Age of information (AoI) is a metric that quantifies the timeliness of information delivered in a system, which is an emerging requirement for a variety of services like autonomous driving, industrial internet of things, as well as the likes of mobile applications. This monograph presents an overview of AoI from the perspective of wireless networking. It gives a comprehensive introduction to the analytical techniques used in deriving this metric as well as networking strategies that improve the AoI. Extensions to other age-related metrics, applications, and future research directions are also discussed.
Cell-free (CF) integrated sensing and communication (ISAC) merges the CF architecture with ISAC functionalities. CF-ISAC leverages distributed access points, removes cell boundaries, and enhances coverage, spectral efficiency, and reliability. It also improves energy efficiency, enabling robust multi-user communication, distributed multi-static sensing, and seamless resource optimization. A comprehensive survey on CF-ISAC has been lacking. This monograph addresses that gap by covering the foundational principles, cooperative transmission, radar cross-section, target parameter estimation, ISAC integration levels, sensing metrics, and key applications. It also explores the advantages of multi-static sensing. Performance analysis, resource allocation, security, and user/ target-centric designs are discussed. Finally, synchronization, multi-target detection, interference management, and fronthaul limitations are discussed. Advanced antenna technologies, network-assisted systems, near-field CF-ISAC, cross-technology integration, and machine learning approaches are presented.
Robotic systems increasingly demand simultaneous high-precision sensing and low-latency communication-a duality that traditional disjoint architectures struggle to satisfy efficiently. Integrated Sensing and Communication (ISAC) addresses this challenge by unifying both functions within shared radio frequency and spectral resources, eliminating hardware redundancy and spectral inefficiency. This article surveys ISAC-enabled robotics, examining how joint waveform design, cross-layer protocols, and emerging technologies (mmWave, THz, in-band full-duplex transceivers) enable transformative applications. We focus on mission-critical scenarios where ISAC provides unique value: (1) factory robots achieving sub-centimeter positioning alongside millisecond-latency coordination for collision-free assembly, (2) surgical robots requiring simultaneous tissue imaging and instrument teleoperation with ultra-reliability, (3) autonomous vehicle platoons performing radar-based spacing control while exchanging cooperative maneuver plans, and (4) UAV swarms conducting distributed target tracking with bandwidth-efficient inter-agent communication. The article analyzes fundamental trade-offs in ISAC system design-sensing accuracy versus communication throughput, spectrum coexistence, RF front-end integration challenges, and security vulnerabilities arising from shared physical layers. We identify open research directions including AI-driven resource allocation, real-time co-optimization frameworks, and regulatory pathways for spectrum sharing. By consolidating sensing and communication primitives, ISAC emerges as an enabling infrastructure for autonomous robotic systems requiring tight perception-action coupling under stringent resource constraints.
Networks have changed significantly in recent decades, particularly with the emergence of SDN. This technology shapes and controls network traffic, focusing on policing techniques and more and more on Artificial Intelligence. This monograph analyzes how these technologies can enhance network performance, security, and scalability. Through detailed explanations of the theoretical foundations and practical applications, the monograph explores how SDN can be used to effectively manage network resources and traffic through the use of advanced models, real-time analysis, and integration with monitoring and anomaly detection tools. Each component is essential for optimizing network performance, particularly during dynamic loads and changing conditions. In addition to the theoretical framework, the monograph explains practical aspects, which will help both researchers and engineers in industry to understand better how to use SDN technologies to achieve effective traffic shaping and policing. Through an analysis of current challenges in the field of network management, a vision of the future of SDN is also given, with special emphasis on its application in various domains. The monograph is intended for anyone involved in the design, implementation, or management of SDN networks, whether academic researchers, engineers, or industry practitioners. We hope readers find useful information and tools to improve their knowledge and skills in modern network technologies.
Edge computing has evolved significantly from early research ideas to modern 5G mobile and multi-access edge computing (MEC). In many 6G-related projects, we see a clear trend toward virtualizing computing resources at the edge. Motivated by the cloud-edge-continuum that is the basis for next-generation metaverse applications, and the need for low-latency solutions, distributed computing is now receiving even more attention. A final hurdle for the wide use of (virtualized) edge computing for mission-critical applications is resilience. In this context, resilience is the ability of modern communication and computation systems to deal with unknown and unforeseen events, both from internal and external sources. Thus, making MEC resilient to outages (e.g., system failures or energy outages due to natural disasters), security incidents (e.g., the use of intelligent jamming or malicious users), and overall challenging conditions (e.g., high mobility or impaired connectivity) is of the highest importance. In this monograph, we review the current state-of-the-art of resilience in mobile edge computing. We explore MEC-specific challenges and resilience objectives, and discuss selected resilience measures. We trust that this monograph will be an invaluable resource for beginners and experts in the field as a compound resource on resilience in MEC.
