Radio Frequency Fingerprinting (RFF) is a physical (PHY) layer security technique enabling the identification of a radio transmitter without resorting to shared secrets while combining deep learning and signal processing techniques. State-of-the-art scientific contributions focus on improving identification performance in different scenarios and configurations while considering the RFF methodology as a black-box. In this work, we apply eXplainable Artificial Intelligence (XAI) techniques to expose the discriminative features allowing a neural network model to identify radio transmitters at the PHY layer. Our analysis considers image-based RFF classifiers, where received signals (in the form of IQ symbols) are processed into images, and proves that symbols contribute unequally to the identification of the transmitter. In particular, our results demonstrate that image pre-processing can be leveraged to significantly reduce the overhead of training (up to 50%) and testing (up to 70%) without affecting the classifier's final accuracy.

Today, an unprecedented number of researchers and companies are interested in exploring advanced and optimized protocols and algorithms making the 5G New Radio technology (and of course its evolutions) able to support different services under heterogeneous scenarios. In most cases, their studies leverage computer simulations and simple datasets describing isolated functionalities of the overall complex mobile communication system. Accordingly, despite all these valuable and available tools, there remains a lack of comprehensive, high-quality datasets that can support in-depth analysis, modeling, and testing of the 5G New Radio in real-world deployments. To bridge this gap, this paper presents a 5G dataset for Quality of Experience assessment in the new RAdio (5G-QoERA). Focusing the attention on a video streaming use case, the goal of the dataset is to indicate the level of quality experienced by mobile end users in terms of Mean Opinion Score, while jointly considering several influencing aspects such as real user mobility traces, real-world base station deployments and related radio map environments, variable scheduling decisions, and application-level details. After detailing the generation process of the dataset, a preliminary analysis of its features is conducted to underline the possible research activities that can take advantage of its usage.

As well known, the integration of Unmanned Aerial Vehicles (UAVs) and Intelligent Reflecting Surfaces (IRS) can enhance the reliability, coverage, robustness, and efficiency of next-generation wireless and mobile networks. Nevertheless, the performance of UAV-mounted Passive Metasurfaces (PMs), referred to as Aerial PMs (APMs), is significantly influenced by system configurations, electromagnetic signal propagation, UAV mobility, and wobbling. While most state-of-the-art studies rely on analytical models and simulations to assess these factors, this work presents an experimental investigation of an APM in a realistic operating environment. To this end, we developed an advanced experimental testbed that combines a precision tracking system with real-time electromagnetic measurements, enabling a detailed characterization of the metasurface response in an indoor scenario. Additionally, we compared the feasibility of APMs against a static setup where the metasurface is mounted on a fixed structure. Experimental results demonstrate that APMs can effectively maintain signal quality and spectral efficiency. However, they also reveal the impact of positioning, orientation, and in-flight stability on overall system performance. Our observations provide interesting insights into optimizing Aerial IRS-assisted networks, contributing to the design of more robust solutions for the Beyond 5th and 6th Generation networks.

In an era dominated by digitalization in corporate strategies, the effectiveness of network infrastructures constitutes the foundation upon which enterprises build their businesses. Within this context, Intent-Based Networking (IBN) emerges as a networking paradigm that addresses the need for autonomous and intelligent systems, shifting network management from static to dynamic and automated processes. Despite its significant advancements in network automation, IBN introduces new complexities and challenges, particularly concerning the assessment of reliability or trustworthiness. Formulating intent without thorough investigation of users’ intentions could potentially lead to deliberate network sabotage, denial of services, data breaches, and privilege escalations, thereby posing significant risks to enterprise networks. To bridge this gap, this study proposes a novel Malicious Intent Detection (MID) module within the IBN framework to construct a security knowledge base for accurately classifying enterprise users’ intentions. Specifically, it detects malicious expressions directly during the intent processing stage, thereby preventing the formulation of disruptive network configurations or policies derived from malicious intents. The obtained results demonstrate the effectiveness of the proposed solution, with the ability to detect 94% of malicious intentions and achieve an accuracy of up to 93%.

In the era of pervasive connectivity, the effective provisioning of multimedia services surely represents a cornerstone challenge for both infrastructure and service providers. Given the recent evolution of Beyond 5G/6G networks, it is conventionally accepted that a Network Operator (infrastructure provider) shares its resources with tenants (service providers) by giving them the possibility to autonomously and efficiently configure the application services they provide to end users. To this end, this contribution proposes a cutting-edge framework for multimedia service provisioning, that harnesses the power of Artificial Intelligence (AI) in conjunction with Digital Twin Networks (DTNs). Specifically, it considers the real network features collected from the physical real network through Software-Defined Networking Controllers to build the DTN, whose purpose is to provide present and future physical, network, and application statistics through AI for efficient and proactive resource allocation. The DTN exposes to the tenant a concise set of monitoring parameters related to actual network-specific statistics and Quality of Service metrics and also future ones thanks to Deep Learning, without sharing in-depth details of the underlying network through Machine Learning (clustering). This information will be exploited by the service orchestrator for optimal resource allocation and redistribution, which will be deeply investigated in future works.

