This paper investigates a depth-layered acoustic Underwater Wireless Sensor Network (UWSN) architecture, to be used for environment monitoring. The underwater scenario is populated by sensor nodes and is partitioned into several horizontal layers. For each layer, we analytically determine the optimal number of sensor nodes required to ensure sensing coverage, while maintaining long-term energy sustainability. To address the severe energy constraints inherent to underwater environments, a mobile charger (MC) is introduced to periodically replenish node energy. The MC’s trajectory, charging locations, and charging durations are jointly optimized to maximize the harvested energy and minimize network outage probability. A comprehensive underwater acoustic communication model and a detailed node energy consumption model are developed to capture the unique characteristics of underwater propagation. Based on these models, outage probability (OP) is analytically derived, and the overall system design is formulated as a mixed-integer optimization problem. Simulation results demonstrate that the proposed depth-layered design and MC optimization significantly improve energy balance, reduce OP, and extend network lifetime, as compared to a non-optimized deployment and charging strategies.

Underwater wireless optical communication (UWOC) enables high-speed, low-latency links for the Internet of Underwater Things (IoUT), but remains highly vulnerable to complex and dynamic channel impairments. In practice, slant transmission paths frequently occur due to spatial offsets between underwater sensors and marine surface vehicles (MSVs), where link quality is jointly affected by MSV-induced misalignment, depth-dependent attenuation, and oceanic turbulence. Most existing models address these factors independently or under static assumptions, limiting their applicability. To address this challenge, this paper proposes a novel modeling and simulation framework that jointly captures the coupled effects of dynamic posture, stratified absorption and scattering, and spatially varying turbulence along slant UWOC paths. A parallelized wave optics simulation (WOS) platform is developed using Argo float data to reflect realistic ocean conditions. Leveraging this dataset, a CNN-based Fast Channel Simulation Method (CNN-FCSM) is designed, achieving over 98% prediction accuracy of received optical intensity, while reducing runtime by more than 90% compared to WOS. Comprehensive evaluations demonstrate that the proposed approach enables accurate and scalable estimation of average bit error rate (ABER) and outage probability (OP) without relying on predefined statistical fading models, offering a robust tool for dynamic UWOC analysis and IoUT system design in complex underwater environments.

In Internet of Underwater Things (IoUT) scenarios, power-hungry devices need to periodically harvest energy to be alive. By dynamically controlling and redirecting the optical beam, reconfigurable intelligent surfaces (RIS) can enhance both the energy transfer and information reception processes, thereby improving the sustainability of low-power underwater devices. Simultaneous wireless information and power transfer (SWIPT) systems allows to harvest energy and receive data from the transmitted optical beam, thus feeding the low-power receiver (Rx) while downloading data. However, realistic underwater scenario can strongly affect the performance of such systems. This paper investigates the performance of ORIS-assisted SWIPT system under a realistic unified channel model for underwater optical wireless communications (OWC), considering both coherent and non-coherent detection schemes. Considering multiple attenuation losses, underwater turbulence, pointing error, and angle of arrival deviation, we derive the joint outage probability of an ORIS-aided SWIPT OWC system for different transmission protocols based on different resources that are allocated. Three approaches are investigatedi.e., (i)power-splitting (PS),(ii)time-switching (TS), and(iii)element-splitting (ES). While PS and TS are based on all-passive RIS elements, ES considers hybrid (active and passive) elements. Simulation results show enhanced performance obtained with ES approach for low signal-to-noise ratio (SNR), while PS outperforms ES for high SNR.

This paper presents a novel transmission protocol for simultaneous transmission and reflection reconfigurable intelligent surface (STAR-RIS) that jointly exploits traditional time switching and mode splitting protocol. The proposed approach, namely time-switching-variable mode splitting (TVM), allows to dynamically allocate STAR-RIS resources (i.e., time slot duration, and number of reflecting and transmitting elements) based on variable environment conditions. Energy harvesting (EH) and information transfer (IT) phases alternate to each other in downlink according to a variable time frame structure, while the energy harvested in downlink is exploited for IT in uplink. The elements of the STAR-RIS are then dynamically switched from transmission to reflection in different time slots based on the demand of the network, allowing the transmission users (TUs) and the reflection users (RUs) to be connected to the base station (BS) simultaneously. The proposed approach is investigated under the hypothesis of a non-orthogonal multiple access (NOMA) network, and the Nakagami-mdistributed channel model with attenuation loss. The analytical performance metrics are obtained considering dynamic time slots and link duration for both IT and EH downlink phases, as well as a variable number of transmission and reflection elements for each time slot. The assessment of the proposed TVM protocol is carried out by means of numerical and Monte Carlo (MC) simulation results of the joint outage probability, the sum throughput, and the age of information in case of multiple reflecting and transmitting users.