The International Mobile Telecommunications (IMT)-2030 framework recently adopted by the International Telecommunication Union Radiocommunication Sector (ITU-R) envisions 6G networks to deliver intelligent, seamless connectivity that supports reliable, sustainable, and resilient communications. Recent developments in the 3rd Generation Partnership Project (3GPP) Releases 17-19, particularly within the Radio Access Network (RAN)4 working group addressing satellite and cellular spectrum sharing and RAN2 enhancing New Radio (NR)/IoT for NTN, highlight the critical role NTN is set to play in the evolution of 6G standards. The integration of advanced signal processing, edge and cloud computing, and Deep Reinforcement Learning (DRL) for Low Earth Orbit (LEO) satellites and aerial platforms, such as Uncrewed Aerial Vehicles (UAV) and high-, medium-, and low-altitude platform stations, has revolutionized the convergence of space, aerial, and Terrestrial Networks (TN). Artificial Intelligence (AI)-powered deployments for NTN and NTN-IoT, combined with Next Generation Multiple Access (NGMA) technologies, have dramatically reshaped global connectivity. This tutorial paper provides a comprehensive exploration of emerging NTN-based 6G wireless networks, covering vision, alignment with 5G-Advanced and 6G standards, key principles, trends, challenges, real-world applications, and novel problem solving frameworks. It examines essential enabling technologies like AI for NTN (LEO satellites and aerial platforms), DRL, edge computing for NTN, AI for NTN trajectory optimization, Reconfigurable Intelligent Surfaces (RIS)-enhanced NTN, and robust Multiple-Input-Multiple-Output (MIMO) beamforming. Furthermore, it addresses interference management through NGMA, including Rate-Splitting Multiple Access (RSMA) for NTN, and the use of aerial platforms for access, relay, and fronthaul/backhaul connectivity.
In this monograph we provide a tutorial on a family of sequential learning and decision problems known as the multi-armed bandit problems. We introduce a wide range of application scenarios for this learning framework, as well as its many different variants. The more detailed discussion is focused on the stochastic bandit problems, with rewards driven by either an IID or a Markov process, and when the environment consists of a single or multiple simultaneous users. We also present literature on the learning of MDPs, which captures coupling among the evolution of different options that a classical MAB problem does not.
The 5th generation (5G) of wireless systems is being deployed with the aim to provide many sets of wireless communication services, such as low data rates for a massive amount of devices, broadband, low latency, and industrial wireless access. Such an aim is even more complex in the next generation wireless systems (6G) where wireless connectivity is expected to serve any connected intelligent unit, such as software robots and humans interacting in the metaverse, autonomous vehicles, drones, trains, or smart sensors monitoring cities, buildings, and the environment. Because of the wireless devices will be orders of magnitude denser than in 5G cellular systems, and because of their complex quality of service requirements, the access to the wireless spectrum will have to be appropriately shared to avoid congestion, poor quality of service, or unsatisfactory communication delays. Spectrum sharing methods have been the objective of intense study through model-based approaches, such as optimization or game theories. However, these methods may fail when facing the complexity of the communication environments in 5G, 6G, and beyond. Recently, there has been significant interest in the application and development of data-driven methods, namely machine learning methods, to handle the complex operation of spectrum sharing. In this survey, we provide a complete overview of the state-of-theart of machine learning for spectrum sharing. First, we map the most prominent methods that we encounter in spectrum sharing. Then, we show how these machine learning methods are applied to the numerous dimensions and sub-problems of spectrum sharing, such as spectrum sensing, spectrum allocation, spectrum access, and spectrum handoff. We also highlight several open questions and future trends.
