Abdelhamid Mellouk

Abdennasser Chebira

Machine Learning can be defined in various ways related to a scientific domain concerned with the design and development of theoretical and implementation tools that allow building systems with some Human Like intelligent behavior. Machine learning addresses more specifically the ability to improve automatically through experience.

Machine Learning

A modern communication network can be described as a large, complex, distributed system composed by higher interoperating, smaller sub-systems. Today, the proliferation and convergence of different types of wired, wireless, and mobile networks are crucial for the success of the next generation networking. However, these networks can hardly meet the requirements of future integrated-service networks, and are expected to carry multimedia traffic with various Quality of Experience (QoE) and Quality of Service (QoS) requirements. Providing all relevant QoS/QoE issues in these heterogeneous networks is then an important challenge for telecommunication operators, manufacturers, and companies. The impressive emergence and the important demand of the rising generation of real-time Multi-service (such as Data, Voice VoD, Video-Conference, etc.) over communication heterogeneous networks, require scalability while considering a continuous QoS. This book presents and explains all the techniques in new generation networks which integrate efficient global control mechanisms in two directions: (1) maintain QoS requirements in order to maximize network resources utilization, and minimize operational costs on all the types of wired-wireless-mobile networks used to transport traffic, and (2) mix the QoS associated with home, access, and core networks in order to provide Quality of Service/Quality of Experience expected by users of new services.

Engineering in Next Generation Heterogenous Networks

End-to-End Quality of Service

Said Hoceini

Hai Anh Tran

Based on a convergence of network technologies, the Next Generation Network (NGN) is being deployed to carry high quality video and voice data. In fact, the convergence of network technologies has been driven by the converging needs of end-users. The perceived end-to-end quality is one of the main goals required by users that must be guaranteed by the network operators and the Internet Service Providers, through manufacturer equipment. This is referred to as the notion of Quality of Experience (QoE) and is becoming commonly used to represent user perception. The QoE is not a technical metric, but rather a concept consisting of all elements of a user's perception of the network services. The authors of this book focus on the idea of how to integrate the QoE into a control-command chain in order to construct an adaptive network system. More precisely, in the context of Content-Oriented Networks used to redesign the current Internet architecture to accommodate content-oriented applications and services, they aim to describe an end-to-end QoE model applied to a Content Distribution Network architecture. About the Authors Abdelhamid Mellouk is Full Professor at University of Paris-Est C-VdM (UPEC), Networks & Telecommunications (N&T) Department and LiSSi Laboratory, France. Head of several executive national and international positions, he was the founder of the Network Control Research activity at UPEC with extensive international academic and industrial collaborations. His general area of research is in adaptive real-time control for high-speed new generation dynamic wired/wireless networks in order to maintain acceptable Quality of Service/Experience for added-value services. He is an active member of the IEEE Communications Society and has held several offices including leadership positions in IEEE Communications Society Technical Committees. Said Hoceini is Associate Professor at University of Paris-Est C-VdM (UPEC), Networks & Telecommunications (N&T) Department and LiSSi Laboratory, France. His research focuses on routing algorithms, quality of service, quality of experience, and wireless sensor networks, as well as bio-inspired artificial intelligence approaches. His work has been published in several international conferences and journals and he serves on several TPCs. Hai Anh Tran is Associate Professor at the Hanoi University of Science and Technology (HUST), Vietnam. His research focuses on QoE aspects, QoS adaptive control/command mechanisms, wired routing, as well as bio-inspired artificial intelligence approaches.

Application to Content Delivery Network Architecture

Quality of Experience for Multimedia

Scott Fowler

Boubaker Daachi

This book constitutes the thoroughly refereed post-conference proceedings of the 12th International Conference on Wired/Wireless Internet Communication, WWIC 2014, held in Paris, France, during May 27-28, 2014. The 22 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on wireless and wired networks; resource management and next generation services; next generation services, network architecture and applications.

12th International Conference, WWIC 2014, Paris, France, May 26-28, 2014, Revised Selected Papers

Wired/Wireless Internet Communications

Mostafa Hashem Sherif

Jun Li

Paolo Bellavista

This book constitutes the thoroughly refereed proceedings of the 5th International Conference on Ad Hoc Networks, ADHOCNETS 2013, held in Barcelona, Spain, in October 2013. The 14 revised full papers presented were carefully selected and reviewed from numerous submissions and cover a wide range of applications, commercial and military such as mobile ad hoc networks, sensor networks, vehicular networks, underwater networks, underground networks, personal area networks, home networks and large-scale metropolitan networks for smart cities. They are organized in topical sections on wireless sensor networks, routing, applications and security.

5th International ICST Conference, ADHOCNETS 2013, Barcelona, Spain, October 2013, Revised Selected Papers

Ad Hoc Networks

Reinforcement Learning (RL) is a very dynamic area in terms of theory and application. This book brings together many different aspects of the current research on several fields associated to RL which has been growing rapidly, producing a wide variety of learning algorithms for different applications. Based on 24 Chapters, it covers a very broad variety of topics in RL and their application in autonomous systems. A set of chapters in this book provide a general overview of RL while other chapters focus mostly on the applications of RL paradigms: Game Theory, Multi-Agent Theory, Robotic, Networking Technologies, Vehicular Navigation, Medicine and Industrial Logistic.

Abdelhamid Mellouk

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