Hybrid radio frequency (RF)/visible light communications (VLC) indoor systems are largely deployed to guarantee high-capacity and seamless connectivity, thanks to the exploitation of benefits coming from both two technologies. Recently, the use of Reconfigurable Intelligent Surfaces (RIS) in VLC systems has provided enhanced network performance thanks to their ability of reflecting the impinging optical intensity to a desired destination, in order to avoid any blockages that may occur in Line of Sight (LoS) links. Taking into account the advantages of RIS deployment in VLC systems, in this paper we present a RIS-aided multi-user communication technique based on a fair RIS partitioning allocation policy (namely, RPMU). The proposed approach is applied in a hybrid RF/VLC indoor system, where asymmetric connectivity links are provided by means of RF uplink and VLC/RIS-aided downlinks. We also present a MAC protocol to support multi-user asymmetric RF/VLC and RIS-aided communications, and investigate packet collision events occurring in the RF uplink. Derivations of the achievable downlink throughput are provided, and the assessment of the proposed RPMU approach is carried out through numerical results showing the achievement of high data rates especially for higher number of RIS elements.

The rapid development of 5G and the upcoming transition to Beyond 5G and 6G networks are accelerating the emergence of the interactive metaverse. Digital twin (DT) is a cornerstone of the interactive metaverse, facilitating real-time dynamic interactions. Task-offloading to edge servers enables metaverse applications to mitigate the resource limitations of mobile devices. Most current research prioritizes latency and energy efficiency over security in offloading systems, neglecting the trustworthiness of offloading actors, necessitating improved security measures. This paper investigates a trustworthy computation offloading system for the DT-empowered interactive metaverse. We propose a DT-assisted task-offloading architecture and a DRL-based solution to optimize task-offloading decisions. Digital twins collect and update real-time data providing the DRL agent with up-to-date view of the system's status. This agent uses the data to make informed task-offloading decisions, enhancing efficiency and decision-making. A bidirectional blockchain-based trust management mechanism ensures secure interactions between mobile devices and edge servers, which is crucial for effective task-offloading and resource management. The performance evaluation of the DRL-based trustworthy offloading system demonstrates its efficient ability to facilitate real-time, reliable offloading decisions.

Apart the well-known benefits of Visible Light Commmunications (VLC), some drawbacks still limit its realworld deployment and market penetration, such as the need of link alignment, shadowing, and blockage. Radio Frequency (RF) technology is traditionally adopted to alleviate such limitations, acting as uplink support in asymmetric RF/VLC systems. Specifically, the downlink is established using VLC direct links, while a RF link is deployed to guarantee uplink data and control transmissions. In this paper, we investigate a Medium Access Control (MAC) protocol for a hybrid asymmetric RFVLC indoor system, enhanced by a Reconfigurable Intelligent Surface (RIS) device, which is able to redirect the impinging wireless signal to the desired destination thus solving any VLC blockage occurrence. We evaluate the impact of the proposed MAC protocol in which packets can collide among them within an RF transmission link, and we derive the expressions for the RF, VLC direct, and RIS-aided VLC throughput when a blockage occurs.

This article presents a novel technique for the simultaneous wireless information and power transfer (SWIPT) toward low-power devices, by means of reconfigurable intelligent surfaces (RISs). Our approach is based on a Reflect-and-Amplify protocol meaning that, based on the RIS beam-steering functionality and assuming different reflection coefficients for the RIS elements, it allows to reflect and amplify the impinging wireless signal from the transmitter toward the receiver, which will be able to both collect energy and download data. Specifically, by considering a hybrid RIS comprised of both passive and active elements, the proposed SWIPT approach is defined active/passive switching (APS). The reflection of the wireless beam toward the receiver is accomplished by means of passive RIS elements, while an amplification of the wireless signal is provided through active RIS elements. Such amplification allows the receiver to convert the incoming wave power into a DC voltage, but also causes an increase of power consumption due to active elements. To assess the performance of the proposed SWIPT approach, we derive the closed-form expression of the joint data transmission and energy harvesting outage probability (OP) in case of both a single and multiple users. We compare the proposed technique to other SWIPT approaches from the literature, such as the power splitting and the time switching, under power fairness conditions. Our results validate the benefits of using hybrid RISs for SWIPT systems, as compared to other existing approaches showing reduced performance, also in case of asymptotic analysis for high power and high number of RIS elements.