Blockchains are meant to provide an append-only sequence (ledger) of transactions. Security commonly relies on a consensus protocol in which forks in the sequence are either prevented completely or are exponentially unlikely to last more than a few blocks. This monograph proposes the design of algorithms and a system to achieve high performance (a few seconds from the time of initiation for transactions to enter the blockchain), the absence of forks, and a very low energy cost (a per transaction cost that is a factor of a billion or more less than bitcoin). The foundational component of this setup is a group of satellites whose blockchain protocol code can be verified and burned into read-only memory. Because such satellites can perhaps be destroyed but cannot be captured (unlike even fortified terrestrial servers), a reasonable assumption is that the blockchain protocol code in the satellites may fail to make progress either permanently or intermittently but will not be traitorous. A second component of this setup is a group of terrestrial sites whose job is to broadcast information about blocks and to summarize the blockchain ledger. These can be individuals who are eager to get a fee for service. Even if many of these behave traitorously (against their interests as fee-collectors), a small number of honest ones is sufficient to ensure safety and liveness. A third component of this setup is a Mission Control entity which will act very occasionally to assign roles to terrestrial sites and time slots to satellites. These assignments will be multisigned using the digital signatures of a widely distributed group of human governors. A reasonable assumption on Mission Control is that, for reputational reasons, they will not send any signed message that would either contradict a previous message or attest to an incorrect affirmation. Because Mission Control needs to act very infrequently (to a first approximation, only when satellites fail), any actions of Mission Control can be carefully and publicly scrutinized. Given these components and these reasonable assumptions, our protocol, called Bounce, will achieve ledger functionality for arbitrarily sized blocks at under five seconds per block (based on experiments done with the International Space Station) and at negligible energy cost. T his monograph will discuss the overall architecture and algorithms of such a system, the assumptions it makes, and the guarantees it gives.
Sixth-generation (6G) wireless communication networks will transform connected things in 5G into connected intelligence. The networks can have human-like cognition capabilities by enabling many potential services, such as high-accuracy localization and tracking, augmented human sense, gesture and activity recognition, etc. For this purpose, many emerging applications in 6G have stringent requirements on transmission throughput and latency. With the explosion of devices in the connected intelligence world, spectrum utilization has to be enhanced to meet these stringent requirements. In-band full-duplex (IBFD) has been reported as a promising technique to enhance spectral efficiency and reduce end-to-end latency. However, simultaneous transmission and reception over the same frequency introduce additional interference compared to conventional half-duplex (HD) radios. The receiver is exposed to the transmitter of the same node operating in IBFD mode, causing self-interference (SI), which could be more than 100dB higher than the signal of interest from other nodes due to the proximity of the transceiver. Due to the significant power difference between SI and the signal of interest (SoI), SI must be effectively suppressed to benefit from IBFD operation. In addition to SI, uplink users will interfere with downlink users within the range, known as co-channel Interference (CCI). This interference could be significant in cellular networks, so it has to be appropriately processed to maximize the IBFD gain. The objective of this monograph is to present a timely overview of self-interference cancellation (SIC) techniques and discuss the challenges and possible solutions to implement effective SIC in 6G networks. Then, we investigate beamforming to manage the complex interference and maximize the IBFD gain in cellular networks. Furthermore, we give a deep insight into the benefits of IBFD operations on various emerging applications, e.g., integrated access and backhaul (IAB) networks, integrated sensing and communications (ISAC), and physical layer security (PLS).
The rapid spread of infectious diseases and online rumors share similarities in terms of their speed, scale, and patterns of contagion. Although these two phenomena have historically been studied separately, the COVID-19 pandemic has highlighted the devastating consequences that simultaneous crises of epidemics and misinformation can have on the world. Soon after the outbreak of COVID-19, the World Health Organization launched a campaign against the COVID-19 Infodemic, which refers to the dissemination of pandemic-related false information online that causes widespread panic and hinders recovery efforts. Undoubtedly, nothing spreads faster than fear. Networks serve as a crucial platform for viral spreading, as the actions of highly influential users can quickly render others susceptible to the same. The potential for contagion in epidemics and rumors hinges on the initial source, underscoring the need for rapid and efficient digital contact tracing algorithms to identify superspreaders or Patient Zero. Similarly, detecting and removing rumor mongers is essential for preventing the proliferation of harmful information in online social networks. Identifying the source of large-scale contagions requires solving complex optimization problems on expansive graphs. Accurate source identification and understanding the dynamic spreading process requires a comprehensive understanding of surveillance in massive networks, including topological structures and spreading veracity. Ultimately, the efficacy of algorithms for digital contact tracing and rumor source detection relies on this understanding. This monograph provides an overview of the mathematical theories and computational algorithm design for contagion source detection in large networks. By leveraging network centrality as a tool for statistical inference, we can accurately identify the source of contagions, trace their spread, and predict future trajectories. This approach provides fundamental insights into surveillance capability and asymptotic behavior of contagion spreading in networks. Mathematical theory and computational algorithms are vital to understanding contagion dynamics, improving surveillance capabilities, and developing effective strategies to prevent the spread of infectious diseases and misinformation.