Law Enforcement Agencies (LEAs) heavily rely on Lawful Interception (LI) tools to investigate criminal and terrorist activities. The growing frequency of cybercrime, terrorism-related offenses, and illegal trades in the European Union (EU) has driven LEAs to explore novel LI techniques that align with the developing 5G and Beyond 5G network architectures. Moreover, the emergence of extremely dynamic and distributed networks, the increased usage of end-to-end encryption applications, and privacy protections present limitations for traditional LI approaches. In order to provide a technological solution capable of extending the 3GPP LI standard, this paper presents a novel LI framework designed on top of the standardized 3GPP LI architecture, leveraging an inspection-friendly end-to-end cryptography mechanism (e.g., a Key Escrow algorithm) at the application layer. Moreover, the proposed Lawful Interception (LI) framework enables authorized LEAs to decrypt intercepted end-to-end encrypted data within the core network. Firstly, a security proof validates the security of the proposed LI framework under two attack scenarios. Subsequently, a proof-of-concept workstation implementation that emulates a 5G network for end-to-end data exchange and cloud-based deployment validates the suggested LI framework by affirming the LEA capabilities in decrypting intercepted data. Additionally, the system performance has been studied through experimental tests, ensuring the scalability of the conceived solution and revealing the possibility of intercepting data with mainly real-time latency without affecting the Quality of Service (QoS) experienced by the user.

As the telecommunications industry embarks on the transition to Sixth-Generation (6G) networks, this paper examines the integration of Non-Terrestrial Networks (NTN), and in particular satellite backhauling, in the context of Fifth-Generation (5G) systems. The Integrated Access and Backhaul (IAB) technology, conceived as a wireless terrestrial backhauling system in the Next Generation Radio Access Network (NG-RAN), has been identified as a possible enabler for the integration of satellite nodes. Despite the work already done in this direction, the combination of IAB architectures with satellite nodes operating in both the access and backhaul side requires further evaluations on feasibility and limitations for networks integrating Low Earth Orbit (LEO) and Geostationary Earth Orbit (GEO) satellites. To this end, this work contributes providing insights on background technologies, as well as a detailed analysis of the issues and challenges arising from such integration and a definition of use cases to support narrow-band and broadband services. Furthermore, the design and implementation of a simulation tool is proposed for a performance evaluation in terms of registration time, link capacity, single-hop and end-to-end delay. Results show that the integration turns out to be feasible, even if with strong constraints coming from the satellite system rather than the IAB usage itself. Indeed, the earth-satellite link in LEO systems has a significant impact on the packet delivery time due to the discontinuous coverage. In case of GEO satellite instead, a non-terrestrial backhaul link could limit the performance of the whole system, especially at lower elevation angles.

This paper describes the integration of Terrestrial and Non-Terrestrial Networks, wherein space-based network entities collaborate with traditional and emerging terrestrial communication frameworks to furnish pervasive, resilient, and three-dimensional wireless connectivity worldwide toward the 6th Generation of communication networks. This integration supports heterogeneous services, such as enhancing coverage, user experience, system capacity, service reliability, and availability, while also providing high-speed connectivity in remote or disaster-affected areas, improving existing 5th Generation technologies. Various Use Cases are detailed, highlighting the pivotal roles that Non-Terrestrial Networks play in distinguishing between urban/suburban and rural environments, with particular emphasis on transportation ecosystems. Through this analysis, Key Performance Indicators and requirements are delineated to characterize the requisite service quality for these diverse Use Cases. The paper further presents an overview of potential and standards-compliant integrated Terrestrial/Non-Terrestrial architectures, delineating their roles both in backhauling and access across different layers of Non-Terrestrial systems and elements. These insights are derived from studies conducted within the Integrated Terrestrial And Non-Terrestrial Networks (ITA-NTN) project, part of the European Union initiative defined as the Italian National Recovery and Resilience Plan (NRRP) RESTART Research Program.