In underwater environment, wireless signal propagation is very challenging, and strongly affected by absorption- and scattering-induced attenuation losses. Optical wireless communications (OWC), due to huge bandwidths, can provide high data rates and medium propagation ranges, representing a viable technology for underwater scenarios. There are several statistical distributions that model the effect of underwater turbulence on OWC, and how to model the underwater OWC (UOWC) channel with higher accuracy is still a topic to investigate. In this paper, we investigate the use of intelligent reflecting surfaces (IRSs) for enhancing performance in underwater OWC systems. In this regard, we present a unified channel model for UOWC, working both for heterodyne and intensity modulated/direct detection (IM/DD) schemes. The analytical expressions of average bit-error-rate (BER), outage probability, and channel capacity are derived including the combined effect of (i) attenuation, (ii) turbulence, (iii) pointing error, and (iv) angle-of-arrival (AOA) fluctuations to ensure the comprehensive characterization of underwater optical wireless communication channel. To make the analysis and results more realistic, the practical scenarios and parameters are considered. The probability density function (PDF) and the cumulative distribution function (CDF) of the underwater OWC channel are obtained analytically. Simulation results are presented for various parameters of underwater channel and communication systems. It is observed that the application of IRS remains as an important tool in terms of mitigating the overall fading effect caused by the combination of previous phenomena in underwater wireless channel. Also, the benefits of heterodyne detection over IM/DD is evinced.

The convergence of Web 3.0 and Metaverse technologies with Connected Autonomous Vehicles (CAVs) is catalyzing a new era of intelligent vehicular systems, characterized by decentralization, immersive interaction, and enhanced autonomy. This paradigm is especially valuable in scenarios demanding secure peer-to-peer coordination, trustless automations, and seamless integration of physical and virtual environments under real-time constraints. Nonetheless, realizing such intelligent applications introduces critical challenges, including the development of robust decentralized governance and smart contracts, ensuring ultra-low-latency and high-throughput communications in edge computing contexts, achieving seamless digital–physical synchronization via high-fidelity digital twins or Metaverse representations, and guaranteeing scalability and privacy across distributed vehicle networks. This special issue brings together a collection of pioneering research that tackles these multifaceted challenges, showcasing innovations that advance the state of the art toward more secure, responsive, immersive, and decentralized CAV systems empowered by Web 3.0 and Metaverse technologies.

In this paper, we consider an indoor visible light communication (VLC) system with multiple "white" light emitting diodes serving to form overlapping wireless communication cells. In order to maintain seamless connectivity to mobile users, a handover procedure should be implemented. In particular, practical conditions such as blockages due to obstacles inside the room environment and the mobility of users can affect direct VLC connectivity. The use of reconfigurable intelligent surfaces (RISs) in optical wireless systems allows to exploit non-direct connectivity links, thus providing efficient communication links. In this paper, we present a proactive handover mechanism that exploits the presence of a RIS, in order to redirect the communication links in case of blockages. The proposed approach has been implemented both in hard and soft modes and assessed in terms of achievable data rate and handover latency for a user walking in a given reference room at different user speeds and blockage conditions. Our presented results and comparisons with conventional handover methods (i.e., without RIS) are helpful in showing the superiority of the presented algorithm.

In the context of 6G next generation networks, the Internet of vehicles (IoV) paradigm will be supported by overlapping network layers, like the aerial and space ones, to guarantee enhanced performance and 3D connectivity. Specifically, the integration of aerial devices, such as unmanned aerial vehicles (UAVs), into IoV is expected to enhance network performance, especially for vehicular safety applications, where packet delivery requires low latency and reduced connectivity loss, as compared to existing communication modes. In this paper, the technique ALI, an aggregate LiDAR images-based approach for road safety applications in a 6G context is introduced. It considers multiple LiDAR images that are shared and collected among vehicles to improve the accuracy in vulnerable road users detection. As compared to a single LiDAR image, ALI approach shows an enhanced detection accuracy, as well as allows alert message forwarding to other approaching vehicles in case of obstacle detection, via multiple interface cards and transmission modes. Results show that the adoption of UAVs as communication nodes allows to extend the coverage between 80 m and 130 m for an outage probability of 1%, overcoming vehicle-to-vehicle and vehicle-to-network communication modes and to provide a communication latency lower than 30 ms achieved up to 150 m.

