Digital Twin Networks (DTNs) are an emerging paradigm where DTs collaborate to share knowledge and deliver intelligent services. To meet the need for low-latency and localized processing, DTs can be deployed at the network edge. However, effective mechanisms for inter-twin communication and service provisioning remain largely unexplored. In this paper, we address these challenges by leveraging a name-based communication paradigm, namely Information Centric Networking (ICN), enhanced with semantic-awareness. To overcome the limitations of exact name matching, we integrate deep learning models into the ICN forwarding fabric to compute semantic similarity. This enables the discovery of relevant cached service results or routes to DT service providers, even under naming heterogeneity. A preliminary evaluation shows improved service provisioning success and reduced latency compared to standard ICN delivery.

Federated Learning (FL) is gaining momentum as a prominent solution to enable on-device training while preserving data privacy. In a typical FL architecture, the function of aggregating model updates from thousands of client devices, each locally training the shared model on its own data, is placed at a dedicated node within the edge domain. Such a placement decision remains static throughout the entire training process. However, the time-varying, heterogeneous, and limited availability of computing capabilities in edge environments, coupled with fluctuating populations of participating clients across training rounds, calls for dynamic per-round placement of the aggregation function. To further optimize the usage of heterogeneous resources while accounting for FL aggregation tasks, which may require different scales of computing capabilities, a fine-grained allocation of computing resources is needed across edge nodes. The objective of this work is to jointly optimize the FL aggregation function placement at each training round and the allocated computing resources in order to minimize the overall per-round training time while not exceeding the computing capabilities of each edge node. An optimization problem is formulated, and an efficient and effective heuristic algorithm is proposed, based on local search techniques. Experimental results demonstrate that the proposed solution significantly outperforms benchmark approaches, achieving a reduction in per-round training time and bandwidth consumption. Under the considered settings, the proposal yields up to a 27% gain in training time compared to methods that optimize aggregation placement only, without performing fine-grained resource allocation.

In-Network Computing (INC) is emerging as a key enabler of Sixth-Generation (6 G) systems, allowing programmable network nodes to provide not only connectivity, but also storage and processing across the cloud-to-edge continuum. Machine learning (ML) tasks, particularly Deep Neural Network (DNN) inference, stand to benefit significantly from this shift. Under the Split Inference (SI) paradigm, different layers of a DNN can be distributed across multiple in-network nodes that cooperate with the end-device requesting inference. In this work, we explore the potential of Named Data Networking (NDN) as an enabler for in-network SI. We demonstrate how NDN’s native features, such as in-network caching and routing-by name, can reduce inference delays and improve robustness under lossy edge connectivity, compared to traditional host-centric networking. Simulation results validate the effectiveness of NDN-based innetwork SI, highlighting its potential to enable resilient and efficient ML services in future 6 G environments.

Unmanned Aerial Vehicles (UAVs) integrated with Internet of Things (IoT) systems represent a powerful solution for reestablishing connectivity in emergency scenarios where terrestrial infrastructure is damaged or overloaded. However, ensuring service continuity under UAV mobility and resource constraints poses significant orchestration challenges. This paper presents a mobility-aware orchestration framework tailored for UAV-enabled IoT networks in such critical contexts. Leveraging Kubernetes for service orchestration and Prometheus for telemetry monitoring, we design and implement a modular architecture that dynamically reallocates containerized services across mobile UAV nodes in real time. Our framework is validated through physical testbed experiments on Raspberry Pi-equipped UAVs, where container migration is triggered by geographic constraints and monitored across varying pod workloads and link conditions. Results demonstrate robust adaptability, sub-second recovery under favorable link quality, and a scalable orchestration strategy for mission-critical operations. This work advances the practical deployment of orchestrated UAV swarms, bridging the gap between theoretical frameworks and real-world mobility-aware computing.

Split inference (SI) has been devised as a valuable solution to enable the execution of computation-heavy deep neural network (DNN) inference models on resource-constrained edge devices. The different layers of a DNN model are distributed to one or several nodes (mainly edge/cloud servers) cooperating with the end-device requesting the inference. Boosted by the sixth generation (6 G) trends, programmable network nodes equipped with computing, caching and intelligence capabilities can be involved in such a cooperative task. In this work, we propose Named Data Networking (NDN) as a key enabler of in-network SI. Its connectionless communication model coupled with routing-by-name and native in-network caching capabilities can facilitate dynamic splitting operations on nodes throughout the cloud-to-things continuum. We show how NDN design principles and communication primitives can be leveraged to support in-network SI. Then, preliminary results are reported to showcase the benefits of the conceived proposal.

Infrastructure-assisted automated driving will highly rely on real-time updates received from the network about the surroundings, which demand for ultra-low latency, high-throughput and highly reliable wireless connectivity. In the future, the quality of connectivity will directly impact the driving capability of these autonomous vehicles: lower downlink quality will in fact reduce the situational awareness, forcing the vehicle to, for example, reduce speed and increase safety distance. In this context, we propose a solution which allows a vehicle to choose the route that ensures the best connectivity conditions to reach its destination. Specifically, we consider that different connected and automated driving (CAD) Modes are possible depending on the estimated downlink radio quality, and the route is selected accordingly. Experiments have been conducted through simulations in an urban environment, utilizing the SUMO mobility simulator and the Sionna RT channel modelling tool. The obtained results demonstrate that the network quality can indeed significantly influence route selection, paving the way for future research towards sixth generation (6G) where services and mobility predictions can drive network optimizations.

Federated Learning (FL) is gaining momentum as a promising solution to enable the efficient and privacy-preserving distributed training of Machine Learning (ML) models. Unlike centralized ML solutions, only the ML model and its updates are transferred between the clients and the aggregator server, eliminating the need to share large datasets. Notwithstanding, poor connectivity conditions experienced over the path that interconnects the FL clients and the aggregator server, either due to (wireless) channel losses or congestion, may deteriorate the training convergence. Several methods have been devised to reduce the training duration, primarily by minimizing data transfer through the design of ML algorithms at the application level. However, these solutions still exhibit unsettled issues, as they may only reduce the communication footprint but do not improve the communication process as a whole. Differently, in this work, our aim is to improve FL data exchange from a networking perspective by promoting Information Centric Networking (ICN) approaches rather than host-centric TCP/IP-based solutions. To this aim, we analyse the impact that host-centric transport protocols as well as ICN approaches have on the FL performance, in terms of duration of the model training and exchanged data (model and updates) load, under different channel loss settings. We show that ICN-based FL solutions significantly reduce the network data load and decrease the duration of the training round by up to an order of magnitude for high channel loss rates.

Federated Learning (FL) enables multiple devices (clients) training a shared machine learning (ML) model on local datasets and then sending the updated models to a central server, whose task is aggregating the locally-computed updates and sharing the learned global model again with the clients in an iterative process. The population of clients may change at each round, whereas the node executing the aggregation function is typically placed at an edge domain and remains static until the end of the overall FL training process. Indeed, the computing capabilities of the edge node hosting the aggregation function and the distance (latency) of such a node from the selected clients can highly affect the convergence rate of the FL training procedure. Moreover, the heterogeneous time-varying capabilities of edge nodes, coupled with the dynamic client population selected at each round, call for the optimal dynamic placement of the aggregation function across the available nodes in an edge domain. In this work, we formulate an optimization problem for the placement of the FL aggregation function, which aims to select at each round the edge node able to minimize the overall per-round training time, encompassing the aggregation time, the local training time at the clients and the time for exchanging the global model and the model updates. A time-efficient greedy heuristics is proposed, which is shown to well approximate the optimal solution and outperform the considered benchmark solutions.

E-bikes are recognized for their sustainable transportation benefits. However, the higher speeds associated with e-bikes pose an increased risk of potential accidents and hinder fluid riding in swarms with conventional bicycles. In this paper, we analyze the accuracy of maintaining an unknown speed, assess the associated workload, and investigate the self-reported speeds of e-bike cyclists in order to adapt the electric assistance to dynamic speed limits based on the surrounding traffic conditions. Our results from a pilot study with 15 participants show that the accuracy of maintaining a speed limit through active motor control and the associated workload are influenced by factors such as the level of electrical assistance and the perception of motor disengagement. E-bike cyclists using higher levels of electrical assistance demonstrated more accurate target speed maintenance. On average, participants consistently underestimated adapted speed limits, which were also influenced by the level of electrical support.

Mobile network traffic has seen a significant surge, doubling in the past two years, due to increased adoption of fifth-generation ($\mathbf{5 G)}$ subscriptions. This emphasizes the need for efficient solutions like multicasting to manage escalating data demands. Multicast communications, however, encounter challenges in highly directional transmission scenarios, typical for 5G and sixth-generation (6G) systems. In such scenarios, characterized by the presence of obstacles or signal attenuation affecting one user, the performance degradation propagates across the entire multicast group. While Reconfigurable Intelligent Surfaces (RISs) have shown promise in mitigating blockage issues and optimizing wireless propagation environments, limited research has been done on their application to multicast communication. To address this gap, this study introduces a novel multicast group formation framework designed for highly directional RIS-enhanced multicast communications. The framework utilizes Self-Organizing Map (SOM) to organize close-range users into multicast groups based on the similarity of their azimuth angles relative to the RIS, while either microwave multicasting or mmWave unicasting are considered for users at greater distances. Furthermore, the study provides closed-form expressions for the transition threshold from SOM to either microwave multicasting or mmWave unicasting. Our results (in terms of data rate) demonstrate that the proposed approach with microwave technology outperforms all benchmark schemes and remains stable as the number of users increases, while the mmWave unicast approach exhibits performance similar to pure unicasting.

In the fifth generation (5G) Vehicle-to-Everything (V2X) autonomous mode, vehicles may select radio resources for their packet transmissions without the support of the base station (BS). For periodic traffic, the same resources can be accessed at consecutive reservation intervals to improve the selection procedure. However, potential collisions occurring during this period may remain undetected and persist over time. Previous studies introduced algorithms leveraging in-band full-duplex (FD) transceivers to detect and react to collisions by performing resource reselection. However, as demonstrated in this paper, in more realistic scenarios where part of the data traffic is not periodic, performing reselections after collisions, regardless of the traffic type, may not be effective and could even be counterproductive. To address this issue, this work introduces two novel alternative schemes, each with its own advantages and drawbacks, both based on FD transceivers. Simulation results demonstrate that both solutions effectively handle scenarios with mixed traffic. Without penalising the aperiodic traffic, the range of periodic traffic is improved by up to 38% over the legacy Mode 2 under heavy traffic conditions.

Tele-operated Driving (ToD) is an ambitious use case in the automotive sector that enables the remote operation of vehicles, e.g., when they are located in dangerous environments, for logistics fleet operations. ToD heavily relies on 5G connectivity able to guarantee strict latency, reliability, and bandwidth requirements, for instance through a dedicated network slice. In this paper, we propose a Digital Twin (DT)-assisted radio resource allocation scheme that manages the Radio Access Network (RAN) resources within the ToD network slice. In particular, our contributions leverage interactions between the DT of the RAN and of other ToD players to feed an algorithm for efficient radio resource allocation, based on the actual ToD service demand on the planned driving paths. Early results on a realistic map demonstrate the resource savings achieved by our proposal compared to a static resource allocation scheme.