Attribute-based Searchable Encryption is emerging as a promising cryptographic technique supporting data protection, flexible access control, and keyword search over encrypted data. The current scientific literature already investigated its adoption in cloud-based services and additionally explored the usage of edge computing to implement some of the cryptographic tasks in scenarios with limited computational capabilities (such as Internet of Things). In the majority of the available solutions, however, the remote cloud is still responsible for data storage, keyword search over encrypted data, and delivery tasks. Indeed, the heavy computational load generated in scenarios with multiple data producers and data consumers (never studied yet) and large communication latencies can inevitably compromise the overall system performance. To bridge this gap, this work proposes a decentralized service architecture offering privacy-preserving data dissemination, by jointly leveraging attribute-based Searchable Encryption techniques, publish–subscribe communication model, and edge computing capabilities. Here, customized Edge Servers are deployed at the network edge to (i) collect subscription requests encoded via Searchable Encryption Trapdoors, (ii) receive data publications, encrypted via Attribute-based Searchable Encryption scheme, (iii) implement keyword search over encrypted data, and (iv) deliver encrypted data only to authorized requesters. Experimental tests explored the impact of network configuration and traffic load on both communication latency and energy consumption. Obtained results demonstrated the unique ability of the proposed solution to achieve shorter data delivery delays as well as less energy consumption with respect to cloud-based alternatives.

In the upcoming Sixth-Generation (6G) of mobile communication systems, space network entities will cooperate with conventional terrestrial networks to provide three-dimensional wireless connectivity around the World. By considering the resulting massive amount of data to be managed into non-terrestrial segments, it will be necessary to dynamically configure functionalities across space network entities. Preliminary contributions in this context focus on quasi-static scenarios, while ignoring the challenging issues (i.e., intermittent visibility, dynamic network configuration, and communication delays) introduced by satellites’ movement and communication protocols enabling the integration of terrestrial and non-terrestrial networks. To bridge this gap, this work presents a network architecture with novel orchestration capabilities of services into non-terrestrial segments. In the proposed approach, the interaction between terrestrial and non-terrestrial entities and the cloud has been detailed across service request, configuration, and provisioning phases. Then, starting from a system model describing the network configuration and the resulting deployment delays of services, an optimization problem has been formulated to dynamically allocate Virtual Network Functions (VNFs) among LEO CubeSats over a looking-ahead horizon, based on service requests, computational capabilities of the involved CubeSats, visibility matrices, and expected deployment delay bounds. Finally, the proposed optimization problem has been solved through three heuristic strategies. Computer simulations have been carried out to demonstrate the ability of the developed strategies to achieve results close to the optimal solution and to ensure better performance against a benchmark scheme.

In the emerging 6G satellite deployments, the interaction between Non-Terrestrial Network terminals and satellite constellations will generate a large surface of attack, which requires the design of novel security architectures. The scientific literature suggests to implement security services as Virtual Network Functions, installed onboard the satellites. The dynamic orchestration of these services, however, still represents a challenging and open research issue. To bridge this gap, this paper presents a novel approach willing to allocate security Virtual Network Functions across satellites, in a dynamic and optimal way. To this end, an optimization problem is formulated by deeply considering the intermittent connectivity between terminals on the Earth and the satellite constellation, the limited computational capabilities of satellites, and the need to provide secure Virtual Network Functions before a given time deadline. Then, the Tabu Search algorithm is used to solve the optimization problem and achieve preliminary results in realistic scenarios. The study illustrates the feasibility of the proposed approach and highlights the issues to address in future research activities.

The fifth-generation and beyond (B5G) communication systems are evolving for computation-intensive and communication-sensitive applications with diverse Quality-of-Service (QoS) requirements on processing, bandwidth, latency, and reliability. This work focuses on an ultra-dense edge network with Multi-access Edge Computing (MEC) facilities, serving agents that execute their tasks by touring the cells. Specifically, we propose a novel methodology for optimally and flexibly managing task offloading in the context of heterogeneous computing and communication services required by real-time robotic applications. Differing from many related work, the proposed approach takes the number of admitted service migrations and the QoS upper and lower bounds as binding constraints. We model the QoS evolution based on the agent positions, the MEC servers serving the agents, the QoS requirements, the communication capabilities in the edge network, and the computing capabilities of the servers. The model is formalized as a mixed-integer linear program (MILP) to obtain an optimal schedule for the service migrations and communication and computation bandwidth allocation. Experimental results show that the approach outperforms baseline approaches and can scale to large deployments.

Digital services and digital service chains are the heart beating of the modern economy. Their composition involves several players, i.e., processes, software, devices, and many kinds of data exchanged among them. In such a scenario, it is important to guarantee data confidentiality, integrity, as well as authentication and authorization procedures between the communicating parties of a service chain. Cyber-security frameworks are explicitly designed for this purpose. They rely on the integration of different software modules, mutually interfaced to accomplish complex security tasks. Nevertheless, it is important to guarantee a high level of protection during data exchange among the modules. Currently, standardized authentication and authorization mechanisms are implemented through proprietary “As-a-Service” products, but the deployment of a mature on-premise solution is still missing. To bridge this gap, this contribution proposes an authentication and authorization module that automatically protects the information flowing among the modules of cyber-security frameworks. It guarantees resource availability only to authenticated subjects. Thus, their operations are confined in what actions they are authorized for. The proposed module has been implemented and tested in a real cyber-security framework under development into the H2020 GUARD project. Experimental tests show that the proposed module enables authentication and authorization procedure delegation among GUARD modules, which eases their implementation, while maximizing the flexibility of the set of access control policies and an efficient protection of the services.