This paper investigates the role of reconfigurable intelligent surface (RIS) for enhanced handover management in 6G networks with overlapping wireless network layers i.e., ground, aerial, and space. A high altitude platform system (HAPS) is equipped with RIS and the comparison of direct and RIS-assisted link performance is presented. To do this, the average bit error rate, the outage probability (OP), and the channel capacity of direct and HAPS-assisted links are obtained in closed form expressions. By estimating the link error probability, a novel handover mechanism exploits the use of RIS, resulting in enhanced connectivity management. Hard and soft handover modes are defined depending on the radio frequency (RF) connectivity by means of link error threshold. The decision for the handover execution is based on selecting the optimal link among multiple available ones from ground, aerial, and space layers. The performance of RIS-assisted handover mechanism has been compared to traditional hard and soft handover procedure, as well as link performance achieved with relay node. Numerical and simulation results reveal that the connectivity of a user equipment can be maintained through RIS-aided links in case of any performance degradation in the direct RF links. Particular scenarios highlight that the use of RIS for handover is preferred to traditional handover procedures, as well as relay nodes.

To limit the spread of COVID-19, social distancing measurements and contact tracing have become popular strategies implemented worldwide. In addition to manual contact tracing, smartphone-based applications based on proximity detection have emerged to speed up the discovery of potential infectious individuals. However, so far, their effectiveness has been limited, mainly due to privacy issues. A new tracing mechanism is represented by Online Social Networks (OSNs), which provide a successful way to track, share and exchange information in real-time. Being extremely popular and largely used by citizens, OSNs are less exposed to privacy concerns. In this paper, we present an OSN-based contact tracing platform called TraceMe to reduce the spread of the epidemic. The proposal currently targets COVID-19, but it can be used in presence of other infectious diseases, like Ebola, swine flue, etc. TraceMe implements conventional contact tracing based on physical proximity and, in addition, it leverages OSNs to identify other contacts potentially exposed to the virus. To efficiently find the targeted social community, while saving the time complexity, a clique-based method is applied. Performance evaluation based on a realistic dataset shows that TraceMe is able to analyse large-scale social networks in order to find, and then alert, the tight communities of contacts that are at high risk of infection.

The use of Optical Wireless Communications is largely adopted in both indoor and outdoor applications. Recently, it is also extending to underwater scenarios, as an alternative technology to the acoustic one, which is traditionally adopted. Knowing more precisely the position of artifacts, technical/scientific instruments and operators in the marine environment increases the operational potential and consequently, the interest in the progress of knowledge is guaranteed. Furthermore, the possibility of operating in both shallow and deep waters and the opportunity to be a new underwater navigation system increases the possibility of success of underwater activities, in the context of the Internet of Underwater Things (IoUT). This paper introduces an underwater all-optical IoT network architecture for both communication and positioning tasks. We initially discuss the main issues for data transmission via underwater visible light communications, and present an IoUT schematic based on Light Emitting Diode (LED) devices accordingly deployed on the seabed and illuminating a given space of interest. Then, a simple but accurate fingerprinting-based localization approach is presented, able to estimate the position of an object moving within the space of interest (e.g., a diver or an Autonomous Underwater Vehicle). The positioning error is auto-adjusted in case of variable channel coefficients, mainly due to changes in water turbidity space distribution. The achieved results have been assessed in case of two different paths, where variable distances from the positioning/communication LEDs are assumed.

The Internet of Drones represents an emerging framework with a plethora of applications in the context of Beyond-5G networks. Drone technology uses are spreading from commercial, industrial up to military applications. Drones, a.k.a. Unmanned Aerial Vehicles (UAVs), are largely adopted in all those fields where men cannot reach or are unable to perform in a timely and efficient manner. Communications among UAVs are important to allow task coordination and network organization. However, as a drawback, UAVs are strongly affected by energy consumption that limits their flight and task accomplishment. In this paper, we address the energy consumption issue in UAV swarms and present a novel routing approach, namely ENSING, that aims to save energy consumption. Differently from previous approaches that simply reduce the number of control packets to save UAV battery level, ENSING approach selects the next-hop UAV forwarder according to energy constraints. In this way, only eligible UAVs with acceptable energy requirements can be selected in the packet forwarding, thus avoiding the involvement of those UAVs with limited battery level. Compared to other routing techniques, ENSING exhibits better performance in terms of packet delivery rate, throughput and latency.