With the fast expansion of communication networks and the increasing dynamic of wireless communication activities, a significant proportion of messages in wireless networks are being transmitted using distributed protocols that feature opportunistic channel access without full user coordination. This challenges the basic assumption of long message transmissions among coordinated users in classical channel coding theory. In this monograph, we introduce channel coding theorems for the distributed communication model where users choose their channel codes individually. We show that, although reliable message recovery is not always guaranteed in distributed communication systems, the notion of fundamental limit still exists, and can indeed be viewed as an extension to its classical correspondence. Due to historical priority of developing wireline networks, network architectures tend to achieve system modularity by compromising communication and energy efficiency. Such a choice is reasonable for wireline systems but can be disastrous for wireless radio networks. Therefore, to reduce efficiency loss, large scale communication networks often adopt wireless communication only at the last hop. Because of such a special structure, architectural inefficiency in wireless part of the network can be mitigated by enhancing the interface between the physical and the data link layers. The enhanced interface, to be proposed, provides each link layer user with multiple transmission options, and supports efficient distributed networking by enabling advanced communication adaptation at the data link layer. In this monograph, we focus on the introduction of distributed channel coding theory, which serves as the physical layer foundation for the enhanced physical-link layer interface. Nevertheless, early research results at the data link layer for the enhanced interface are also presented and discussed.
Age of information (AoI) was introduced in the early 2010s as a notion to characterize the freshness of the knowledge a system has about a process observed remotely. AoI was shown to be a fundamentally novel metric of timeliness, significantly different, to existing ones such as delay and latency. The importance of such a tool is paramount, especially in contexts other than transport of information, since communication takes place also to control, or to compute, or to infer, and not just to reproduce messages of a source. This volume comes to present and discuss the first body of works on AoI and discuss future directions that could yield more challenging and interesting research.
Since their conception satellites have offered the promise of more capacity for terrestrial communication systems or to exploit their inherent multicasting and broadcasting capabilities. Recent advances in satellite technology have resulted in the integration of satellite and terrestrial networks to meet the quality and capacity requirements of modern day communication systems. Network and Protocol Architectures for Future Satellite Systems reviews the emerging technologies being deployed in the networking architectures being proposed in the framework of the Future Internet. Novel protocols such as Multi Path TCP (MPTCP) and networking trends such as Information Centric Networking (ICN) are described in depth and their application in segments deploying both satellite and terrestrial networks are illustrated. This is also the first monograph to review content-based networking extensively. This is becoming increasingly important driven by the ubiquitous nature of the internet. Applications to satellite communications are illustrated and the technical challenges to be further addressed are highlighted.
The network calculus is a framework for the analysis of communication networks, which exploits that many computer network models become tractable for analysis if they are expressed in a min-plus or max-plus algebra. In a min-plus algebra, the network calculus characterizes amounts of traffic and available service as functions of time. In a max-plus algebra, the network calculus works with functions that express the arrival and departure times or the required service time for a given amount of traffic. While the min-plus network calculus is more convenient for capacity provisioning in a network, the max-plus network calculus is more compatible with traffic control algorithms that involve the computation of timestamps. Many similarities and relationships between the two versions of the network calculus are known, yet they are largely viewed as distinct analytical approaches with different capabilities and limitations. We show that there exists a one-to-one correspondence between the min-plus and max-plus network calculus, as long as traffic and service are described by functions with real-valued domains and ranges. Consequently, results from one version of the network calculus can be readily applied for computations in the other version. The ability to switch between min-plus and max-plus analysis without any loss of accuracy provides additional flexibility for characterizing and analyzing traffic control algorithms. This flexibility is exploited for gaining new insights into link scheduling algorithms that offer rate and delay guarantees to traffic flows. J. Liebeherr. Duality of the Max-Plus and Min-Plus Network Calculus. Foundations and Trends R © in Networking, vol. 11, no. 3-4, pp. 139–282, 2016. DOI: 10.1561/1300000059.