This contribution proposes a novel task offloading scheme for robotics applications in Information-Centric Networks. The reference scenario includes heterogeneous agents connected to various wireless Network Attachment Points, asking for computational services to Multi-access Edge Computing servers deployed at the network edge. It also uses Information-Centric Networking facilities to implement resource announcement, resource discovery, and service provisioning. The effectiveness of the conceived solution has been tested through experimental tests in realistic scenarios.

The Social Internet of Things is gaining momentum thanks to its unique capability of i) autonomously building social relationships among smart objects and ii) supporting the novel services within the Social Network. During the service provisioning, the Trust Management System is in charge of selecting suitable objects able to accomplish the requested services. In this context, available solutions present two relevant issues to be solved. First, they generally assume to select social objects that only achieve higher trustworthiness without considering their actual computing capabilities. Indeed, it would significantly compromise the Quality of Experience in the Social Network of objects. Second, they assume to implement this task directly within constrained devices, becoming unpractical considering their limited computational and storage capabilities. To improve and speed up service provisioning, this paper proposes a novel Trust Management System scheme that fairly distributes service requests by jointly considering the trustworthiness and resource capabilities of available objects. This Trust Management System has been designed to exploit fog computing to efficiently handle the whole process of service provisioning in real-world deployments while relieving constrained devices from all processing and storage efforts. Its behavior is investigated through computer simulations. Obtained results demonstrated that the conceived approach outperforms baseline solutions in terms of latency, fairness in services distribution, and responsiveness in malicious nodes' detection.

The adoption of the Narrowband-Internet of Things technology in satellite communications intends to boost Internet of Things services beyond the boundaries imposed by the current terrestrial infrastructures. Apart from link-level studies in the scientific literature and preliminary 3GPP technical reports, the overall debate is still open. To provide a further step forward in this direction, the work presented herein pursues a novel service-oriented methodology to design an effective solution, meticulously stitched around application requirements and technological constraints. To this end, it conducts link-level and system-level investigations to tune physical transmissions, satellite constellation, and protocol architecture, while ensuring the expected system behavior. To offer a real smart agriculture service operating in Europe, the resulting solution exploits 24 low-Earth orbit satellites, grouped into eight different orbits, moving at an altitude of 500 km. The configured protocol stack supports the transmission of tens of bytes generated at the application layer, by also counteracting the issues introduced by the satellite link. Since each satellite has the whole protocol stack onboard, terminals can transmit data without the need for the feeder link. This ensures communication latencies ranging from 16 to 75 min, depending on the served number of terminals and the physical transmission settings. Moreover, the usage of the early data transmission scheme reduces communication latencies up to 40%. These results pave the way toward the deployment of an effective proof of concept, which drastically reduces the time to market imposed by the current state of the art.

In the Social Internet of Things paradigm, the Trust Management System computes trust values of involved social objects, identifies trusted relationships, and selects the most suitable object able to provide a target service. State-of-the-art mechanisms conceived to address these tasks generally avoid considering the actual availability of social objects and demand the implementation of complex algorithms to constrained nodes. This work presents a novel multi-tiered and fog-based Social Internet of Things architecture to solve these open issues, ensuring fast service provisioning, high scalability, fault tolerance, and security. On the one hand, the Trust Management System hosted at the first fog layer of the architecture jointly addresses the trustworthiness of service providers and monitors the re-source availability exposed by social objects, thus simplifying the forwarding of service requests to trusted and unloaded nodes. From another hand, to securely implement advanced services at a large scale, a second fog layer exploits a Blockchain-based storage for sharing services, relationships, and trust values across organizations and service domains. Computer simulations demonstrate the effectiveness of the proposed architecture in a realistic Social Internet of Things while showing the performance gain obtained against a baseline approach.

Named-Data Networking is a prominent solution for offering flexible communications in Metropolitan Area Networks. Its features were recently extended with SDN and MEC capabilities for better supporting consumer mobility and improving packet forwarding functionalities. However, the scientific literature lacks a thorough investigation on the impact on the energy consumption of these protocols. Focusing the attention on the novel approach presented by the same authors of this paper, this contribution analyzes the energy saving in Information-Centric Metropolitan Area Networks. Results demonstrate the efficacy of the investigated approach by evaluating the different components of energy consumption in the considered scenario.

