Autonomic Computing Enabled Cooperative Networked Design

This book introduces the concept of autonomic computing driven cooperative networked system design from an architectural perspective. As such it leverages and capitalises on the relevant advancements in both the realms of autonomic computing and networking by welding them closely together. In particular, a multi-faceted Autonomic Cooperative System Architectural Model is defined which incorporates the notion of Autonomic Cooperative Behaviour being orchestrated by the Autonomic Cooperative Networking Protocol of a cross-layer nature. The overall proposed solution not only advocates for the inclusion of certain Decision Making Entities, but it also provides all the necessary implementation guidelines along with the pertinent standardisation orientated insight.

Autonomic Intelligence Evolved Cooperative Networking offers a comprehensive advancement of the state-of-the art technological developments in the fields of Cooperative Networking and Autonomic Computing. Based on his track record in industrial standardisation, as well as academic and applied research, the author presents a fully-fledged Autonomic Cooperative Networking Architectural Model that encompasses the relevant workings of both the Layers of the Open Systems Interconnection Reference Model and the Levels of the Generic Autonomic Network Architecture. .

Cooperative transmission aims to improve the reliability of wireless mobile communications through the use of diversity provided by additional relays assisting in the transmission between the source and destination nodes. This is possible as the rationale behind spatio-temporal processing can be easily mapped onto networked systems. Autonomic Cooperative Networking studies the further evolution of this phenomenon by first involving the network layer routines and then additionally incorporating the notion of autonomic system design.

Autonomic Intelligence Evolved Cooperative Networking offers a comprehensive advancement of the state-of-the art technological developments in the fields of Cooperative Networking and Autonomic Computing. Based on his track record in industrial standardisation, as well as academic and applied research, the author presents a fully-fledged Autonomic Cooperative Networking Architectural Model that encompasses the relevant workings of both the Layers of the Open Systems Interconnection Reference Model and the Levels of the Generic Autonomic Network Architecture. .

Autonomic Computing and Networking presents introductory and advanced topics on autonomic computing and networking with emphasis on architectures, protocols, services, privacy & security, simulation and implementation testbeds. Autonomic computing and networking are new computing and networking paradigms that allow the creation of self-managing and self-controlling computing and networking environment using techniques such as distributed algorithms and context-awareness to dynamically control networking functions without human interventions. Autonomic networking is characterized by recovery from failures and malfunctions, agility to changing networking environment, self-optimization and self-awareness. The self-control and management features can help to overcome the growing complexity and heterogeneity of exiting communication networks and systems. The realization of fully autonomic heterogeneous networking introduces several research challenges in all aspects of computing and networking and related fields.

From cloud computing to data analytics, society stores vast supplies of information through wireless networks and mobile computing. As organizations are becoming increasingly more wireless, ensuring the security and seamless function of electronic gadgets while creating a strong network is imperative. Advanced Methodologies and Technologies in Network Architecture, Mobile Computing, and Data Analytics highlights the challenges associated with creating a strong network architecture in a perpetually online society. Readers will learn various methods in building a seamless mobile computing option and the most effective means of analyzing big data. This book is an important resource for information technology professionals, software developers, data analysts, graduate-level students, researchers, computer engineers, and IT specialists seeking modern information on emerging methods in data mining, information technology, and wireless networks.

Autonomic computing and networking (ACN), a concept inspired by the human autonomic system, is a priority research area and a booming new paradigm in the field. Formal and Practical Aspects of Autonomic Computing and Networking: Specification, Development, and Verification outlines the characteristics, novel approaches of specification, refinement, programming and verification associated with ACN. The goal of ACN and the topics covered in this work include making networks and computers more self-organized, self- configured, self-healing, self-optimizing, self-protecting, and more. This book helpfully details the steps necessary towards realizing computer and network autonomy and its implications.

This textbook provides a practical perspective on autonomic computing. Through the combined use of examples and hands-on projects, the book enables the reader to rapidly gain an understanding of the theories, models, design principles and challenges of this subject while building upon their current knowledge. Features: provides a structured and comprehensive introduction to autonomic computing with a software engineering perspective; supported by a downloadable learning environment and source code that allows students to develop, execute, and test autonomic applications at an associated website; presents the latest information on techniques implementing self-monitoring, self-knowledge, decision-making and self-adaptation; discusses the challenges to evaluating an autonomic system, aiding the reader in designing tests and metrics that can be used to compare systems; reviews the most relevant sources of inspiration for autonomic computing, with pointers towards more extensive specialty literature.

Autonomic networking aims to solve the mounting problems created by increasingly complex networks, by enabling devices and service-providers to decide, preferably without human intervention, what to do at any given moment, and ultimately to create self-managing networks that can interface with each other, adapting their behavior to provide the best service to the end-user in all situations. This book gives both an understanding and an assessment of the principles, methods and architectures in autonomous network management, as well as lessons learned from, the ongoing initiatives in the field. It includes contributions from industry groups at Orange Labs, Motorola, Ericsson, the ANA EU Project and leading universities. These groups all provide chapters examining the international research projects to which they are contributing, such as the EU Autonomic Network Architecture Project and Ambient Networks EU Project, reviewing current developments and demonstrating how autonomic management principles are used to define new architectures, models, protocols, and mechanisms for future network equipment. Provides reviews of cutting-edge approaches to the management of complex telecommunications, sensors, etc. networks based on new autonomic approaches. This enables engineers to use new autonomic techniques to solve complex distributed problems that are not possible or easy to solve with existing techniques. Discussion of FOCALE, a semantically rich network architecture for coordinating the behavior of heterogeneous and distributed computing resources. This provides vital information, since the data model holds much of the power in an autonomic system, giving the theory behind the practice, which will enable engineers to create their own solutions to network management problems. Real case studies from the groups in industry and academia who work with this technology. These allow engineers to see how autonomic networking is implemented in a variety of scenarios, giving them a solid grounding in applications and helping them generate their own solutions to real-world problems.