The Third Generation Partnership Project (3GPP) recently introduced the fifth-generation (5G) new radio (NR) sidelink to enable vehicle-to-everything (V2X) communications supporting advanced safety services. Nevertheless, improvements over the previous generation still pose challenges to meet the reliability and latency requirements of V2X communications, particularly in the allocation of distributed resources, i.e., Mode 2. In Mode 2, vehicles autonomously select radio resources for their message transmissions and can maintain the selected resources for a given reservation period to efficiently handle periodic data traffic. However, potential collisions during this period may remain undetected due to half-duplex communications and unacknowledged broadcast transmissions, resulting in persistent message losses and posing a threat to road safety. This paper aims to improve the 5G NR-V2X sidelink for systems beyond 5G-Advanced by exploiting full-duplex transceivers. We propose a novel medium access control (MAC) scheme where vehicles can detect collisions while transmitting, dynamically adapt the collision detection threshold according to the measured channel load, and react to detected collisions through appropriate resource reselection and retransmission procedures. Extensive simulations conducted under various settings show that this MAC scheme brings substantial performance gains in terms of reliability and latency, compared to the current legacy Mode 2 procedure and a benchmark full-duplex scheme from the literature.

Digital Twins (DTs), which are paired to Internet of Things (IoT) devices to represent them and augment their capabilities, are gaining ground as a promising technology to enable a wide variety of applications in the sixth-generation (6G) ecosystem, ranging from autonomous driving to extended reality and metaverse. In particular, “social” IoT (SIoT) devices, which are devices capable to establish social relationships with other devices, can be coupled with their virtual counterparts, i.e., social DTS (SDTs), to improve service discovery enabled by browsing the social network of friend devices. However, the mobility of SIoT devices (e.g., smartphones, wearables, vehicular on board units, etc.) may require frequent changes in the corresponding SDT placement in the edge domain to maintain a low latency between the physical device and its digital replica. Triggering SDT relocation at the right time is a critical task, because an incorrect choice could lead to either increased delays or a waste of network resources. This work proposes a learning-powered social-aware orchestration that predicts the mobility of SIoT devices to make more judicious migration decisions and efficiently move the paired SDTs accordingly, while ensuring the minimization of both intra-twin and inter-twin communication latencies. Different machine learning (ML) and deep learning (DL) algorithms are used for SIoT device mobility prediction and compared in terms of a wide set of meaningful metrics in order to identify the model that achieves the best trade-off between prediction accuracy and inference times under different scenarios. Simulation results showcase the improvements of the proposal in terms of reduced network overhead (by up to a factor of 3) and intra-twin and inter-twin communication latency (by up to 10%) compared to a more traditional solution, which activates the relocation of the DTs at fixed time intervals following periodic optimizations.

Edge computing is aimed to support compute-intensive data-hungry interactive applications which can hardly run on resource-constrained consumer devices and may suffer from running in the cloud due to the long data transfer delay. The edge network nodes' heterogeneous and limited (compared to the cloud) capabilities make the computing task placement a challenge. In this paper, we propose a novelin-networktask placement strategy aimed at minimizing the edge network resources usage. The proposal specifically accounts fortime-limited reusablecomputing tasks, i.e., tasks whose output can be cached to serve requests from different consumers for a certain time. Caching such results, during their time validity, achieves the twofold benefit of reducing the service provisioning time and improving the edge resource utilization, by avoiding redundant computations and data exchange. The devised strategy is implemented as a network application of a Software-defined Networking Controller in charge of overseeing the edge domain. We formulate the optimal task placement through an integer linear programming problem, and we define an efficient heuristic algorithm that well approximates the solution achieved through a standard optimal solver. Achieved results show that the proposal successfully meets the targeted objectives in a wide variety of simulated scenarios, by outperforming benchmark solutions.

The increasing volume of Internet traffic is pushing the Internet Service Providers to deploy distributed caching services at the network edge, close to the end users, in order to speed up the data retrieval and reduce the bandwidth demands. In parallel, centralized paradigms like Software Defined Networking (SDN) are considered to optimize network management while supporting a variety of network applications like routing, load balancing and caching. In this paper, we extend the SDN control plane to support a novel content caching strategy. We consider a softwarised edge network domain where SDN nodes, augmented with storage capabilities, cache incoming data with the twofold target of limiting the retrieval delay and the inter-domain traffic. The caching decision is taken in a centralized mode by the SDN Controller, according to a newly defined content-driven closeness centrality metric, which identifies the importance of the SDN nodes as cachers based on their proximity to the majority of the clients requesting the most popular contents. Simulation results show the superiority of the solution in terms of higher cache hits and reduced latency, when compared against benchmark caching strategies.

The outbreak of the Covid-19 pandemic has caused a severe overload of intensive care units with a consequent drastic reduction of ordinary hospitalization, diagnostic tests, and interventions that has led to a significant increase in the number of deaths due to diseases other than the new coronavirus. Information and Communication Technologies (ICT) and the forthcoming Sixth-Generation (6G) system may revolutionize the doctor-patient relationship and healthcare modalities owing to the introduction of eHealth (or digital health). In this context, Non-Terrestrial Networks (NTNs) have vital importance in providing global connectivity thus improving the availability of eHealth services, especially in rural and remote areas. In this paper, we propose a Reliable Satellite Routing Algorithm (RSRA) for a 3D NTN based on Low-Earth Orbit (LEO) satellites. RSRA enables health data detected by sensors worn by the patients to be transmitted to health professionals by selecting a chain of reliable LEO satellites in order to protect such sensitive data. The system-level performance of proposed RSRA algorithm is assessed through simulation campaigns and compared against a routing approach that neglects LEO satellite reliability.

Applications envisioned to enable connected and autonomous vehicles entail the exchange of data through reliable and low-latency direct communications between vehicles. The current specifications for the cellular-vehicle-to-everything (C-V2X) technology can still barely match such requirements. To tackle this issue, we investigate here the joint application to the C-V2X sidelink with autonomous resource allocation of two techniques that are being considered for the evolution of cellular systems, i.e., in-band full-duplex (FD) and non-orthogonal multiple access (NOMA). In particular, we consider FD capabilities to detect ongoing collisions while transmitting and thus resolve persistent resource allocations, which are causing repeated errors at the neighboring receivers. Regarding NOMA, we consider the use of successive-interference cancellation (SIC) for the decoding of multiple signals when different vehicles are transmitting simultaneously using the same resources, thus converting packet losses into improved spectral efficiency. The investigation is based on the latest fifth generation (5G) New Radio (NR)-V2X specifications and focuses on broadcast transmissions, which are expected to cover the majority of the exchanged traffic in V2X contexts. As shown through simulations in large-scale scenarios, the two techniques, both relying on signal processing at the receiver to cancel the (self or successive) interference, provide complementary advantages under different conditions. FD is in fact very effective to improve the delivery performance at short distances when periodic data traffic is assumed, while SIC-based NOMA improves the reception probability at medium distances both under periodic and aperiodic data traffic conditions.

The analysis of data coming from massively deployed Internet of Things (IoT) devices pave the way to a myriad of intelligent applications in several vertical domains. Federated Learning (FL) has been recently proposed as a prominent solution to train Machine Learning (ML) models directly on top of devices (FL clients) generating data, instead of moving them to centralized servers in charge of training procedures. FL provides inherent benefits, mainly in terms of privacy preservation and reduction of network congestion for datasets exchange. Despite the huge recent research efforts, it still faces challenges for a practical implementation effectively targeting low communication footprint, robustness and interoperability. To fill this gap, in this work we propose a novel comprehensive framework built upon the Message Queue Telemetry Transport (MQTT) publish/subscribe messaging protocol and the Open Mobile Alliance (OMA) Lightweight Machine-to-Machine (LwM2M) semantics to facilitate FL operations and make them more suited to handle IoT devices acting as FL clients. The viability of the proposal as well as its communication efficiency compared to a literature solution are evaluated through a realistic Proof-of-Concept (PoC) under different link settings and for different datasets.

The support of multicast communications in the fifth-generation (5G) New Radio (NR) system poses unique challenges to system designers. Particularly, the highly directional antennas do not allow to serve all the user equipment devices (UEs) that belong to the same multicast session in a single transmission. The capability of modern antenna arrays to utilize multiple beams simultaneously, with potentially varying half-power beamwidth, adds a new degree of freedom to the UE scheduling. This work addresses the challenge of optimal multicasting in 5G millimeter wave (mmWave) systems by presenting a globally optimal solution for multi-beam antenna operation. The optimization problem is formulated as a special case of multi-period variable cost and size bin packing problem that allows to not impose any constraints on the number of the beams and their configurations. We also propose heuristic solutions having polynomial time complexity. Our results show that for small cell radii of up to 100 meters, a single beam is always utilized. For higher cell coverage and practical ranges of the number of users (5-50), the optimal number of beams is upper bounded by 3.

According to the 6G vision, the evolution of wireless communication systems will soon lead to the possibility of supporting Tbps communications, as well as satisfying, individually or jointly, a plethora of other very stringent quality requirements related to latency, bitrate, and reliability. The achievement of these goals will naturally raise many research issues within radio communications. In this context, a promising 6G wireless communications enabler is the reconfigurable intelligent surface (RIS) hardware architecture, which has already been recognized as a game-changing way to turn any naturally passive wireless communication setting into an active one. This paper investigates RIS-aided multicast 6G communications by first modeling the system delay as a first-come-first-served (FCFS) M/D/1 queue and analyzing the behavior under different blockage conditions. Then the study of multi-beam operation scenarios, covering multicast and RIS-aided multicast communications, is conducted by leveraging an M/D/c queue model. Achieved results show that large-size RISs outperform even slightly obstructed direct BS-to-user paths. In contrast, RISs of smaller sizes require the design of sophisticated power control and sharing mechanisms to achieve better performance.

Federated learning (FL) is gaining momentum as a prominent solution to perform training procedures without the need to move sensitive end-user data to a centralized third party server. In FL, models are locally trained at distributed end-devices, acting as clients, and only model updates are transferred from the clients to the aggregator, which is in charge of global model aggregation. Although FL can ensure better privacy preservation than centralized machine learning (ML), it exhibits still some concerns. First, clients need to be properly discovered and selected to ensure that highly accurate models are built. Second, huge models may still require to be exchanged from the aggregator to all the selected clients, incurring a not negligible network footprint. To tackle such issues, in this paper, we propose a framework built upon in-network caching, multicast and name based data delivery, natively provided by the Named Data Networking (NDN) paradigm, in order to support client discovery and aggregator-clients data exchange. Benefits of the proposal are showcased when compared to a conventional application-layer solution.

Efforts are underway to finalize the fifth generation (5G) vehicle-to-everything (V2X) communication technology. Direct communication among vehicles over the sidelink interface through the autonomous selection of radio resources is among the main and more challenging capabilities of such a connectivity solution. Nonetheless the crucial enhancements conceived by the Third Generation Partnership Project (3GPP) in Release 16, the autonomous resource allocation (a.k. a. Mode 2) still suffers from collisions due to the wrong estimation of the resource occupancy status enforced by half-duplex (HD) transceivers. In this paper, we argue in favour of the usage in vehicles of in-band full-duplex (FD) transceivers, gaining momentum in the research towards sixth generation (6G) systems thanks to their simultaneous transmission and reception capability. Exploiting FD, we propose to enhance the autonomous mode by detecting collisions and triggering resource reselection procedures in a more conscious manner. Simulation results show that the conceived proposal allows sidelink V2X to achieve significant improvements in terms of reliability and timeliness when compared against the legacy Mode 2.