Satellite Communication is expected to play a leading role in 5G & Beyond networks. Current studies, however, focus the attention on physical and link-level aspects, while ignoring to evaluate system-level performance. This paper presents a novel simulation tool, conceived as a new module for the open-source 5G-air-simulator, modeling NB-IoT satellite-based communication systems. Specifically, it implements several link-to-system abstraction models, the cell selection procedure, and a configurable satellite constellation. Furthermore, these essential features are successfully integrated within the rest of the 5G-air-simulator, thus offering the opportunity to test flexible network deployments (e.g., by varying the number and the distribution of users) under different application statistics. To demonstrate the actual effectiveness of the developed tool, this work also presents a preliminary performance assessment of an NB-IoT satellite-based communication system enabling reference monitoring scenarios.

Piezoelectric nanogenerators recently emerged as a turning point in the design of energy-aware and energy harvesting transmission scheme at the nanoscale. This work considers their adoption in diffusion-based molecular communications, proposing a power control strategy based on feedback control theory. In particular, the transmission power of an electrochemical nanodevice fed by a piezoelectric nanogenerator is dynamically set proportionally to the available energy budget, by using a closed-loop control scheme. The resulting system is analytically modeled with a discrete-time nonlinear state equation. The range of acceptable values of the proportional gain is theoretically derived by studying technological constraints and global asymptotic stability. The impact of the proportional gain on both output variance and time constant of the linearized system around the equilibrium point is also investigated. Computer simulations validate the theoretical analysis under different parameter settings. The comparison against state of the art transmission scheme also demonstrates the unique ability of the conceived approach to ensure, at the equilibrium, the targeted performance level.

Multi-access Edge Computing represents a key enabling technology for emerging mobile networks. It offers intensive computational resources very close to the end-users, useful for task offloading purposes. Many scientific contributions already proposed approaches for optimally allocating these resources over time. However, most of them fail to take advantage of the prediction of both users’ mobility and service demands over a look-ahead temporal horizon. To bridge this gap, this paper formulates a novel methodology for anticipatorily allocating communication and computational resources at the network edge, based on the prediction of spatio-temporal dynamics of mobile users. The conceived architecture exploits a Software-Defined Networking approach to monitor users’ mobility, a Convolutional Long Short-Term Memory to predict over different look-ahead horizons the number of users within a given number of cells and their related service demands, and Dynamic Programming to optimally allocate users’ requests among available Multi-access Edge Computing servers. Computer simulations investigate the effectiveness of the proposed approach in a realistic autonomous driving use case and compare its behavior against a baseline solution. Obtained results demonstrate its unique ability to dynamically and fairly distribute users’ requests among the resources available at the network edge, while ensuring the targeted quality of service level.

Thanks to the recent advancements in the Software-Defined Networking (SDN) and Network Function Virtualization research domains, telecom operators are encouraged to upgrade their optical transport networks towards programmable, energy-efficient, service-oriented, and interoperable architectures. The availability of a large set of open-source building blocks, supported by different standardization bodies makes the selection and the integration of such technologies a very complex task. In this context, the INTENTO project has the objective to create an innovative simulation framework by selecting the best technologies and use it to test applications, services, and advanced optimization algorithms in a real environment. In the initial phase, the project designed a large-scale, distributed, and hierarchical Transport SDN architecture, where optical switches and networking functionalities are monitored and dynamically configured through a two-level structure of SDN controllers. On top of that, Virtual Network Functions are optimally deployed and managed by a centralized orchestrator, based on network condition, user requests, and application requirements. Based on this architecture, the project team started to develop a complex simulation environment that harmoniously integrates within the OpenStack cloud: optical node simulators composed by simulation agent and a suitable hardware emulation layer; proprietary SDN network controller designed to enable the innovative optical nodes characteristics; Open Network Operating System as the second level controller, enabling the integration of third-party or standardized models (multivendor environment), based on standardized interfaces and communication protocols. After having described the main components and functionalities already implemented into the simulation framework, the paper concludes by highlighting future research and development activities.

The new generation of digital services are natively conceived as an ordered set of Virtual Network Functions, deployed across boundaries and organizations. In this context, security threats, variable network conditions, computational and memory capabilities and software vulnerabilities may significantly weaken the whole service chain, thus making very difficult to combat the newest kinds of attacks. It is thus extremely important to conceive a flexible (and standard-compliant) framework able to attest the trustworthiness and the reliability of each single function of a Service Function Chain. At the time of this writing, and to the best of authors knowledge, the scientific literature addressed all of these problems almost separately. To bridge this gap, this paper proposes a novel methodology, properly tailored within the ETSI-NFV framework. From one side, Software-Defined Controllers continuously monitor the properties and the performance indicators taken from networking domains of each single Virtual Network Function available in the architecture. From another side, a high-level orchestrator combines, on demand, the suitable Virtual Network Functions into a Service Function Chain, based on the user requests, targeted security requirements, and measured reliability levels. The paper concludes by further explaining the functionalities of the proposed architecture through a use case.