Network calculus is a methodology for performance evaluation of communication networks that expresses the analysis of networks in a min-plus or max-plus algebra. In these algebras, the conventional addition and multiplication operations are replaced by the minimum or maximum operation, respectively, and addition. This monograph gives an accessible and concise review of the research conducted in Network Calculus to date. In doing so, it unearths the question: why are min-plus and max-plus calculus not isomorphic whereas the underlying min-plus and max-plus algebras upon which they are based are? This question is fully investigated and the differences between a max-plus and min-plus analysis are presented. This enables scheduling algorithms with rate and delay guarantees by service curves of the network calculus to be characterized, leading to useful results for their use in network research. The monograph is of interest to students and researchers working on the mathematical theory of networks.
The aim of the smart electric energy grid is to improve efficiency, flexibility, and stability of the electric energy generation and distribution system, with the ultimate goal being the added value of energy-related services to the end-consumer and to facilitate energy generation and prudent consumption toward energy efficiency. New technologies, such as networks and sensors, are combined with consumer behaviour to create a complex eco-system in which many factors interact. Modeling and Optimization of the Smart Grid Ecosystem gives some structure to the complex ecosystem and surveys key research problems that have shaped the area. The emphasis is on the presentation of the control and optimization methodology used in approaching each of these problems. This methodology spans convex and linear optimization theory, game theory, and stochastic optimization. Modeling and Optimization of the Smart Grid Ecosystem serves as a reference for researchers wishing to understand the fundamental principles and research problems underpinning the smart grid ecosystem, and the main mathematical tools used to model and analyze such systems.
The aim of the smart electric energy grid is to improve efficiency, flexibility, and stability of the electric energy generation and distribution system, with the ultimate goal being the added value of energy-related services to the end-consumer and to facilitate energy generation and prudent consumption toward energy efficiency. New technologies, such as networks and sensors, are combined with consumer behaviour to create a complex eco-system in which many factors interact. Modeling and Optimization of the Smart Grid Ecosystem gives some structure to the complex ecosystem and surveys key research problems that have shaped the area. The emphasis is on the presentation of the control and optimization methodology used in approaching each of these problems. This methodology spans convex and linear optimization theory, game theory, and stochastic optimization. Modeling and Optimization of the Smart Grid Ecosystem serves as a reference for researchers wishing to understand the fundamental principles and research problems underpinning the smart grid ecosystem, and the main mathematical tools used to model and analyze such systems.
Random access represents possibly the simplest and yet one of the best known approaches for sharing a channel among several users. Since their introduction in the 1970s, random access schemes have been thoroughly studied and small variations of the pioneering Aloha protocol have since then become a key component of many communications standards, ranging from satellite networks to ad hoc and cellular scenarios. A fundamental step forward for this old paradigm has been witnessed in the past few years, with the development of new solutions, mainly based on the principles of successive interference cancellation, which made it possible to embrace constructively collisions among packets rather than enduring them as a waste of resources. These new lines of research have rendered the performance of modern random access protocols competitive with that of their coordinated counterparts, paving the road for a multitude of new applications. This monograph explores the main ideas and design principles that are behind some of such novel schemes, and aims at offering to the reader an introduction to the analytical tools that can be used to model their performance. After reviewing some relevant thoretical results for the random access channel, the volume focuses on slotted solutions that combine the approach of diversity Aloha with successive interference cancellation, and discusses their optimisation based on an analogy with the theory of codes on graphs. The potential of modern random access is then further explored considering two families of schemes: the former based on physical layer network coding to resolve collisions among users, and the latter leaning on the concept of receiver diversity. Finally, the opportunities and the challenges encountered by random access solutions recently devised to operate in asynchronous, i.e., unslotted, scenarios are reviewed and discussed.
Future vehicles will require massive sensing capability. Leveraging only onboard sensors, though, is challenging in crowded environments where the sensing field-of-view is obstructed. One potential solution is to share sensor data among the vehicles and infrastructure. This has the benefits of providing vehicles with an enhanced field-of-view and also additional redundancy to provide more reliability in the sensor data. A main challenge in sharing sensor data is providing the high data rates required to exchange raw sensor data. The large spectral channels at millimeter wave mmWave frequencies provide a means of achieving much higher data rates. This monograph provides an overview of mmWave vehicular communication with an emphasis on results on channel measurements, the physical PHY layer, and the medium access control MAC layer. The main objective is to summarize key findings in each area, with special attention paid to identifying important topics of future research. In addition to surveying existing work, some new simulation results are also presented to give insights on the effect of directionality and blockage, which are the two distinguishing features of mmWave vehicular channels. A main conclusion of this monograph is that given the renewed interest in high rate vehicle connectivity, many challenges remain in the design of a mmWave vehicular network.