The increasing processing capabilities of massively deployed Internet of Things (IoT) and edge devices coupled with the rising demands for fast and autonomous decision-making pave the way for accurate Machine Learning (ML) model training in proximity to where data is collected, as proposed by the Federated Learning (FL) paradigm. The devices contributing to the local training (clients) are typically large in number and differ in terms of computing and battery capabilities, experienced link quality conditions and owned datasets. If clients are not properly selected by the entity in charge of aggregating the individual models (FL server) both the convergence speed and the accuracy of the resulting model can be affected. The interest in the literature for the optimization of the client selection policies is manifest, but less attention has been devoted to the design of the practical implementation of such policies with focus on the client discovery procedures. In order to fill this gap, an edge-based framework is proposed to improve the FL client discovery procedures by leveraging (i) the Message Queue Telemetry Transport (MQTT) protocol for FL clients-server interactions aimed to retrieve the capabilities of the potential clients and (ii) the Open Mobile Alliance (OMA) Lightweight-Machine-to-Machine (LwM2M) for the semantic description of such capabilities. A proof-of-concept is provided to assess the communication footprint incurred by the proposal.

Internet of Space Things (IoST) is a challenging paradigm, which is currently attracting great interest from the scientific and industrial communities. IoST is based on the integration of the space segment into the global Internet-of-Things (IoT) infrastructure. In the relevant literature, reference is generally made to multiple constellations of nanosatellite platforms, used to enable IoT services on a global scale, including also disadvantaged and poorly infrastructured areas. In this article, we focus on multitenant IoT scenarios, wherein multiple CubeSats constellations are enabled to offer services by exploiting a dynamic federation model. The objective is to efficiently provide services in an IoST scenario by leveraging an effective cooperation strategy originally designed for terrestrial IoT networks, the Mobile-IoT-Federation-as-a-Service (MIFaaS) paradigm. We extend this vision to IoT satellite networks in order to allow a constellation of satellites to effectively execute tasks through a tight cooperative behavior with other CubeSats constellations. The reported performance evaluation studies show that better performance, in terms of percentage of tasks successfully completed, can be achieved through the implementation of the proposed cooperation paradigm.

As the fifth-generation (5G) and beyond (5G+/6G) networks move forward, and a wide variety of new advanced Internet of Things (IoT) applications are offered, effective methodologies for discovering time-relevant information, services, and resources are being demanded. To this end, computing-, storage-, and battery-constrained IoT devices are progressively augmented via digital twins (DTs) hosted on edge servers. According to recent research results, a further feature these devices may acquire is social behavior; this latter offers enormous possibilities for fast and trustworthy service discovery, although it requires new orchestration policies of DTs at the network edge. This work addresses the dynamic placement of DTs with social capabilities [social digital twins (SDTs)] at the edge, by providing an optimal solution under IoT device mobility and by accounting for edge network deployment specifics, types of devices, and their social peculiarities. The optimization problem is formulated as a particular case of the quadratic assignment problem (QAP); also, an approximation algorithm is proposed and two relaxation techniques are applied to reduce computation complexity. Results show that the proposed placement policy ensures a latency among SDTs up to 1.4 times lower than the one obtainable with a traditional proximity-based only placement while still guaranteeing appropriate proximity between physical devices and their virtual counterparts. Moreover, the proposed heuristic closely approximates the optimal solution while guaranteeing the lowest computational time.

The COVID-19 pandemic has changed the world. Today, the use of information and communications technology (ICT) in support of education, medicine, business, and administration has become a reality practically everywhere. In particular, the eHealth (digital Health) sector is on the cusp of a revolution, fueled by the worldwide health emergency due to the spread of the new coronavirus. With a view to developing new sixth-generation (6G)-oriented architectures, advanced eHealth services like telemonitoring would benefit from the support of technologies that guarantee secure data access, ultralow latency and very-high reliability targets, which are hardly achievable by the fifth generation (5G). This is the reason why this work proposes an eHealth system architecture, in which low-latency enabling technologies like Device-to-Device (D2D) communications and multiaccess edge computing (MEC) are integrated and supported by security mechanisms for an optimal management of sensitive health data collected by Internet of Medical Things (IoMT) devices. A preliminary evaluation of the proposed framework is provided that shows promising results in terms of data security and latency reduction.

Vehicle-to-everything (V2X) connectivity is deemed crucial to enable upcoming cooperative automated driving applications. The Cellular-V2X (C-V2X) technology supports direct interactions among vehicles over the sidelink interface. According to the autonomous mode, vehicles select sidelink radio resources for their message transmissions in a completely distributed manner, without the support of the base station. The majority of works focused so far on periodic message transmissions, for which sidelink resources can be semi-persistently reserved after a channel sensing procedure. In this paper, we take a step forward by considering both periodic and high-priority aperiodic messages, such as sporadic decentralized environmental notification messages (DENMs), competing for the same resources. The impact of some new sidelink features devised in 5G-V2X (Release 16) for the autonomous mode, such as the new radio (NR) flexible numerology, the short-term sensing, the pre-emption mechanism, are preliminarily investigated in this paper. They are coupled with a newly proposed resource reservation scheme for the repetitions of DENMs. Results showcase the improvements of our proposal in terms of higher DENM reliability achieved with little-to-none additional signaling, with a negligible impact on periodically transmitted messages.

With more than 75 billions of objects connected by 2025, Internet of Things (IoT) is the catalyst for the digital revolution, contributing to the generation of big amounts of (transient) data, which calls into question the storage and processing performance of the conventional cloud. Moving storage resources at the edge can reduce the data retrieval latency and save core network resources, albeit the actual performance depends on the selected caching policy. Existing edge caching strategies mainly account for the content popularity as crucial decision metric and do not consider the transient feature of IoT data. In this article, we design a caching orchestration mechanism, deployed as a network application on top of a software-defined networking Controller in charge of the edge infrastructure, which accounts for the nodes’ storage capabilities, the network links’ available bandwidth, and the IoT data lifetime and popularity. The policy decideswhich IoT contentshave to be cached andin which nodeof a distributed edge deployment with limited storage resources, with the ultimate aim of minimizing the data retrieval latency. We formulate the optimal content placement through an Integer Linear Programming (ILP) problem and propose a heuristic algorithm to solve it. Results show that the proposal outperforms the considered benchmark solutions in terms of latency and cache hit probability, under all the considered simulation settings.

The research into wireless communication and mobile computing is called to formulate novel smart mobility solutions to improve the quality of a citizen's life in smart cities. In such a context, in this paper we elaborate on the role of technologies like multi-access edge computing (MEC), Internet of Things (IoT) messaging protocols, such as Constrained Application Protocol (CoAP) and Message Queue Telemetry Transport (MQTT), and virtualization (i.e., digital twins) in the design of a framework enabling the collection and processing of data about the mobility of commuters and public transport vehicles. Such data have the purpose to feed mobility monitoring and transport planning solutions. A Proof-of-Concept (PoC) is developed to validate the framework under realistic experimental settings. Results in terms of efficiency and effectiveness of the considered messaging protocols are reported.

Non-Terrestrial Networks (NTNs) based on the emerging 5G New Radio (NR) technology stand as an effective solution to complement terrestrial networks in service provisioning, owing to their ability to satisfy requests of anywhere and anytime connection, and to increase network scalability by delivering multicast/broadcast services to groups of NTN terminals through Point-to-Multipoint transmissions. However, current satellite systems operating at different orbits remain isolated islands and fail to express their true potential if not properly made interoperable with ground networks. In the light of effectively integrating existing 5G networks into a unified system, we propose a cooperative radio resource management scheme that enhances the performance of an integrated terrestrial-NTN system based on the emerging 5G NR technology. It leverages the principles of multicast subgrouping techniques to determine which users will get connected to either terrestrial base station (i.e., gNB) or NTN cell (i.e., NTN-gNB) and properly allocate resources in order to improve the overall network throughput. Simulation results show the effectiveness of the proposed solution.

Age of Information is a new metric used in real-time status update tracking applications. It measures at the destination the time elapsed since the generation of the last received packet. In this paper, we consider the co-existence of critical and noncritical status updates in a two-hop system, for which the network assigns different scheduling priorities. Specifically, the high priority is reserved to the packets that traverse the two nodes, as they experience worse latency performance. We obtain the distribution of the age and its natural upper bound termed peak age. We provide tight upper and lower bounds for priority updates and the exact expressions for the non-critical flow of packets with a general service distribution. The results give fundamental insights for the design of age-sensitive multi-hop systems.

Software Defined Networking (SDN) and Named Data Networking (NDN) have been recently advocated as complementary paradigms to improve content distribution in the next-generation Internet. On the one hand, SDN offers a centralized control plane that can optimize routing decisions; on the other, the distinctive features at the NDN data plane, such as name-based delivery, in-network caching, and stateful forwarding, simplify data dissemination. In the integrated design, when a request cannot be handled locally at the NDN data plane in the Forwarding Information Base (FIB), the SDN Controller is contacted to inject the forwarding rule. Decisions such as which rules need to be stored in the node and for how long deeply affect the packet forwarding performance. This paper debates about the issues related to forwarding rules in the FIBs of SDN-controlled NDN nodes, by specifically accounting for their name-based nature, representing a key novelty compared to legacy SDN implementations. Quantitative results are reported to showcase the impact of crucial parameters, like the content popularity, the content requests rate, the table size, on the FIB performance in terms of valuable metrics (e.g., hit ratio, rejected requests, incurred signaling with the Controller).

Current vehicular communication technologies were designed for a so-called phase 1, where cars needed to advise of their presence. Several projects, research activities and field tests have proved their effectiveness to this scope. But entering the phase 2, where awareness needs to be improved with non-connected objects and vulnerable road users, and even more with phases 3 and 4, where also coordination is foreseen, the spectrum scarcity becomes a critical issue. In this work, we provide an overview of various 5G and beyond solutions currently under investigation that will be needed to tackle the challenge. We first recall the undergoing activities at the access layer aimed to satisfy capacity and bandwidth demands. We then discuss the role that emerging networking paradigms can play to improve vehicular data dissemination, while preventing congestion and better exploiting resources. Finally, we give a look into edge computing and machine learning techniques that will be determinant to efficiently process and mine the massive amounts of sensor data.

The first set of specifications for the Cellular-Vehicle-to-Everything (C-V2X) technology has been issued by the Third Generation Partnership Project (3GPP) in Release 14 to enable the exchange of periodic cooperative awareness messages supporting basic safety applications. Enhancements towards 5G New Radio (NR) V2X are under study in Release 16 in order to support advanced vehicular use cases with stricter latency and reliability demands, and different traffic patterns (e.g., aperiodic messages, unicast delivery). In this paper, we focus on the support of aperiodic traffic like Decentralized Environmental Messages (DENMs), which are sent out asynchronously to vehicles alerting them to road hazard events such as anomalous traffic conditions, road-works or signal violation, emergency braking. DENMs can be repeatedly transmitted in a relevant area to increase message reliability during the event lifetime. Simulations have been conducted to analyze scenarios where periodic and event-triggered messages share the same radio resource pool(s) in the autonomous sidelink mode of NR V2X. The main parameters of the autonomous resource allocation mechanism affecting the DENM delivery have been investigated as well as the benefits of DENM repetitions, while also considering their impact over periodically transmitted messages, under different simulation settings.