The Fifth Generation of mobile networks is emerging as a key enabler for Ultra Reliable and Low Latency Communications. However, to effectively design and provide safety-critical applications through mobile systems, many research issues still need to be deeply investigated. The most important ones include: (1) the dynamic and flexible management of radio resources of a new Radio Access Network jointly used by many virtual mobile operators, (2) the optimized and realtime configuration of network slices, and (3) the harmonious integration of Multi-access Edge Computing services. Starting from the efficient methodologies and solutions available in the current state of the art, this position paper sheds some important basis for the design of a comprehensive architecture enabling Radio Access Network slicing for Ultra Reliable and Low Latency Communications, including design criteria, system components and their baseline interactions, and critical open issues to be investigated in future research initiatives.

The latest advances in mobile devices and the widespread diffusion of networked objects are driving the evolution of traditional Mobile Cloud Computing (MCC) systems toward a new framework where storage, computing, sensing, and other device capabilities are offered as a service at the network edge. This visionary scenario, encompassing heterogeneous resources generated, shared, and consumed everywhere in the network, requires innovative architectural and protocol design. In this context, can the approaches recently formulated in the Future Internet research arena (e.g., middleware-based virtualization, Information Centric Networking, and Software-Defined Networking/Network Function Virtualization) support the evolution of mobile cloud systems? This paper provides an affirmative answer by proposing Future-MCC, a novel architecture that capitalizes on such promising approaches and re-thinks (when needed) their philosophy to better fit the evolution of MCC systems. The performance of Future-MCC has been investigated in a representative heterogeneous and dynamic Smart City scenario. Computer simulation results clearly demonstrate that the proposed solution ensures (i) a reduction of the bandwidth requirements spanning from 66 to 91 percent and (ii) an average energy saving equal to 99 percent with respect to a conventional cloud computing platform.

Time Slotted Channel Hopping (TSCH) is a recent enhancement of the IEEE 802.15.4 standard aimed at the industrial sector. To complement its unique features, the IPv6 over the TSCH mode of IEEE 802.15.4e (6tisch) Working Group released a set of specifications that define the way Time Slotted Channel Hopping could be integrated in embedded IPv6 networks based on the IPv6 over Low Power WPAN. TheI 6tisch standard is now available under several hardware/software platforms so that a cross-comparison of the different implementations deserves particular attention in order to properly identify performance bottlenecks and scavenge pros and cons of the 6tisch technology. The present contribution provides an experimental cross-comparison of protocol stack implementations running on top of different devices. In particular, experimental tests were conducted to characterize the behavior of OpenWSN and Contiki in Time Slotted Channel Hopping- based scenarios made up by TelosB, Zolertia Z1, and OpenMote motes. By considering star and chain topologies and different traffic load conditions, many performance indices were measured, including memory footprint, energy consumption, synchronization time, duty- cycle, end-to-end packet delays, and Packet Loss Ratio. Obtained results highlight strengths and weaknesses of each hardware/software platform, while providing trade-off considerations about flexibility, accuracy, energy-efficiency, and Quality of Service.

NarrowBand Internet of Things (NB-IoT) is a novel radio interface proposed by the Third Generation Partnership Project for addressing the challenging requirements of Machine-Type Communications through a mobile network architecture. Although it natively promises an impressive battery lifetime to constrained devices, advanced methodologies that further reduce energy consumptions are still required. To this aim, this work investigates an extended NB-IoT architecture, embracing the cooperative relaying paradigm. It formulates an optimal relay selection algorithm that minimizes the overall amount of energy consumed in a NB-IoT cell. In addition, it proposes a greedy algorithm able to reach the same goal with a lower computational complexity. System level simulations clearly demonstrate that the adoption of the proposed cooperative relaying paradigm brings to an energy saving up to 30%. Moreover, the greedy approach registers energy consumptions which are only 10% higher than the optimal strategy.

Uncoordinated deployment of HeNBs has been widely considered, in the research community. However, due to economic or physical constraints, a coordinated deployment of HeNBs can also be considered. This work studies a selected examples of HeNB deployment. We consider the deployment of four Enterprise HeNB which serve up to 8 simultaneous users, in a building, with a geometry of 5x5 apartments. From the theoretical study on the average SINR, we have learned that the smaller the apartment areas are the higher the values for the average SINR are. The performance evolution of the system focuses on the values obtained for the average goodput, Packet Loss Ratio (PLR) and delay for the Proportional Fair, Frame Level Scheduler (FLS) and Exponential Rule (EXPRule) schedulers, with users using a video and a best effort flows at the same time. For the video flows the maximum average goodput was obtained with the FLS scheduler, but when the PLR is taken into account the EXPRule present a slight advantage. In the case of the BE flows, the EXPRule present the best performance. But the main lesson learned is that it is possible to operate a coordinated HeNB deployments without setting the transmitter power of the HeNBs to the maximum value, which can be a step to achieve a greener system.

