Modern day wireless communication systems rely heavily on the random access schemes that were originally developed in the 1970s. The pioneering Aloha protocol has become a key component of many communications standards, ranging from satellite networks to ad hoc and cellular scenarios. Recent developments, however, have seen a fundamental leap forward based on using the principles of successive interference cancellation. The modern random access protocols using these new techniques have opened up a wealth of new applications. This tutorial style monograph explores the main ideas and design principles that are behind some of these novel schemes. It introduces the reader to the analytical tools used to model such performance. Focussing on slotted solutions it shows how Aloha can be combined with successive interference cancellation and optimized using the theory of codes on graphs. These techniques are illustrated in applications using physical layer network coding to resolve collisions among users and receiver diversity. It concludes by introducing the reader to the recently asynchronous (or unslotted) schemes. Modern Random Access Protocols is a comprehensive and erudite introduction to a set of techniques that will form part of many future modern communication or networked system.

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 enduring them as a waste of resources. These new lines of research have rendered the performance of modern random access protocols competitive to 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 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.

Computer communication networks have come of age. Today, there is hardly any professional, particularly in engineering, that has not been the user of such a network. This proliferation requires the thorough understanding of the behavior of networks by those who are responsible for their operation as well as by those whose task it is to design such networks. This is probably the reason for the large number of books, monographs, and articles treating relevant issues, problems, and solutions in this field. Among all computer network architectures, those based on broadcast mul tiple access channels stand out in their uniqueness. These networks appear naturally in environments requiring user mobility where the use of any fixed wiring is impossible and a wireless channel is the only available option. Because of their desirable characteristics multiple access networks are now used even in environments where a wired point-to-point network could have been installed. The understanding of the operation of multiple access network through their performance analysis is the focus of this book.

The proliferation of powerful but cheap devices, together with the availability of a plethora of wireless technologies, has pushed for the spread of the Wireless Internet of Things (WIoT), which is typically much more heterogeneous, dynamic, and general-purpose if compared with the traditional IoT. The WIoT is characterized by the dynamic interaction of traditional infrastructure-side devices, e.g., sensors and actuators, provided by municipalities in Smart City infrastructures, and other portable and more opportunistic ones, such as mobile smartphones, opportunistically integrated to dynamically extend and enhance the WIoT environment. A key enabler of this vision is the advancement of software and middleware technologies in various mobile-related sectors, ranging from the effective synergic management of wireless communications to mobility/adaptivity support in operating systems and differentiated integration and management of devices with heterogeneous capabilities in middleware, from horizontal support to crowdsourcing in different application domains to dynamic offloading to cloud resources, only to mention a few. The book presents state-of-the-art contributions in the articulated WIoT area by providing novel insights about the development and adoption of middleware solutions to enable the WIoT vision in a wide spectrum of heterogeneous scenarios, ranging from industrial environments to educational devices. The presented solutions provide readers with differentiated point of views, by demonstrating how the WIoT vision can be applied to several aspects of our daily life in a pervasive manner.

This book constitutes the thoroughly refereed proceedings of the Second International Conference on Machine Learning for Networking, MLN 2019, held in Paris, France, in December 2019. The 26 revised full papers included in the volume were carefully reviewed and selected from 75 submissions. They present and discuss new trends in deep and reinforcement learning, pattern recognition and classification for networks, machine learning for network slicing optimization, 5G system, user behavior prediction, multimedia, IoT, security and protection, optimization and new innovative machine learning methods, performance analysis of machine learning algorithms, experimental evaluations of machine learning, data mining in heterogeneous networks, distributed and decentralized machine learning algorithms, intelligent cloud-support communications, ressource allocation, energy-aware communications, software de ned networks, cooperative networks, positioning and navigation systems, wireless communications, wireless sensor networks, underwater sensor networks.

This book examines the cyber risks associated with Internet of Things (IoT) and highlights the cyber security capabilities that IoT platforms must have in order to address those cyber risks effectively. The chapters fuse together deep cyber security expertise with artificial intelligence (AI), machine learning, and advanced analytics tools, which allows readers to evaluate, emulate, outpace, and eliminate threats in real time. The book’s chapters are written by experts of IoT and machine learning to help examine the computer-based crimes of the next decade. They highlight on automated processes for analyzing cyber frauds in the current systems and predict what is on the horizon. This book is applicable for researchers and professionals in cyber security, AI, and IoT.