The ever-increasing demand for high-quality video contents over mobile networks is pushing Telco operators towards the design of new delivery solutions. 3GPP has defined Multimedia Broadcast/Multicast Service Single Frequency Network (MBSFN) to enable the simultaneous transmission of the same content within multiple cells over the same radio resources, with improved network scalability and spectral efficiency. This paper proposes a Dynamic MBSFN Area Formation (DMAF) algorithm that suitably selects the adjacent synchronized cells to include in any MBSFN Area of a 5G New Radio (NR) system to the purpose of increasing the system Aggregate Data Rate while avoiding user outage. The proposed algorithm dynamically creates MBSFN Areas by leveraging the multicast “subgrouping” paradigm for Scalable Video Coding (SVC) traffic delivery. Cells are grouped into different MBSFN Areas and any cell can be part of Disjoint MBSFN Area or Overlapping MBSFN Area. Each Overlapping MBSFN Area broadcasts a Base video flow at a given quality level to all users, whereas Enhancement Layers are only delivered to users with better channel conditions. Simulation results testify to the better performance achieved by the proposed algorithm w.r.t. other schemes available from the literature.

Broadcast traffic in IEEE 802.11 vehicular networks is known to suffer from poor performance due to the lack of recovery mechanisms from packet losses, based on the rules of the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) protocol. This may have a detrimental impact on cooperative vehicular safety applications that build on the reliable regular broadcasting of status messages by vehicles in a local neighborhood. Full-Duplex (FD) techniques can improve the broadcast CSMA/CA performance by letting a sending vehicle sense the channel while transmitting, thus enabling “collision detection”. The vehicle, consequently, can abort the packet prone to collision and reattempt a later transmission. In this paper, we define a stochastic geometry model that captures the collision detection capability of FD-enabled vehicles, while accurately characterizing the interference power generated by other vehicles on a road segment, and the dynamics of the backoff mechanism used for broadcast packet retransmissions. The model provides helpful insights into the FD broadcast CSMA/CA behaviour, highlighting a clear relationship between the settings for the carrier sense threshold and the collision detection threshold and the number of covered receivers on the road.

Mobility as a Service (MaaS) implies the integration of different transport services in a unique platform accessible by commuters on demand. Collection and processing of data concerning the mobility of customers is crucial to calculate trips options satisfying users' needs and preferences. In this paper, we propose to exploit Multi-access Edge Computing (MEC) facilities to more efficiently deploy MaaS solutions. Specifically, we design a MEC-based MaaS framework that is fully compliant with the Open Mobile Alliance (OMA) Lightweight Machine-to-Machine (LwM2M) protocol. The OMA LwM2M server hosted in the MEC platform continuously collects data from the commuters, and uses native MEC applications to provide value-added services. The OBSERVE extension of the Constrained Application Protocol (CoAP) is used to reduce energy consumption during data collection from the OMA LwM2M clients installed in the mobile user devices. Preliminary results are collected that show the performance of the proposed MaaS framework, integrated with a mobility generator tool (i.e., SUMO) that emulates the commuter paths.

A new class of miniaturized satellites, named CubeSats, have recently drawn the attention of the academic community first, and later of industry too, because they appear as a high attractive solution to provide a true widespread connectivity that allows also objects in remote areas to be part of the global Internet of Things (IoT). In this paper, we study the integration of this kind of satellites into multi-tenant scenarios, wherein multiple CubeSats constellations may be able to offer services even in an integrated manner. In particular, an IoT platform running within SDN/NFV-ready infrastructures which also includes CubeSat segments is designed. In the proposed architecture, CubeSats are considered as IoT sensing and actuation devices in the sky always available and able to provide enhanced services through their virtual counterpart (i.e., the virtual object). Useful scenarios are described and studied in which different constellations of CubeSats can be orchestrated via the proposed virtualisation platform to cooperate in providing IoT services.

The Multi-access Edge Computing (MEC) paradigm and the Cellular Vehicle-to-Everything (C-V2X) technology prove to be good candidates to address the vehicular applications' demands of high-performing connectivity and low-latency access to computing and storage resources. MEC provides cloud-like resources at the network edge, i.e., at the Multi-access Edge (ME) host. While vehicles move around, a service application instance running on a ME host may be triggered to move to another ME host to better support the application's demands. As a side effect, this migration may undermine service continuity. In this paper, we refer to the latest available ETSI MEC and 3GPP C-V2X specifications to investigate the issue of service migration between ME hosts in the context of vehicular communication. Early experimental results provide measures of the service migration latencies when ME applications run as Docker containers.

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.

Pushed by the challenging demands of fifth generation (5G) use cases and the recent advancements in virtualization technologies, edge network devices are rapidly evolving from simple forwarders to softwarized infrastructures augmented with computing and storage capabilities. Such a trend blurs the distinction between IT and telco domains and paves the way for the integrated management of network and computing resources. In this paper, we focus on the interplay of the Software Defined Networking (SDN) and Named Data Networking (NDN) paradigms as key drivers for the orchestration of computing services in softwarized edge infrastructures. We propose a new framework that brings out the best of the SDN centralized intelligence to take “smart” decisions and inject rules for service allocation (e.g., retrieve input data, execute a function over them), and the best of the adaptive NDN forwarding plane and its native in-network caching to request and deliver services by name. Within the framework, we devise a service allocation strategy that aims at selecting as an executor, among the potential candidates, the one which is able to guarantee the shortest service provisioning delay for each service request, while accounting for the network topology, the links status, and the available computing resources in the edge nodes. Performance evaluations testify to the superiority of our proposal against benchmarking solutions from the literature under different operation settings.

Edge computing is a key paradigm to offload the core network and effectively process massive Internet of Things (IoT) raw data without sending them to the cloud. This paradigm normally relies on a set of purpose-built and pre-planned servers, which host storage and processing resources to provide IoT services close to the data sources, thus saving core network resources and offloading the remote cloud infrastructure. In this paper, we propose to turn the network edge into a dynamic, distributed computing environment that supports the provisioning of IoT services, by exploiting the recent evolution of named data networking (NDN), supporting both name-based data retrieval and computation. Specific name structure and novel NDN forwarding mechanisms are designed; a distributed strategy is also engineered to select the service executor among edge nodes, with the objectives to: 1) limit the raw IoT data traffic crossing the network and 2) allocate the service execution according to the nodes' available processing resources. Numerical analysis shows that the performance of the proposed framework approaches the one of the optimal solution of a formulated integer linear programming problem. System-level ndnSIM simulations confirm that the proposal also outperforms the considered state-of-the-art benchmark solutions in terms of service provisioning time.

The ever-increasing demand for ubiquitous high- data rate services pushes the Telco operators to face high challenging requirements for supporting bandwidth-hungry applications and for ensuring service continuity when a user is moving over a wide area. To guarantee this, Mobile Satellite Services (MSSs), especially Multimedia Broadcast Multicast Services (MBMSs), have gained great importance. Therefore, in this paper we propose a novel Radio Resource Management scheme for the efficient allocation of radio resources when delivering multicast video flows in 5G Satellite systems. The proposed Satellite - Multicast Subgrouping Multiple Layers (S-MSML) scheme jointly exploits both the Multicast Subgrouping and the Scalable Video Coding (SVC) technique to provide a minimum required quality to all multicast users and enhanced video quality to users in good channel condition. Finally, the results show that the proposed algorithm achieves better performance than the Legacy approach when considering multiple multicast groups in all considered environments.

Named Data Networking (NDN) has been recently extended to enable the discovery and provisioning by name of in-network cloud-like services such as processing and data storage. Such a feature is particularly helpful in distributed edge environments, where mobile end devices can be involved in service offering. In such a context, a challenging issue is to motivate a mobile device to behave as a provider and share its resources (e.g., CPU, memory) in order to assist other end devices (consumers), in wireless proximity, asking for a given service. In this paper, we propose a solution revolving around two concepts: enhanced NDN primitives and a social-driven stimulus for mobile devices to volunteer as service providers. A bio-inspired response function is used by a potential provider's device to rate both its available resources and the social ties with the current consumer's device, established according to the Social Internet of Things (SIoT) paradigm. An early evaluation showcases to which extent the conceived solution allows a consumer to find a nearby provider available to offer its services, under different social neighbourhood settings.

The coexistence of human type communications (HTC) with an ever-increasing number of machine type communications (MTC) is a challenge that the forthcoming Fifth Generation (5G) network is claimed to tackle. Ultra-Reliable and Low Latency Communications (URLLC) are among the most demanding services that 5G network will support. Also referred to as mission-critical services, URLLC often requires group communications. The evolved Multimedia Broadcast and Multicast Services (eMBMS) architecture, currently specified by 3GPP to support group-based services in cellular networks, needs a revision to deliver future mission-critical services. In this paper, we analyze the performance of different machine-type multicast service (MtMS) scenarios and we compare three subgroup based approaches for multicast data delivery to MTC devices with limited channel bandwidth. Achieved simulation results provide useful guidelines for the design of multicasting schemes able to support delay-sensitive applications in 5G networks.

On the path to zero fatalities on the roadways, all vehicles have to periodically broadcast cooperative awareness messages (CAMs) in a timely and reliable manner, even in areas of high traffic density. The carrier senses multiple access with collision avoidance (CSMA/CA) scheme of IEEE 802.11, the de-facto standard for vehicular communications, is known to offer no reliability to broadcast packets that cannot be acknowledged, and to poorly perform at high network load due to collisions and interference. In this paper, an enhanced CSMA/CA protocol is analyzed for vehicular networks, which improves the CAM timeliness and reliability by leveraging full-duplex (FD) transceivers on board. FD devices can listen to the channel while transmitting, thus making collision detection viable. A FD vehicle can detect a CAM collision while sending, promptly abort the packet and retransmit it later. Results achieved through an analytical model under mathematically tractable assumptions, and through extensive system-level simulations in a complex urban environment, show the effectiveness of the protocol to cope with direct collisions, especially in high traffic areas, paving the way towards the realization of cooperative automated driving.

Modern vehicles are equipped with several interconnected sensors on board for monitoring and diagnosis purposes; their availability is a main driver for the development of novel applications in the smart vehicle domain. In this paper, we propose a Docker container-based platform as solution for implementing customized smart car applications. Through a proof-of-concept prototype-developed on a Raspberry Pi3 board-we show that a container-based virtualization approach is not only viable but also effective and flexible in the management of several parallel processes running on On Board Unit. More specifically, the platform can take priority-based decisions by handling multiple inputs, e.g., data from the CANbus based on the OBD II codes, video from the on-board webcam, and so on. Results are promising for the development of future in-vehicle virtualized platforms.