The Internet of Vehicles (IoV) can deliver services for intelligent transportation systems. However, it typically relies on the exchange of sensitive information, including passwords and personal data, which makes it vulnerable to many security risks, such as phishing attacks, which have largely increased in the last decade. Cryptography-based security measures look as a form of protection to preserve sensitive information, but they can be bypassed by inside attackers and, in addition, they increase the burden on the network. To tackle the aforementioned issues, in this paper, we present an approach to control phishing attacks in the IoV environment, based on Machine Learning (ML) and Deep Learning (DL) techniques.

With the outbreak of COVID-19, and its terrible and fast spread among communities, contact tracing methods have become crucial to protect people. However, conventional mechanisms, for instance based on the manual search of close contacts, lack of high efficiency due to the high time consumption. The research community is therefore exploring new ways to track contagious diseases by exploiting modern communications paradigms and technologies. In this paper, we propose a new contact tracing method based on Online Social Network (OSN) platforms. In our design, contact detection occurs in real-time by means of traditional proximity approaches. Then, a likely future contact forecast is notified through OSN communities.

Handover management in Visible Light Communications (VLC) networks is an open issue due to the need of maintaining alignment between a transmitting Light Emitting Diode (LED) and a receiver PhotoDetector (PD). Mobility strongly affects VLC connectivity links, as well as occlusions that may obstruct the Line-of-Sight (LoS) propagation. In this paper we present a proactive handover solution, which is able to switch connectivity links from a serving VLC “lighting” cell to a candidate one, in case of blockage that affects the VLC link. Differently from conventional handover mechanisms, where a handover is trigged by quality of service metrics or localization information, our technique is dedicated to VLC networks which can be affected by occlusions causing blockages. The proposed approach has been implemented both in hard and soft mode, and assessed in terms of achievable data rate and hand over latency for a user walking in a given reference room at different speeds.

Recently, pushed by the COVID-19 pandemic, the need of respecting social distancing has motivated several researchers to define novel technological solutions to monitor and track user movements. Information and Communications Technologies (ICT) world has addressed this challenge by means of the use of different technologies, such as Bluetooth, in order to track user interdistance and encounter time. Technology solutions should be able to not only track contacts, but also alert users to restore social distancing. In this article, we present IMPERSONAL framework, with the twofold aim of both: 1) tracking and monitoring social distancing and 2) alerting users in case of gatherings. The framework is based on a subnetwork of computer vision-based devices that are adopted to monitor and track users’ movements to estimate their interdistance and compute the encounter time. Such information is then the input to an Internet of Things subnetwork, aiming to retrieve the anonymous IDs of people belonging to a gathering, as well as to send alert messages to them. We assess IMPERSONAL framework by means of extensive Monte Carlo simulations and experimental results, showing its effectiveness in terms of accuracy in correctly identifying users and gatherings in videos taken from live cameras, both in case of indoor and outdoor real scenarios. The benefits of the IMPERSONAL framework are expressed in terms of the ability to track people, solve gatherings, and send warning messages.

Reconfigurable Intelligent Meta-surfaces (RIMs) are particular devices able to control and manipulate radio frequency wireless signals. This promising technology allows to improve the reliability of wireless networks, thanks to the capacity of reflecting the desired signals through appropriate phase shifts. The joint use of RIMs and Computer Vision (CV) technology is the main objective of this paper. This synergistic approach is used to correctly identify the specific configuration of a radiation pattern, to be used as input for computing optimal coding sequences of the RIM. Indeed, by the means of a CV algorithm it is possible to infer a connectivity graph related to a real scenario, where people is moving. The information about network nodes such as their distance, the relative position, etc. is used for feeding an intelligent logic, able to compute the optimal configuration for re-directing the signals towards a given receiver target node.Numerical results show the huge potentiality of this combined approach in terms of interference reduction. It has been observed that for high traffic load, it is possible to reduce the average interference in the network of 40%. Furthermore, an analysis including the positioning estimation error of the CV algorithm has been addressed, in order to consider how it affects the interference reduction. Results show that, even though there is an increasing effect of interference, when the error is accounted, the interference reduction impact is still important.

