously compiled classes that represent XML data types. Semantic and structural properties encoded in service descriptions are exploited to implement a mechanism, based on the Graphplan algorithm, for the run-time specification of composite service plans. Composite services are then executed through the stubless invocation of constituent services. Stubless invocation is achieved by exploiting structural properties of service descriptions for the run-time generation of messages.

Continuous care models for chronic diseases pose several technology-oriented challenges for home-based care, where assistance services rely on a close collaboration among different stakeholders, such as health operators, patient relatives, and social community members. This paper describes an ontology-based context model and a related context management system providing a configurable and extensible service-oriented framework to ease the development of applications for monitoring and handling patient chronic conditions. The system has been developed in a prototypal version, and integrated with a service platform for supporting operators of home-based care networks in cooperating and sharing patient-related information and coordinating mutual interventions for handling critical and alarm situations. Finally, we discuss experimentation results and possible further research directions.

Care models for chronic condition treatment place point-of-care in the community and at patient's home and imply an organized care system ("continuous care network"). The contribution of this work consists in the proposal of a service framework to support information acquisition, integration and sharing in continuous care networks. The framework is based on a service-oriented message-oriented middleware ("SAI middleware") easing the development of context-aware and information integration applications. We describe an ongoing case study aiming at demonstrating the use of the service framework in a reference application scenario for patient conditions monitoring, alarm detection and policy-based handling.

Several mobile guides exist providing tourists with location-based content delivery. This paper presents a novel mobile application, named InfoTour, aiming at enriching touristspsila experiences by supporting social interactions among tourists and by enabling seamless interaction with third-party service and data providers. The proposed system is based on service oriented architecture principles, and we describe here the main issues related to the system prototype design and development.