The efficient usage of multiple channels allocated for vehicular communications is deemed crucial to support the increasing spectrum demand of current and upcoming Intelligent Transportation Systems (ITS). In this context, an accurate modeling of adjacent channel interference (ACI) is needed to better understand its adverse effects on simultaneous communications on different channels. In this paper, we modeled ACI in the simulation framework Veins by strictly following the standard specifications in what concerns spectral emission masks. The model was validated in a set of experiments using off-the-shelf chipsets and a software defined radio. We then studied ACI effects at the physical and packet levels in multi-channel vehicular networks through extensive simulations. Our results clearly indicate that slightly larger delays and significantly lower reliability can be experienced when ACI is modeled. Insights are also provided about the usability of the devised ACI simulation model in future studies.

Name-based communication and in-network caching make Named Data Networking (NDN) a promising solution for content dissemination in Vehicular Ad hoc Networks (VANETs). So far, different NDN packet forwarding mechanisms have been proposed, but none of them have considered the idea of a prioritized traffic treatment based on vehicular content type. This is instead the focus of this paper, since priority-based content dissemination is a rather crucial objective in vehicular environments in order to meet the requirements of heterogeneous applications. Based on the NDN hierarchical namespace, we propose specific “name-prefixes” that identify globally understood priorities for vehicular data traffic. A prefix-based prioritized technique is then implemented on top of basic NDN forwarding algorithms. Simulation results show that the proposed enhancement succeeds in achieving differentiated traffic treatment and in reducing the latency of both high and low priority data.

Reliable and timely exchange of periodic beacons, a.k.a. cooperative awareness messages (CAMs), in the one-hop neighborhood is essential in vehicular networks to support cooperative driving applications. The problem is that broadcasted CAMs are neither acknowledged nor retransmitted in case of failure, e.g., due to channel errors or collisions, and this makes data transmission unreliable and without any delivery guarantee. In this paper, we propose in-band full-duplex communications to improve the reliability of vehicle-to-vehicle beacon exchanges. The FD capability to simultaneously transmit and receive on the same channel can be beneficially exploited by a vehicle to detect a collision while transmitting, and to promptly retransmit to recover from the packet failure. Achieved simulation results show that the proposed solution provides several improvements in terms of reliability and timeliness in CAMs delivery when compared against a naïve half-duplex broadcasting and a simple CAM repetition technique.

This paper investigates relay-based schemes in cellular systems, where multihop device-to-device (D2D) communications are exploited for content uploading toward the eNodeB. All user equipments (UEs) are sources of their own content and form a multihop D2D chain, with the head of the chain being in charge of uploading all the generated content to the eNodeB. By pooling the cellular radio resources assigned to the D2D chain and by using high-quality short-range radio links, the proposed cooperative content uploading scheme guarantees lower upload delays than in the traditional cellular mode operation. To model the D2D chain formation in a cell and to best characterize self-interested users concerned about their own payoff, a constrained coalition formation game is defined, where each UE is a player whose cost is identified as the content upload time. The solution of the game determines the stable feasible partition for the UEs in the cell. We demonstrate through simulations that with this solution the content uploading time is reduced by 52% with respect to the traditional cellular mode.

Recently, mobile multimedia services have represented an increasingly large source of revenue for the telecommunication industry. Subscribers are often interested in simultaneously receiving the same data flow and, hence, they fuel the growing demand for multicast multimedia services. Therefore, the design of efficient radio resource management strategies to jointly handle multicast and more traditional unicast traffic and to increase user satisfaction is of primary importance for the successful deployment of future mobile networks. This paper proposes an efficient radio resource management framework to handle unicast and multicast multi-layer video services. The proposed virtual unified group (VUG) approach makes use of a channel-aware subgrouping principle to provide fair throughput to both unicast and multicast users. The idea is to assign unicast subscribers to a virtual group, thus allowing them to compete for network resources on an equal footing with multicast users. Simulations highlight the benefits that VUG provides in a long term evolution network scenario, under different traffic load conditions, in terms of throughput and fairness in the distribution of resources to unicast and multicast users.

The Information-Centric Networking (ICN) paradigm for the future Internet is fundamentally different from the classic host-centric Internet Protocol (IP). By leveraging unique, persistent and location-independent content names, ICN provides native multicast support, content-based security, in-network caching, and easy data access, which can be especially useful in the Internet of Things (IoT). In this paper, the attention is on the design of an ICN framework tailored to the smart home domain, considered as a major representative of IoT scenarios. The proposed solution encompasses the definition of a flexible and expressive naming scheme that supports data/command exchanges and configuration/ management operations, and also fits the common service models in the smart home domain (i.e., push, pull, multi-party). Use cases are provided to shed light on the system behaviour and preliminarily assess its potential and performance.

This paper addresses the radio resource management of multicast transmissions of video streaming services in the emerging 5G-Satellite systems. A subgroup-based approach is used to split any multicast group into subgroups. This allows an effective exploitation of multi-user diversity according to the experienced channel conditions and the achievement of a high throughput level. The main drawback is the high computational cost usually related to the selection of the optimal subgroup configuration. In this paper, we propose a low-complexity subgroup-based algorithm that achieves performance close to optimum. Our solution is suitable for implementation in practical systems, such as Satellite-Long Term Evolution (S-LTE), since the computational cost does not depend on the multicast group size and the number of available resources. Through simulations conducted in different radio propagation and multicast group environments, the effectiveness of our proposed scheme is assessed.

This paper investigates on novel effective schemes based on Device-to-Device (D2D) communications for data relaying, to upload content from a set of cooperating User Equipments (UEs) acting as sources of the data towards a cellular base station (eNodeB). Enabling factors of the resulting cooperative data uploading able to improve the system performance are: (i) the differentiated channel quality experienced by UEs and (ii) the introduced possibility to pool together the allocated radio resources. A constrained coalition formation game is used for multi-hop D2D overlapping coalition formation, where the time needed to upload the content is the utility for the players. The proposed model directly considers the coverage constraints for the D2D links among the players. The proposed solution allows to determine the final cooperating network topology as a tree of overlapping coalitions. We demonstrate that the solution guarantees an average gain in the uploading time for the UEs up to a 23% with respect to non-cooperative content uploading methods.

Dense Networks (DenseNet) and Multi-Radio Access Technologies (Multi-RATs) are considered as key features of the emerging fifth generation (5G) wireless systems. A Multi- RAT DenseNet is characterized by a very dense deployment of low- power base stations (BSs) and by a multi-tier architecture consisting of heterogeneous radio access technologies. In this work, we propose an effective RAT selection algorithm that efficiently manages the RAT handover procedure by (i) choosing the most suitable RAT that guarantees high system and user performance, and (ii) reducing unnecessary handover events. In particular, the decision to trigger a handover is based on a new system parameter named Reference Base Station Efficiency (RBSE). This parameter takes into account metrics related to both the system and the user: the BS transmitted power, the BS traffic load and the users' spectral efficiency. We compare, by simulation, the proposed scheme with the standardized 3GPP policies. Results show that the proposed RAT selection scheme significantly reduces the number of handovers and the end-to- end delay while maintaining high system throughput and user spectral efficiency.

The rapid demand growth for group-oriented services mandates telco operators to efficiently manage the contemporary presence of the unicast services and the emerging multicast applications. We propose a novel radio resource management approach for providing fair throughput to unicast and multicast users in a broadband wireless network. The idea is to assign unicast subscribers to a virtual group in order to compete on an equal footing with multicast users for network resource distribution. We also revisit the traditional fairness indexes in order to capture the fairness in the degree of user satisfaction for unicast and multicast users. Simulations highlight the effectiveness of the virtual group strategy in terms of achieved fairness in several scenarios and under different traffic loads.

Leveraging the concept of controlled node mobility in this paper we develop an algorithm for tracking and controlling proximity malware propagation in Wireless Sensor Networks (WSN). Our proposal aims at: (i) notifying the nodes of malwarepropagation, (ii) leading a flying robot along a path in the WSNthat guarantees the minimum recovery time to (iii) heal the infected nodes. We formulate the targeted curing problem as a binary integer problem and determine the optimal solution by a central solver. We use the analytical result as a benchmark to evaluate the recovery time of the proposed solution. The achieved results show a satisfactory performance in terms of tracking the presence of an ongoing epidemic and healing the nodes.

The research on the Internet of Things (IoT) has made rapid strides towards the definition of a global network of interconnected objects. Some IETF Working Groups are giving major contributions in this direction by standardizing an IPv6-based framework for resource-constrained nodes. Although this solution handles different constrained networks' devices, it does not explicitly manage the integration with a key IoT enabler: the RFID (Radio Frequency Identification) technology. In this paper, we propose a CoAP-compliant solution where RFID tags are directly accessible via a reader that acts as a proxy. The RFID tags, behaving as virtual CoAP servers, are included in the IoT realm. Key design aspects are addressed such as tag addressing, service and resource discovery, and mapping of CoAP methods onto RFID commands. Finally, the performance of the proposed solution is evaluated in order to provide useful indications for future deployments.

Named Data Networking (NDN) is a new architecture for the Future Internet that supports efficient data delivery by directly using content names instead of IP addresses. This content-centric approach can be especially useful for IoT applications, where everyday objects embedding wirelessly connected constrained devices should be accessed, by both other machines and users. In such a context, we focus on the smart home domain and propose a framework called eDomus that (i) leverages functionalities by a popular social network, i.e., Facebook, to allow a user to remotely interact with the home network and (ii) is augmented with NDN concepts to properly monitor the domestic environment. In this paper, we present our framework and our preliminary prototype, by also providing some hints on future work.

Content-Centric Networking (CCN) provides a complete communication framework for data retrieval and dissemination. It leverages innovative naming, security schemes and novel routing strategies, augmented with caching at intermediate nodes. Content requests are forwarded towards the source(s) by direct use of content names (instead of IP addresses), matching the layout of the Wireless Sensor Network. Despite its potential CCN can not be directly applied to wireless environments, specifically resource-constrained sensor nodes. In this paper, a two-tier CCN architecture is proposed to manage the heterogeneity of involved devices (remote server, sink, sensor nodes). CCN is enhanced with some changes to the forwarding strategies to improve data collection.

Multiple channels have been allocated in the 5 GHz spectrum for vehicular communications in USA and in Europe. Due to the limited spectrum, simultaneous communications may occur over nearby channels and be affected by adjacent channel interference (ACI). To protect safety messages delivered on the control channel (CCH), the most likely approach is to prevent the use of adjacent channels with the consequence of spectrum resources wasting. In this paper we identify temporarily stopped vehicles (e.g., at the gas station for refuelling) as users that are potentially allowed to transmit on a channel that is adjacent to the CCH. A simulation study has been conducted to evaluate the viability of our proposal. Achieved results show that the two conflicting objectives of improving spectrum utilization and not penalizing safety messages can be successfully met, provided that the transmission power on the adjacent channel is adequately tuned and the stopped vehicle is at a sufficient distance from the vehicle that is using the CCH.

Long Term Evolution (LTE) is considered the most promising cellular system able to support the growing demand of multicast services (e.g., IPTV, video streaming) over mobile terminals. The design of effective strategies for the management of these applications is still an open issue, especially in scenarios where several multicast streams are simultaneously transmitted in a cell. In this paper we propose different resource allocation policies for the delivery of multicast scalable video flows. Such policies efficiently exploit the multi-user diversity and the frequency selectivity in order to match the requirements of both users and providers. The performance of the proposed strategies is analyzed through simulations by evaluating different cell deployment and user load environments and by focusing on spectral efficiency, throughput, fairness, and amount of resources needed for multicast service delivery. The last parameter is important in practical scenarios where multicast services share the available resources with other flows, e.g., unicast services.