The unsupervised and chaotic deployment of Home eNBs (HeNBs) is leading to high levels of interference. To understand the behaviour of the interference of these uncoordinated deployments is vital to reach significant capacity improvement and also to explore opportunities to save energy. This paper considers high and middle interference level scenarios, with a maximum of four users per cell. HeNBs indoor deployed is considered within building. We theoretically analyse the traffic performance of this scenario through the study of the Signal-to-Interference-plus-Noise-Ratio (SINR). Through the use of the LTE-Sim simulator one obtains the quality indicators for two flows that are being utilised by the users. Video and best effort are studied, while varying the transmitter power and the areas of the apartments. The achieved SINR is higher (around 10 dBm) when the area of the cells is smaller. The variation of the transmitter power of the HeNBs does not present any significant impact. Noticeable throughout the simulations is observed that is possible to operate the system without setting the transmitter power of HeNBs to the maximum value at both interference levels. Simulation results also show that with the considered flows is possible to serve the maximum number of four users per HeNB with high quality. This statement is confirmed by the maximum achieved Packet Loss Ratio for video with a value of value of 1.6 %, which is lower than the maximum of 2 % indicated by the 3GPP. Taking into account the obtained results it is possible to promote a reduction in energy consumption of the HeNBs without penalizing the service quality.

While enabling brand new services and opportunities, the federation of vertical Internet of Things platforms presents new challenges in terms of secure and controlled access to heterogeneous resources, especially when authorization permissions must be regulated by multiple decentralized authorities. The work presented herein designs, develops, and experimentally validates a flexible and effective attribute-based access control framework, properly devised to operate in a federated and cloud-assisted cyber-physical system (CPS). Our main novelty stems in the original way we turn a policy-based encryption scheme, customarily used for accessing data, into a cyber-physical resource access control protocol. The proposed design approach is able to address several security issues characterizing the emerging use cases in this context, including the decoupling between authentication and authorization, fine-grained, offline, and time-limited authorization, protection against collusion attacks, access rights revocation, and user privacy. A security analysis and a performance evaluation executed through experimental tests clearly demonstrate the viability of the proposed approach in realistic cloud-assisted CPSs, as well as its ability to overcome the lacks affecting competitive approaches without introducing huge communication and computational requirements.

This paper focuses on Long Range Wide Area Networks (LoRaWAN) and sheds some light on the feasibility of fully cable-less Internet of Things deployments, where dual-radio gateways are fed by a photovoltaic plant and equipped with a wireless backhaul. As a first step, the power needs of a dual-radio gateway, serving a mix of realistic machine-to-machine applications and leveraging different combinations of front-end chipsets and backhaul wireless technologies, are investigated. Then, the achieved results are properly employed to size the PV plant, as well as to estimate its installation costs and land acquisition. Finally, cost-saving and carbon footprints analysis is presented to demonstrate the socio-economic benefits arising out of these cable-less deployments for LoRaWANs. The conducted study clearly exhibits that network operators can achieve their break-even point during the early stages after the deployment, while adopting environment-friendly approaches because of carbon emission savings achieved by renewable energy.

Internet of Things (IoT) is widely recognized as a key enabling driver in environmental monitoring systems, thanks to its inherent capabilities to provide sensing and actuation functionalities on a distributed basis. At the same time, the majority of IoT applications are Information Centric by design: they target specific actions that are not related to any network node but can be provided by multiple resources within the system. In this perspective, the Information-Centric Networking (ICN) paradigm, formulated to answer to Future Internet requirements, can natively and seamlessly support IoT technologies as a service bus. Moving to IoT-enabled environmental monitoring systems, the publish-subscribe data exchange model is the pivotal functionality that ICN architectures have to support. In fact, an environmental monitoring system can be easily set up by letting one or more collecting stations to subscribe to the events or sensed values, generated (i.e., published) by IoT nodes scattered in the scenario of interest. Unfortunately, the support for publish-subscribe functionalities is not uniform across the main ICN architectures designed so far. To shed some light on this issue, the present contribution analyzes to what extent ICN architectures are able to support publish-subscribe and highlights the missing building blocks to purse this objective.