Vehicular Social Networks (VSNs) consist of groups of individuals (i.e., people) who may share common interests, preferences and needs in the context of temporal spatial proximity on roads. In this environment, the impact of human social factors, such as mobility, willingness to cooperate and personal preferences, on vehicular connectivity is taken under consideration, thus extending the concept of Vehicular Ad-hoc Networks. In VSNs, vehicles are classified based on their social degree, a vehicle considered to be a “social” one if it accesses the vehicular social network and posts messages with a frequency higher than a given threshold. Therefore, to speed up the data dissemination process within a vehicular social network, a packet should be forwarded to those vehicles showing high social activity. In a previous paper, we introduced a new probabilistic-based broadcasting scheme called SCARF (SoCial-Aware Reliable Forwarding Technique for Vehicular Communications), and we analytically demonstrated its effectiveness in packet transmission reduction while guaranteeing network dissemination. In this paper, we assess SCARF in more realistic scenarios with real traffic traces, and we compare it with other similar techniques. We show that SCARF outperforms other approaches in terms of delivery ratio, while guaranteeing acceptable time delay values and average number of forwardings.

In this work, we demonstrate that Vehicular Social Networks (VSNs) require specific data dissemination techniques. To this aim, we consider the Barabási model and we study the impact of its use for data dissemination in VSNs. Moreover, the use of a probabilistic data dissemination protocol based on social features [1] proves that the time-evolving dynamics of the vehicular social network graph presents a small-world structure, where nodes tend to connect through clusters whose average distance is low on average. This result highlights how VSNs are a specific class of vehicular ad hoc networks with peculiar features that distinguish them from classical online social networks.

The Internet of Vehicles (IoV) has emerged as a new spin-off research theme from traditional vehicular ad hoc networks. It employs vehicular nodes connected to other smart objects equipped with a powerful multisensor platform, communication technologies, and IP-based connectivity to the Internet, thereby creating a possible social network called Social IoV (SIoV). Ensuring the required trustiness among communicating entities is an important task in such heterogeneous networks, especially for safety-related applications. Thus, in addition to securing intervehicle communication, the driver/passengers honesty factor must also be considered, since they could tamper the system in order to provoke unwanted situations. To bridge the gaps between these two paradigms, we envision to connect SIoV and online social networks (OSNs) for the purpose of estimating the drivers and passengers honesty based on their OSN profiles. Furthermore, we compare the current location of the vehicles with their estimated path based on their historical mobility profile. We combine SIoV, path-based and OSN-based trusts to compute the overall trust for different vehicles and their current users. As a result, we propose a trust-aware communication architecture for social IoV (TACASHI). TACASHI offers a trust-aware social in-vehicle and intervehicle communication architecture for SIoV considering also the drivers honesty factor based on OSN. Extensive simulation results evidence the efficiency of our proposal, ensuring high detection ratios >87% and high accuracy with reduced error ratios, clearly outperforming previous proposals, known as RTM and AD-IoV.

Intelligent inter-vehicle communication is a key research field in the context of vehicular networks that applies in real-life applications (e.g., management of accidents, intelligent fuel consumption, smart traffic jams, etc.). Considering different roles of nodes based on their “social aptitude” to relay information could provide a social component in the vehicular structure that can be useful in getting a clear prediction of the topological evolution in time and space proving to be very effective in managing intelligent data forwarding. In this work we characterize a vehicular network as a graph using the link layer connectivity level and we classify nodes on the basis of specific attributes characterizing their “social aptitude” to forward data. Two forwarding approaches are presented, based on different socialites that allow to (i) select the most social node (i.e., a social hub) or (ii) choose among various social nodes.

Recently, Internet-of-Things (IoT) applications have been moving toward a network of intelligent objects with social capabilities, defined as the Social IoT (SIoT). Different types of relationships exist among things, thus forming social connections such as parental-object relationship (POR), co-work-object relationship (CWOR), co-location-object relationship, ownership-object relationship, and so on.

Recent progress in the field of nanotechnology is enabling communication between nanodevices to be considered also for in-vivo applications. In particular, nanodevices enabling light-controlled process have started to attract a lot of interest in the research community, due to potential applications like healthcare wearable devices, intra-body applications, and optogenetics, whose main objective is to stimulate neurons by the means of the light signals. Leveraging on these premises, we consider upconversion phenomenon, namely the ability of specific nanoparticles to convert low energy radiations (e.g., near-infrared radiations) into higher energy radiation (e.g., visible light) via a non-linear process. Energy transfer as viable communication mean has been already considered based on the Förster-Resonance-Energy Transfer. In this paper, we focus on phonon-assisted energy transfer, and we analyze the requirements and conditions for generating optical signals from a genuine signal processing point of view. More specifically, based on information theory approach, we derive the conditions to minimize the error probability. We show that the dopant concentration, (i.e., the concentration of elements drugging a pure material in order to change its features) mostly influences the correct generation of the light signal. The performed analysis is based on experimental results.