Content-centric is an emerging networking paradigm conceived for the future Internet. Data retrieval and distribution are based on content names instead of host addresses. In this paper we propose a content-centric architecture for energy-efficient multihop communications in a wireless mesh network and compare its performances against a legacy IP-based approach.

Long Term Evolution (LTE) is the emerging 4G wireless technology developed to provide high quality services in mobile environments. It is foreseen that multimedia services and mobile TV will assume an important role for the LTE proliferation in mobile market. However, several issues are still open and meaningful improvements have to be introduced for managing physical resources when group-oriented services should be supplied. To this end, we propose a Frequency Domain Packet Scheduling (FDPS) algorithm for efficient radio resource management of Multimedia Broadcast/Multicast Services (MBMS) in LTE networks. The proposed scheduler exploits an optimization process to organize multicast subscribers in subgroups according to channel quality feedbacks provided by users. Optimization is driven by the aim of minimizing the “user dissatisfaction” with a consequent improvement in the network capacity. The effectiveness of the proposed scheduling algorithm is evaluated through simulation; obtained results demonstrate significant improvement in the multicast traffic performance.

The IEEE 802.11p/WAVE family of standards has been designed to provide multi-channel communications for vehicular use. Despite the increasing interest on vehicular networking, further efforts are still required to improve realism of simulations, in order to account for the latest standards and for physical-related phenomena. In this paper, we aim at overhauling the physical and MAC layers of ns-2 to include the last recommendations on frequency allocation, the effects of channel impairments (fading, obstructions, in-channel and adjacent channel interference), an enhanced receiver design, and the WAVE multi-channel related effects.

The 802.11p standard has been recently ratified to provide Wireless Access in Vehicular Environments (WAVE). According to the WAVE alternating channel access scheme, singleradio devices must tune into a common frequency during the control channel (CCH) interval, to exchange safety and control packets, and regularly (every 50 ms) switch to one of the available service channels (SCHs) for non-safety data exchange. In order to improve non-safety data delivery performance, the extended access mode has been recently proposed by the standardization groups in order to allow vehicles to stay tuned on the SCH as long as they need before switching on the CCH. In this paper we identify some drive-thru scenarios as possible use cases for the extended access scheme, and propose some enhancements to this scheme with the aim of improving channel utilization and non-safety applications performance without penalizing the delivery of safety messages on the CCH.

This paper focuses on the design of radio resource management policies for multicast service delivery in WiMAX networks. With the purpose of finding an alternative solution to the conventional multicast scheme that is conservative towards resource utilization, we propose to use a subgroup-based link adaptation technique that dynamically chooses the modulation and coding schemes based on the perceived channel conditions in each subgroup of multicast receivers. The main idea is to split the multicast destinations into different subgroups depending on the perceived channel quality, and to apply subgroup-based adaptive modulation and coding for a more efficient spectrum exploitation. The performance of different solutions for the subgroups formation will be analyzed and their effectiveness evaluated through simulations to show how the network can take advantage from the proposed subgrouping approach.

Wireless cooperation is emerging as a viable approach for next generation networks to offer important benefits in terms of content transfer delay, data rate, energy consumption, and cell capacity. One of the possible applications of a wireless user cooperation paradigm is represented by the provision of content sharing services. Data is seeded into a cooperative cluster through cellular links while short-range links are used to distribute data to all the interested nodes. Besides showing the beneficial effects of cooperation, this paper focuses on the best way to seed information into such a cluster of nodes and on a solution offering benefits in terms of either the time or the energy consumption for the service. Starting from static environments, the potentialities offered by an ad-hoc conceived Genetic Algorithm (GA) are shown. The analysis is then extended to the more realistic nomadic environments with low speed pedestrian mobility for the nodes.

Despite the massive research effort in the design of reliable techniques for dissemination of information in vehicular ad hoc networks, only a few works have investigated performances when considering the multichannel operation of the recently published IEEE 802.11p/WAVE standard. Moreover, most of the works focused on highway scenarios, basically due to the lack of scalable models simultaneously representing fading and obstructions, and providing a solution for realistic simulations in urban scenarios. In this paper, by exploiting a propagation model accounting for radio obstructions recently proposed in literature, the performance of IEEE 802.11p/WAVE is studied in an urban scenario where providers are mobile nodes. The achieved results show that the effectiveness of mobile providers is heavily affected by the urban obstructions (e.g., buildings), in terms of both coverage and service quality.

Broadcasting of data and control packets is expected to be crucial in vehicular environments. Both safety-related and non-safety applications rely on broadcasting for the exchange of data or status and advertisement messages. According to the specifications of the IEEE 802.11p/WAVE (Wireless Access in Vehicular Environments) standard, vehicles tune into a common frequency during the control channel (CCH) interval, where most of the broadcasting traffic is expected to be delivered. The rest of the time, vehicles switch to one of the available service channels (SCHs) for non-safety related data exchange. Although the WAVE channel switching could heavily affect the network performance, it has not been widely investigated in the literature. In this paper, an analytical model is designed for characterizing the losses of broadcast packets by explicitly accounting for the WAVE channel switching. Loss probabilities have been derived as a function of contention window size, number of vehicles and channel errors.

In this paper, a delay tolerant approach for traffic management in LTE over satellite link is presented. Due to the long propagation delays and frequent disruptions, mobile satellite communications pose many challenges, especially to the transport layer when the TCP protocol is used. We design and evaluate the performance of a transport protocol solution based on the DTN architecture in the satellite-LTE system. Our proposal, named Tiny Bundle Layer, acts as an overlay on top of different versions of TCP in order to overcome the satellite link impairments.

This paper introduces a user cooperation technique thought to support content sharing services in wireless environments. WLAN inter-device data exchange is effectively exploited, combined with network coding techniques. Specifically, the content of interest is seeded into the WLAN user group through cellular-enabled devices, while short-range links are used to cooperatively distribute data to all the interested users. The focus is on scenarios where nodes in the same network area are not all interested in the same content, they rather form different cooperative groups. Beneficial effects of intra-group cooperation have already been demonstrated in the past; differently, this research focuses on inter-group cooperation. Objective of this paper is the investigation of any obtainable benefit (either in terms of energy consumption, service latency, or probability of successful service distribution) from such a cooperative attitude of different groups.

A wide variety of applications aiming to improve traffic efficiency or to provide information/entertainment to passengers in vehicles are intended to be delivered in Vehicular Ad hoc Networks in the near future. Most of these applications require vehicles to access a remote network. However, due to the high costs for deploying and maintaining an ubiquitous roadside infrastructure, just a few stationary Road-side Units (RSUs) are expected to be installed, which provide discontinuous and shortlived network connections. In this paper, the feasibility of vehicle-to-roadside communications is investigated when considering features and capabilities of the 802.11p/WAVE standard for vehicular environments. We expect that, by complementing advertisement repetitions from RSUs with smart piggybacking of some RSU parameters in the beacons transmitted by all vehicles (On board Units, OBUs), the RSU-awareness can be improved and RSU-OBU connection lifetimes can be lengthened.

In this paper, the current trends and the most recent advancements in the utilization of aerospace communications for emergency rescue applications will be discussed, with a special focus on the integration of the aerospace segment with terrestrial backbones and ad hoc terrestrial networks for both data connections and assisted localization (information about position is essential in emergency relief).

A wide variety of applications aimed to improve road safety and traffic efficiency or to provide comfort/entertainment to passengers in vehicles are intended to be delivered in VANETs (Vehicular Ad hoc Networks) in the near future. Most of these applications require vehicles to access a remote network. However, due to the high costs needed for deploying and maintaining an ubiquitous roadside infrastructure, just a few stationary access points are expected to be installed, which provide partial network coverage; hence multihop communications must be enforced in order to provide remote connectivity to vehicles on the road. The upcoming IEEE 802.11p/WAVE (Wireless Access for Vehicular Environment) standard relies on a multi-channel architecture to deliver both safety and non-safety applications to vehicles, but it does not explicitly support multihop data delivery. In this paper some main design issues are investigated which deal with the provision of multihop communications in 802.11p/WAVE networks. A set of forwarding schemes compliant to the draft standard is specified and analyzed, which aim to improve data delivery and delay performances, by reducing the overhead incurred for relaying packets.

Abstract Multicast service delivery can be easily guaranteed to users in disadvantaged areas by effectively integrating HAPs (High Altitude Platforms) into the terrestrial cellular system. HAPs are meant to be as unmanned aerial vehicles, airships or aircrafts, which remain relatively stationary in the stratosphere at short distance from Earth compared to satellites. In the scientific literature, there is evidence of the effectiveness of a UMTS (Universal Mobile Telecommunications Systems) system augmented by the presence of HAPs, which are equipped with UMTS payloads and play the role of additional base stations. This integrated terrestrial‐space platform intrinsically fits the exigencies of rural and emergency scenarios, which are characterized by network resource scarcity, due to either geographical reasons (such as in rural areas) or to temporary resource over‐utilization/reduction (due to emergency status). In this paper, the focus is on the delivery of Multimedia Broadcast/Multicast Services (MBMS) in the reference integrated architecture. Main objectives are designing resource allocation policies to manage multicast groups between space and terrestrial coverages, and analysing their feasibility and performances in terms of offered grade of service. Copyright © 2008 John Wiley & Sons, Ltd.

The provision of Quality of Service (QoS) is one of the primary requirements for IEEE 802.16/WiMAX to become a reference technology for multimedia service delivery. This paper reports on the design and analysis of some channel- aware scheduling algorithms for downlink traffic delivery in a fixed point-to-multipoint WiMAX network. In particular, compensation-based and greedy approaches are compared according to their ability to provide QoS and fairness to traffic flows when not working in ideal channel conditions. Simulations highlight that the greedy philosophy fails to provide service differentiation, especially when users perceive heterogeneous channel conditions.

Broadcast/multicast is a service of paramount importance for wireless users, which poses several serious challenges. Many multicast applications, such as multicasting streaming or alarm signalling, require a reliable and efficient medium access control (MAC) layer. However, the current IEEE 802.11 protocol does not offer any MAC layer recovery mechanisms on unsuccessfully delivered broadcast/multicast frames. Consequently, lost frames cannot be detected, hence retransmitted, and this may deteriorate the quality of broadcast/multicast services. To address these issues, we propose a reliable multicast MAC protocol for wireless multihop networks, which aims at providing high packet delivery ratio as well as low control overhead and multicast delivery delay.

Multimedia broadcast multicast services (MBMS), introduced by Third Generation Partnership Project (3GPP) in universal mobile telecommunications system (UMTS) release 6 specification, have the aim to support downlink streaming and game services to groups of users. MBMS can supply users with resources in two different modalities: point-to-point (PtP) and point-to-multipoint (PtM). The power consumed by the network is an important topic to discuss when considering the presence of MBMS services. The UMTS system is, in fact, interference- limited; thus, the power available to Node B is limited and it must be enough to serve any user under its coverage. Therefore, the choice of the most efficient transport channel in terms of power consumption is a key aspect for the MBMS, since a wrong transport channel selection for the transmission of the MBMS data could adversely affect the overall capacity of the system. In this paper we search for the most efficient transport channel to convey MBMS data, by comparing the performance of the high speed downlink shared channel (HS-DSCH), the dedicated channel (DCH), and the forward access channel (FACH), for given transmission power levels and cell coverage size.