While the Internet of Things is breaking into the market, the controlled access to constrained resources still remains a blocking concern. Unfortunately, conventional solutions already accepted for both web and cloud applications cannot be directly used in this context. In fact, they generally require high computational and bandwidth capabilities (that are impossible to reach with constrained devices) and offer poor interoperability against standardized communication protocols for the Internet of Things. To solve this issue, this contribution presents a flexible authentication and authorization framework for the Internet of Things, namely OAuth-IoT. It leverages and properly harmonizes existing open-standards (including the OAuth 2.0 authorization framework, different token formats, and the protocol suite for the Internet of Things tailored by the Internet Engineering Task Force), while carefully taking into account the limited capabilities of constrained devices. Functionalities and benefits offered by OAuth-IoT are pragmatically shown by means of an experimental testbed, and further demonstrated with a very preliminary performance assessment.

With reference to the IEEE 802.15.4 standard, many solutions have been formulated to face the different facets of layer-2 security. Unfortunately, the opportunities and subtleties arising from their joint adoption has been not investigated, due to the lack of an integrating framework. To this end, hereby a novel standard compatible framework is proposed, which is able to orchestrate several layer-2 security mechanisms with a limited computational footprint. Conceived as a distributed scheme, it covers the following key features: (i) multiple security configurations in homogeneous and heterogeneous scenarios; (ii) adaption to dynamic networks; (iii) lean and scalable initialization functionalities; (iv) lightweight Key Management Protocol; and (v) resilience to several attacks. The robustness against security attacks have been evaluated through a well-known automatic cryptographic protocol verifier, namely ProVerif. Moreover, to further demonstrate its effectiveness, the proposed framework has been implemented within the emerging OpenWSN protocol stack, experimentally evaluated, and compared with respect to the ZigBee IP security architecture, which integrates the Symmetric Key - Key Establishment protocol (SKKE). Results clearly show that, although security features in constrained nodes incur not negligible computational costs (which impair latencies and energy efficiency), the proposed approach always guarantees better performances with respect to the ZigBee IP security architecture. In fact, it speeds up the configuration of security services (up to 120%), while ensuring relevant energy savings (larger than 50%).

Carrier Aggregation (CA) has been proposed by 3GPP LTE-Advanced to meet or even exceed IMT-Advanced systems enhanced peak data rates requirements. In its rationale, multiple Component Carriers (CC) can be flexibly aggregated so that user equipment can access a total bandwidth of up to 100 MHz. As each CC has the same structure as the one from LTE R8, CA does not require notable changes in the LTE physical layer structure. Nevertheless, the way radio resources are allocated to mobile users in CA scenarios is still an hot research topic and the availability of an open source tool modelling such kind of feature is highly demanded in both academia and industry contexts. The present contribution is three-folded. First, it presents an open source and freeware extension of the well-known LTE-Sim simulator, which implements CA functionalities. Second, it also proposes an implementation of multi-band scheduling strategies able to optimally distribute radio resource among mobile users in the presence of multiple CCs and strict Quality of Service (QoS) constraints. Third, computer simulations have been also carried out to demonstrate the effectiveness of the aforementioned contributions. In particular, simulation results show the capacity improvements achieved by the proposed Enhanced Multi Scheduler against systems without CA, considering values of the bandwidth per component carrier of 5 and 20 MHz, in terms of average cell packet loss, delay, goodput and spectral efficiency.

Recent studies have shown that in LTE Uplink, the handshake procedure consisting of a scheduling request message from the User Equipment and a scheduling grant from the eNB required twice a communication over the air interface and caused notable delay. It could be harmful for loss and latency-sensitive applications such as Videotelephony traffics. So, we propose in this paper a new scheme which improves resource allocation for Videotelephony traffics and reduce the delay caused by Dynamic scheduling. The key idea is to schedule Videotelephony traffics using a Semi-Persistent strategy with Provisioning. The performance of our proposed algorithm have been evaluated in real LTE environments with LTE-Sim and simulations results demonstrated its effectiveness by showing that it optimized Videotelephony traffics performance and provided the best QoS support compared to the Dynamic Scheduling.

Long-term evolution represents an emerging technology that promises a broadband and ubiquitous Internet access. But several aspects have to be considered for providing effective multimedia services to mobile users. In particular, in this work, we consider the design of a quality-of-service (QoS) aware packet scheduler for real-time downlink communications. To this aim, a novel two-level scheduling algorithm is conceived. The upper level exploits an innovative approach based on discrete-time linear control theory. Instead, at the lower level, a proportional fair scheduler has been properly tailored to our purposes. The performance and the complexity of the proposed scheme have been evaluated both theoretically and by using simulations. A comparison with recently proposed scheduling strategies has been also presented, considering several network conditions and real-time multimedia flows. Particular attention has been devoted to the evaluation of the quality-of-experience (QoE) provided to end users. Results have clearly shown that the proposed approach is able to greatly outperform the existing ones especially in the presence of real-time video flows.