The co-deployment of radio frequency (RF) and visible light communication (VLC) technologies has been investigated in indoor environments to enhance network performances and to address specific quality-of-service (QoS) constraints. In this paper, we explore the benefits of employing both technologies when the QoS requirements are imposed as limits on the buffer overflow and delay violation probabilities, which are important metrics in designing low latency wireless networks. Particularly, we consider a multi-mechanism scenario that utilizes RF and VLC links for data transmission in an indoor environment, and then propose a link selection process through which the transmitter sends data over the link that sustains the desired QoS guarantees the most. Considering an ON-OFF data source, we employ the maximum average data arrival rate at the transmitter buffer and the non-asymptotic bounds on data buffering delay as the main performance measures. We formulate the performance measures under the assumption that both links are subject to average and peak power constraints. Furthermore, we investigate the performance levels when either one of the two links is used for data transmission, or when both are used simultaneously. Finally, we show the impacts of different physical layer parameters on the system performance through numerical analysis.

To meet the food demand of the future, farmers are turning to the Internet of Things (IoT) for advanced analytics. In this case, data generated by sensor nodes and collected by farmers on the field provide a wealth of information about soil, seeds, crops, plant diseases, etc. Therefore, the use of high tech farming techniques and IoT technology offer insights on how to optimize and increase yield. However, one major challenge that should be addressed is the huge amount of data generated by the sensing devices, which make the control of sending useless data very important. To face this challenge, we present a Bayesian Inference Approach (BIA), which allows avoiding the transmission of high spatio-temporal correlated data. In this paper, BIA is based on the PEACH project, which aims to predict frost events in peach orchards by means of dense monitoring using low-power wireless mesh networking technology. Belief Propagation algorithm has been chosen for performing an approximate inference on our model in order to reconstruct the missing sensing data. According to different scenarios, BIA is evaluated based on the data collected from real sensors deployed on the peach orchard. The results show that our proposed approach reduces drastically the number of transmitted data and the energy consumption, while maintaining an acceptable level of data prediction accuracy.

Smart city services are enabled by a massive use of Internet of Things (IoT) technologies. The huge amount of sensors, and terminals with a great variety of typologies and applications, requires a secure way to manage them. Capillary networks can be seen as a short range extension of conventional access network in order to efficiently capture the IoT traffic, and are enablers for smart city services. They can include both IP and non-IP devices, and security can become an issue, especially when simple unidirectional communication devices are considered. The main goal of this paper is to analyze security aspects in IoT capillary networks including unidirectional and bidirectional IP or non-IP devices. We propose an algorithm for secure access for uni- and bi-directional devices. The security procedure is based on a secure key renewal (without any exchange in air), considering a local clock time and a time interval of key validity. Following previous work in 2014 by Giuliano et al., in this paper we assess the duration of the validity of the time window, and present extended simulation results in terms of (average) transmission time in a realistic scenario, i.e., including the presence of disturber(s), then providing indications for the setting of the duration of the key validity time window. Finally, we present the benchmark analysis in order to assess the effectiveness of our approach with respect to other existing standards, as well as the security analysis in terms of typical attacks.

This paper investigates a novel communication system architecture for traffic management and data control in railway scenarios. The proposed solution should be integrated in the existing European Railway Traffic Management System/European Train Control System, the most advanced and successful standard even outside the European countries. Our system integrates public land mobile networks that usually offer best-effort packet services, with a quality-of-service (QoS) guaranteed satellite network. It represents a cost-effective substitution for 4G and 5G networks, aiming to replace current well-known GSM-R standard. The coexistence of heterogeneous networks is guaranteed by the multi-path transmission control protocol (TCP) protocol that addresses specific “add and drop” subflow policies and priority handling logics, in order to realize efficient seamless handovers. Providing priority to TCP subflows corresponds to select QoS-guaranteed, and the best effort networks able to fulfill railway requirements. The logic of adding and dropping subflows exploits both a real-time check of the current status of the serving network and “a priori” network performance information. Experimental results have been carried out in both city and harsh environments, where the main performance metrics (i.e., average delay, jitter, and bit rate) have been assessed.