Focus of the present paper is the integration between high altitude platforms (HAPs) and terrestrial UMTS system to support multimedia broadcast/multicast services. HAPs are characterised by a wide coverage area, which makes them a very attractive solution to support broadcast and multicast applications, while increasing both resource capacity and grade of services. In the depicted scenario, we propose to enhance the system efficiency by envisaging a novel radio resource management (RRM) protocol based on the evaluation of the power consumption relevant to users belonging to each multicast group. We demonstrate that the use of the proposed RRM policy, coupled to a wise selection of transport channels, leads to the effective management of multiple multicast groups.

WAVE (W band Analysis and VErification) is a project funded by the Italian Space Agency (ASI) with the aim to design and deploy different missions for scientific experimental use of the W band channel in satellite data communications. The second phase (A2) of the Project is currently in progress. This paper summarises the main scientific results early achieved in the WAVE A2 Project on the analysis assessment of W band GEO and LEO satellite missions.

Mobile devices provided with cellular and short-range radio network interface cards offer the user potentials for new communication paradigms based on a cooperative behavior. The idea is that devices in close proximity exchange, through available short-range links, complementary shares of information downloaded from the cellular connections. Results in the literature have proven equal benefits for all partners in terms of energy consumption, achieved data rate, and transfer time, under homogeneous conditions. Notwithstanding, there could be heterogeneous cooperative scenarios in which gains are not perceived, unless novel smart policies for the content splitting among cooperating entities are implemented. In this paper we design a novel cooperation strategy based on a multi-criteria optimization algorithm for the bargaining of the content fraction each cooperating unit shall download according to the predicted cellular throughput. It will be shown that it is able to always match the expectations of the cooperating partners.

This paper introduces a novel seamless handoff approach for DVB-H networks aimed at reducing the user terminal power consumption and at making the handoff algorithm be driven by the quality of the user received signal. This implies the substitution of standard RSSI-based procedures with a method based on the Modulation Error Rate (MER) monitoring. The additional use of an underlying cellular network, for DVB-H related data delivering, allows to achieve additional advantages: a superior power saving and a faster handoff execution. Obtained results suggest that the DVB-H handoff protocol design is an issue, which definitely deserves further investigation in the view of making DVB-H an effective solution for delivering broadcast content to mobile users.

The strong user need for receiving multimedia content while on the move opens up new challenges in future hybrid wireless communication scenarios. Delivering broadcast and multicast multimedia services through existing cellular networks is surely one of the toughest issues to investigate. The wide coverage area of High Altitude Platforms (HAPs) makes them a very attractive solution to deliver multicast/broadcast applications to a large number of sparse users. The authors examine the implications arising from the integration of UMTS and HAP systems to provide Multimedia Broadcast and Multicast Services (MBMS). In this reference scenario, two radio resource management policies are compared in terms of overall offered Grade of Service (GoS). By a thorough simulation investigation, the performance trade-off between a "User Number oriented" vs. a "User Distribution oriented" solution is evaluated. The different conditions under which one approach outperforms the other are investigated, and the degree of achieved performance augmentation is highlighted.

Key issues in the design of soft handoff policies for DVB-H systems are energy saving and constant monitoring of the received signal quality. With this idea in mind, a novel algorithm is proposed in this paper with the aim of reducing the frequency of handoff-related measurements in DVB-H systems, thus enabling manifest power saving in portable terminals than in the case of standard RSSI-based procedure. The objective is accomplished by making handoff algorithm be driven by the quality of the signal received by the user, constantly monitored through techniques of MER (Modulation Error Rate) measurement and estimation. The performing behavior of the proposed mechanism, assessed through a comprehensive evaluation campaign, allows us being confident that this is a direction to consider for future research activities in the field of effective DVB-H handoff protocols design.

In this paper we provide a general and repeatable experimental evaluation campaign of location algorithms based on RSSI measures for active RFID systems. We start from the well-known LANDMARC approach and conduct a thorough investigation aiming at evaluating its actual potentials and limitations under different environmental conditions. For the sake of completeness, we compare its behavior with the one of a further technique, named RSSI spatial interpolation (RSI), which is taken as a representative of a wider family of solutions which also LANDMARC belongs to. Experimental results show that by even introducing some modifications, still both algorithms get poor performance in indoor scenarios; location errors lower than 2m are only attainable in limited size outdoor environments in 90% of the experiments.

The IEEE 802.16 standard has been promoted by the WiMAX (Worldwide Interoperability for Microwave Access) forum as a leading wireless broadband access technology. The packet scheduling mechanism represents the core of WiMAX QoS architecture; however, each vendor needs to design its own algorithm to offer effective quality provisioning to the end user. This paper reports on the design and analysis of a channel-aware WF2Q+ based scheduling algorithm for downlink traffic delivery in a point-to-multipoint WiMAX network. A technique for compensation of channel errors is proposed to preserve QoS and fairness of the scheduling algorithm when working under non-ideal channel conditions. Simulation analysis confirms the effectiveness of the compensation mechanism under different channel conditions, network load, and traffic characteristics.

The focus of this paper is on the integration of High Altitude Platforms (HAPS) into a terrestrial UMTS system to effectively support MBMS applications. Its main objective is the efficient allocation of transmission resources to multicast traffic streams (by suitably selecting terrestrial and/or HAP channels) while still preserving the desired Grade of Service of background unicast traffic. Specifically, we compare two different approaches to the Radio Resource Management (RRM) in the depicted scenario: the first one takes into account the Number of users in each multicast group to drive the RRM policies; while the second one bases the RRM behavior on the Distribution of users belonging to each multicast group. By conducting a thorough investigation, the performance trade-off between "User Number oriented" vs. "User Distribution oriented" solutions is evaluated. The different conditions under which one approach outperforms the other are investigated and the degree of performance augmentation is always highlighted.

In this paper we present a novel multi-criteria network selection algorithm for always best connected service provisioning. It relies on a suitably defined cost function, which at the same time takes into account metrics reflecting both objective, i.e. network related, and subjective, i.e. user preference related, conditions. Point of strength of our proposal is the implementation of the selection algorithm at a middleware layer; this hiding both network cost computation and 4G scenario complexity from user and application layers. The good performance observed is mainly due to the possibility of associating a weight to each cost parameter that is dynamically adapted to user preferences and profile not only on a per-session basis but also within the same session

To provide QoS guarantees to a variety of traffic types is becoming a key feature for the success of wireless LANs. In this paper, we contribute to this issue by proposing a framework under which the nodes in an IEEE 802.11e ad hoc network may cooperate to provide the user with the desired QoS level

This paper contributes to the issue of QoS differentiation in wireless ad hoc networks. The focus is on the IEEE 802.11e MAC protocol that we propose to enhance by introducing a mechanism to "dynamically" assign priorities to traffic. Priorities are hop-by-hop assigned according to network resource availability and load in order to satisfy throughput requirements of each class of traffic

In wireless LANs, QoS provisioning and multimedia traffic support are critical elements for the successful deployment of such networks. In this paper, we propose a dynamic mechanism to adapt data rate and priority of multimedia wireless stations equipped with IEEE 802.11e network cards. We show how the introduced dynamicity is able to improve performance of the enhanced distributed channel access (EDCA) of IEEE 802.11e networks.

In this paper a novel concept of "situation and location" based quality of service (QoS) control for next generation hybrid wireless system is investigated. A brief overview of the evolutionary paths involving the QoS concept is given and the new vision of I-centric telecommunications scenario is addressed. In such a context, a definition of a situation and location aware mechanism for QoS management and resource allocation is proposed by approaching the issue at a middleware layer in such a way as to make the underlying heterogeneous system completely transparent to the mobile user roaming across its segments.

Multi-layered networks exploiting HAP and satellite segments are becoming a very attractive solution to deploy global telecommunication infrastructures. In fact, they can help in offering users ubiquitous access to multimedia information in an efficient and cost-effective way. In this paper a multi-layered infrastructure is presented aiming at efficiently allocating bandwidth among different user typologies. Two different scenarios are considered for DVB-RCS service delivery. A one-layer system, with the satellite coverage stratum only, and a two-layer one, with an integrated HAP-satellite coverage layer. A simulation campaign is conducted in order to assess the performance of both scenarios and to compare their performance. This study is, therefore, intended as a research contribution to the understanding of the actual usefulness of introducing a HAP stratum into terrestrial-satellite hybrid wireless systems

In the present paper a modular mechanism for QoS management over the return channel of DVB-RCS satellite platforms is proposed. Main aim of the study is to contribute to the standardization research efforts towards the definition of effective QoS management policies over DVB-RCS return channels. By exploiting the proposed solutions a DVB-RCS satellite system is able to keep the throughput always at high levels while satisfying each service class negotiated QoS. Resource wasting is reduced and the performance of low priority traffics is always guaranteed through a "wasted resource reuse" mechanism implemented into the terminal. Proposed solutions are tested within a realistic platform through appropriate simulation campaigns that confirm the expected good performance.

This work presents an enhancement of the hierarchical mobile IPv6 protocol, based on a new concept of "distribution areas" and the assignment of multiple LCoAs. It contributes to low latency and packet loss during intradomain handover events. The size and position of the distribution areas are dynamically adjusted depending on traffic load measurements and terminal/user velocity estimation. Simulation results show that it is possible to trade off packet loss and introduced overhead.

In this paper the authors' attention is on the specification of a middleware functionality for dynamic QoS control in multimedia cellular environments, such as UMTS. The functionality implements a soft QoS paradigm, at the same time optimising the perceptual QoS provided to the end user according to his/her needs. It will be shown that by exploiting suitable performance indexes and resource redistribution algorithms both an acceptable grade of service and a good degree of user satisfaction can be achieved, without an excessive increase in the network-signalling load.

This paper aims at contributing to the dimensioning of the signalling bandwidth of a broadband geo-satellite system for multimedia communications. Signalling channels are used by the satellite terminals to set up connections and ask for on-demand resource assignment. A smart dimensioning of the satellite bandwidth plays a key role in the fulfillment of the service quality required by multimedia traffic and the effective exploitation of the satellite spectrum. We accomplish this task by designing a statistical centralised CAC accorded with an intelligent scheduling of the resource requests on board the satellite. The proposed traffic and resource management techniques have been tested over a simulation platform for the EuroSkyWay satellite system.

In this paper we propose and compare different techniques used by the satellite user terminals to randomly access signaling channels used for connection set-up. The reference scenario is represented by EuroSkyWay [G. Losquadro, 1996], a multimedia geostationary satellite platform conceived for providing personal communications.

This paper proposes a heuristic for re-computing the forwarding zone of route request packets for the location-aided routing (LAR) protocol in ad hoc wireless networks. We evaluate the influence of a "multi-step" resizing of the request zone on the LAR protocol performance, and make comparisons with other routing protocols (LAR scheme 1, LAR scheme 2, and promiscuous-dynamic source routing). Simulation results show that an accurate choice of the request zone size and of the number of steps for the resizing is successful in reducing the control overhead and increasing the throughput.

This paper presents the analysis of some MAC protocols for multimedia applications in wireless ATM networks. The novelty of the approach is the delivery of multimedia applications over separate bearers over the radio interface while maintaining the original synchronisation degree. The presented techniques are able to guarantee low jitter, high degree of synchronization among different streams of the same user application, as well as to effectively exploit the limited radio spectrum of a wireless air interface.

Many recent researches have been conducted on the topic of multimedia applications management in integrated terrestrial-satellite systems with W-CDMA air interfaces. Among the many research issues, the design of suitable radio resource management techniques for soft-QoS guarantees to the user applications surely deserves a particular attention. This paper tries to contribute to this issue by reporting the lessons learned during a performance assessment study on a multi-tier UMTS system simulation platform. It shows that the achievement of good performance is strongly related to the right choice of call management algorithms, which take into account both the nature of the delivered traffic at each coverage level and the effects of the presence of the soft-handoff.

This paper proposes and analyses an architecture providing IP quality of service in integrated terrestrial-satellite networks. The IP Integrated Services framework is used to reserve resources on the satellite path and is combined with Differentiated Services in the terrestrial core network. A seamless integration is achieved by means of a gateway station that acts as interworking unit between terrestrial and satellite segments. The main focus is on the best mapping of integrated service traffic classes over satellite bearer connections.

This paper analyses the performances of two types of CAC algorithms proposed for deciding the admission of new connections in a geostationary satellite system. Both algorithms are specifically designed for high latency networks as they are characterized by low processing time on board, simple parameters, and real-time decisions. Tests are performed on the multimedia satellite platform of EuroSkyWay and aim at assessing the robustness of the CAC algorithms in guaranteeing the target quality to heterogeneous applications and in exploiting effectively the satellite bandwidth.

A new scheme for the management of real-time traffic over high-latency broadband satellite networks is described. Early studies on this topic have been reported by Iera, Molinaro and Marano (see IEEE J. Select Areas Commun.,, vol.18, p.2393-2403, 2000), with reference to an integrated terrestrial-satellite platform. In this paper, further enhancement is introduced into the traffic management scheme with a view to both the reduction of intrinsic impairments caused by the adverse operational environment and the achievement of better performance levels and QoS guarantees. A real-time traffic handling strategy, including distributed connection admission control (CAC) and traffic resource management (TRM) schemes, is harmonized with an in-band signaling technique for burst-based bandwidth request and with an effective policy for the allocation of radio resources. Furthermore, the impact of traffic reshaping at the satellite terminal on the CAC-TRM technique is tested. Added features reduce the adverse effects of the long propagation delay across the satellite link and show outstanding effectiveness in improving CAC-TRM performance and network resource efficiency, while matching service quality requirements. The main reason for the improved performance of the overall management scheme is the adaptability to different traffic profiles conveyed over satellite links.

An attractive challenge in the global communications scenario is the effective transmission of real-time bursty traffic over integrated terrestrial-satellite links. In this paper, the study focuses on the cited issue. In early studies we proposed a solution based on a connection admission control (CAC) scheme, coupled with a traffic resource management (TRM) functionality onboard. In the present work, the traffic handling strategy is complemented with a re-shaping module in the satellite terminal. The additional functionality shows outstanding effectiveness in improving CAC-TRM performance, especially when the long propagation delay across the satellite link prevents the CAC itself to guarantee the target QoS to certain types of traffic. By adopting an "intelligent" shaping at the satellite terminal the full effectiveness in managing system resources and in guaranteeing QoS is recovered, under a wide range of loading conditions and offered traffic profiles. The resulting policy is adaptable, in the sense that it can be dynamically adapted to the traffic profile.

This paper focuses on the analysis of two classes of TDMA-based MAC algorithms for wireless-ATM networks: the urgency-based class, scheduling the bandwidth requests on the basis of their urgency, and the buffer-based class, relying on the estimation of the queue length in the mobile terminals. The main features of the proposed urgency-based algorithms are: contention-based DAMA access, dynamic adaptation of reservation bandwidth, use of piggybacking and control mini-slots to handle real-time VBR traffic, and a scheduling mechanism based on the expiry time of the buffered cells. These aspects contribute to the better performance of urgency-based algorithms in handling heterogeneous traffic when compared to the buffer-based ones.

This paper describes a multiple access protocol, which answers the need for an efficient handling of the traffic coming from a wide range of broadband applications over geo-synchronous satellite air-interfaces. We propose a hybrid medium access control scheme, which combines both random access and demand assignment multiple access policies. It is coupled with a connection admission control algorithm, exploiting the advantages of statistical multiplexing. Dynamic management of the frame header allows minimizing the signaling overhead and maximizing the effectiveness of the reservation procedure.

In this paper we propose the use of an in-band signalling technique coupled with a distributed connection admission control and traffic resource management scheme, to combat the effects of high-latency in geostationary satellite systems. In-band request signalling is introduced to manage burst-based bandwidth demand from satellite terminals transmitting real-time variable bit rate traffic. Performance evaluation has shown the effectiveness of this technique in guaranteeing the service quality negotiated at connection set-up between the user and the network.

In this paper, a novel strategy for handling ATM connections of different natures, traffic profile, and QoS requirements in enhanced satellite systems is proposed. The conducted research starts from early studies on resource management in integrated terrestrial-satellite environments and focuses on a combined connection admission control/traffic resource management strategy for QoS provisioning to both real-time and non-real-time constant and variable bit rate sources. The resulting connection handling policy is dynamic, and effectively exploits the system bandwidth through the statistical multiplexing of traffic sources and a preemptive policy over the satellite air interface. The proposed strategy is suited for a generic integrated ATM-satellite system, although its effectiveness has been assessed on a multimedia satellite platform, based on the Ka-band payload and on-board processing.

Multi-tier cellular systems can answer the rising need for high transmission capacity and provide solutions for supporting heterogeneous (narrow-band and broad-band) traffic. The system analysed in this paper consists of a GEO satellite spot covering micro and macro-cellular layers to provide global user reachability and additional bandwidth. Enhanced traffic and resource management algorithms are proposed to effectively exploit the potential advantages of the multi-tier solution. The basic feature is the allocation of each connection to the most convenient hierarchical layer, according to the user mobility profile (fast/slow) and traffic nature. The system is loaded by heterogeneous traffic sources with different requirements in terms of bandwidth on the two radio link directions (symmetric and asymmetric data), delivery requirements and integrity needs. Algorithms are compared under different external conditions and their performance is assessed in terms of new call blocking and handoff dropping probabilities.

In this paper new techniques are proposed for the handling of multimedia traffic in a hierarchical multi-tier system involving microcellular, macrocellular and satellite coverage. In this environment, efficient channel assignment and hand-off management techniques become critical issues to fully exploit the benefits of the multi-layered architecture. The traffic flow control between layers has to maximise the system capacity without degrading the traffic QoS. This task is particularly hard when in the presence of multimedia calls, which ask for large amount of bandwidth and are characterised by the combination of traffic of different nature. The proposed algorithms differ from the traditional ones as they adopt a multi-bearer transport approach to carry multimedia traffic over the air-interface, coupled with suitable strategies for the allocation of each traffic component at the best layer. This leads to better resource utilisation and multimedia QoS guarantees, while minimising new call blocking and hand-off failure probabilities.

The work presented in this paper aims at contributing to the design of traffic and resource management techniques suited for integrated ATM-satellite systems with composite traffic load. The proposed techniques exploit sources statistical multiplexing and pre-emption based dynamic resource assignment. The features making the techniques suitable for ATM-satellite environments are: very low on-board processing, easy algorithm tuneability, statistical multiplexing of VBR sources, good exploitation of satellite bandwidth, and QoS provisioning to real-time and non-real-time traffic sources. The effectiveness of the proposed strategies is assessed on the Euro-SkyWay multimedia satellite platform.

Different dynamic channel allocation (DCA) strategies based on local signal strength measures are evaluated in terms of the degree of frequency reuse they can afford. Fixed and dynamic channel allocation schemes are compared by using a simulation model, which overcomes the limitations of models traditionally used in literature. Valuable results show the superiority of DCA schemes in various scenarios characterized by different patterns of traffic and propagation conditions.

User speed estimation can be exploited to improve the teletraffic performance in a mobile radio environment with multi-tier coverage. Many algorithms exploit the dwell time estimation to classify the users' speed and assign them to the right hierarchical layer. Most of them assume a constant user speed for the entire call. Thus, they loose their effectiveness in environments in which the mobile speed changes during the call. A new effective scheme for channel allocation and handoff management, based on the concept of bonus time, is proposed in this paper. Sophisticated simulative tools showed that the new scheme performs better, compared to the traditional ones, under a wide range of load distributions and vehicle traffic conditions both in urban and sub-urban environments.

To accomplish the task of providing a wireless access to the fixed network in a UMTS scenario, DECT is also expected to support multimedia traffic requiring multi-slot allocation. To this aim, a modified channel access algorithm, based on a slot-segmentation technique is adopted and combined with a priority-based management of the access requests. This paper illustrates the interesting effects of these enhancements in traditional DECT. The results of a performance evaluation activity in a multi-cell environment with wide-band and narrow-band traffic is reported. Achieved improvements are manifest in terms of both throughput and guaranteed QoS to each type of traffic.

In microcellular systems, cell overlapping can be effectively adopted to improve the teletraffic performance of the mobile terminal population. Anyway, the greatest advantages are mainly achievable by those users, located within an overlapping region, which can exploit the opportunity of receiving acceptable radio signals from more base stations. Effective resource assignment policies are thus necessary to make users located far from overlapping regions benefit from this feature as well. To this aim, a dynamic channel allocation scheme, based on the concepts of reserve channels and protection threshold, is proposed in this paper. A detailed description is given and, by means of analytical tools, it is shown that better performance compared to traditional schemes are attainable under a wide range of load distribution.

It is not an easy task in the UMTS environment to effectively design the transport and the management of traffic belonging to multimedia teleservices, due to the difficult communication requirements of such applications. It is proposed to contemporary use at the "transport" layer of the system several bearers, one for each traffic component of the multimedia service. Furthermore, a two-level (static and dynamic) priority mechanism is to be adopted by the higher protocol levels of the UMTS for the adaptation of call set-up, channel access, and admission control procedures to the nature of the multimedia services and to optimise the sharing of radio channel resources and the management of the reservation buffer. The results achieved demonstrate that the proposed mechanism shows a good performance especially during periods in which the system traffic load is high and reacts well to the worsening of the multimedia service quality, both in terms of information loss and synchronisation of its traffic components.

Wireless-PCS systems, through the introduction of new conception control functions, aim to respond to the user expectation of high performing services and the need for flexibility in the management of disparate categories of multimedia and multi-requirement applications supported by the networks. This paper contributes to the ongoing research work in this scenario by describing some proposals for the handling of multimedia teleservices both at the transport and control level, across the wired and wireless sides of an ATM-based wireless PCS system. Admission control on both sides, mobility management in the fixed side and resource allocation renegotiation are topics on which the study focuses.