The potentialities of the Terahertz (THz) frequency band in the context of nano-scale communications are increasing, thanks to specific features that allow issues related to the spectrum scarcity and capacity limitation to be overcome. Apart from high molecular absorption and very high reflection loss that represent the main phenomena in THz band, in this paper, we investigate the chirality effects that affect the propagation medium, in the frequency range (4 - 10) THz. It is observed that in this interval, the chiral parameter shows resonance peaks in specific frequencies. In this paper, we investigate the channel capacity in a special medium affected by chirality effects, such as biomolecules, DNA chains, and so on. Specifically, we analyze the signal propagation in a chiral medium where a giant optical activity (GOA) is present. This effect is typical of the so-called chiral-metamaterials. Through simulation results we distinguish the behavior of a chirality-affected channel with GOA in line-of-sight and non-line-of-sight propagations, assuming different power allocation techniques and also comparing the performance to the case of No GOA.

To provide advanced services to citizens, Smart City services are enabled by a massive use of Internet of Things (IoT) technologies. The envisaged huge amount of sensors, and terminals with a great variety of typologies and applications, do not allow having a unique way to manage them, requiring for example minimal packaging and presentation overhead for many of them. In general in a network providing Smart City services, both IP and non-IP devices are present. In this paper, we tackle the security issue for non-IP devices able to connect by a short-range with a mediator gateway, forming a capillary access network, which can be seen as a short range extension of conventional access network in order to efficiently capture the IoT traffic. In particular, we propose security algorithms both for uni- and bi-directional terminals, depending on the terminal capabilities. The security algorithms are based on a local key renewal (without any exchange in air), performed just considering the local clock time. Performance are obtained respect to the maximum number of terminals that can be managed by one mediator gateway and the maximum packet delay as a function of the number of terminals in the area.

Nowadays, the use of Visible Light Communications is growing towards several applications, due to the many benefits of this technology. By efficiently modulating visible light, it is possible to reach very high data rates, while at the same time providing illumination. As a result, traditional indoor systems, like open offices and homes, become smarter, providing high efficient services i.e., localization, positioning and navigation. In this paper, we propose a simple method for indoor localization service provided by infrared LED devices. The positioning estimation can be calculated by exploiting the uniform deployment of LED-based transmitters, and the information of the impulse responses. The comparison to the impulse responses time samples of a room map, opportunely built according to the transmitters' deployment, allows to estimate the position of a mobile device inside the room. The estimation error can be then reduced on the basis of the number of LED devices used.

In this paper we present a localization technique for tracking and positioning services in self-organizing hybrid networks, where both indoor and outdoor scenarios coexist. In the proposed framework, outdoor anchor nodes act as reference nodes for estimating the position of mobile nodes, which are moving in a neighboring indoor region. The mobile nodes share some location information for estimating their own position by using flooding communication scheme. Communications between mobile nodes are allowed by IEEE 802.16e technology. The outdoor reference nodes are equipped with Global Positioning Service network interface card. The cooperation among mobile and reference nodes, and the self-organizing network behavior guarantee fast positioning estimate. The accuracy of localization measurement - in terms of position and speed uncertainty - is assessed through the Dilution of Precision factor. Moreover, to minimize position and speed estimation errors of each node, an Extended Kalman Filtering technique is adopted. Simulation results demonstrate the effectiveness of the proposed approach.

Vertical handover (VHO) techniques are applied when mobile users require service continuity and a seamless roaming between heterogeneous networks. A VHO decision can be taken on the basis of physical parameters, such as the received signal strength (RSS), data rate and signal-to-interference and noise ratio (SINR). In this paper, we compare three VHO decision criterions, each of them based on different physical metrics. A smart combination of several VHO criterions is the core of our proposed approach, which uses not only RSS or SINR parameters, but also a hybrid mixture from different wireless access networks. To improve quality of service for mobile users, a data rate gain parameter is introduced that lets an efficient VHO be executed. Simulation results of the proposed VHO approach are in terms of both end-users efficiency, i.e. cumulative received bits, and network performances, i.e. VHO frequency.

In this paper a location-based algorithm is proposed for managing soft mobile-controlled vertical handover between wireless systems. The case of a dual-mode terminal equipped with UMTS and IEEE 802.11 network interface cards is analysed in detail, and an novel approach for optimizing goodput and limit the so-called ping-pong effect is defined. The novel algorithm is based on a preliminary handover initiation phase triggered on the basis of mobile node location. Handover is then carried out by following a goodput estimation phase allowed by a transient of by casting during soft handovers. Experimental results provide an assessment on the use of location information to drive handover decisions.