Part I: Autonomic Computing. General-Purpose Autonomic Computing. Software Architecture-Based Self-Adaptation. Mobile Agent Middleware for Autonomic Data Fusion. Component-Based Autonomic Management for Legacy Software. Dynamic WSDL for Supporting Autonomic Computing. Bio-Inspired Cognitive Radio for Dynamic Spectrum Access. Introducing Autonomous Behaviors into IMS-Based Architectures. Embodied Cognition Based Distributed Spectrum Sensing for Autonomic Wireless Systems. Autonomic Peer-to-Peer Systems: Incentive and Security Issues.- Part II: Autonomic Networking. Towards Autonomic Networks: Knowledge Management and Self-Stabilization. Autonomic Networking in Wireless Sensor Networks. iNetLab: A Model-Driven Development Environment for Biologically-Inspired Autonomic Network Applications. Network Reconfiguration in High-Performance Interconnection Networks. Autonomic Management of Networked Web Services-Based Processes. Concepts for Self-Protection. Formal Aspects of Self- in Autonomic Networked Computing Systems. Autonomic Information Diffusion in Intermittently Connected Networks. Dynamic and Fair Spectrum Access for Autonomous Communications.
Section 1 Autonomic Computing.- General-Purpose Autonomic Computing.- Software Architecture-Based Self-Adaptation.- Mobile Agent Middleware for Autonomic Data Fusion in Wireless Sensor Networks.- Component-Based Autonomic Management for Legacy Software.- Dynamic WSDL for Supporting Autonomic Computing.- Bio-inspired Cognitive Radio for Dynamic Spectrum Access.- Introducing Autonomous Behaviors into IMS-Based Architectures.- Embodied Cognition-Based Distributed Spectrum Sensing for Autonomic Wireless Systems.- Autonomic Peer-to-Peer Systems: Incentive and Security Issues.- Section 2 Autonomic Networking.- Toward Autonomic Networks: Knowledge Management and Self-Stabilization.- Autonomic Networking in Wireless Sensor Networks.- iNetLab: A Model-Driven Development and Performance Engineering Environment for Autonomic Network Applications.- Network Reconfiguration in High-Performance Interconnection Networks.- Autonomic Management of Networked Web Services-Based Processes.- Concepts for Self-Protection.- Formal Aspects of Self-#x0002A; in Autonomic Networked Computing Systems.- Autonomic Information Diffusion in Intermittently Connected Networks.- Dynamic and Fair Spectrum Access for Autonomous Communications.
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.
Introduces the first compiled state-of-the-art research findings, technologies, tools and innovations that provide sufficient reference material for researchers and practitioners in industry and academia
Provides a comprehensive technical guide covering the introductory and advanced concepts that can serve as a reference material to graduate students in the fields of computing, engineering and computer engineering
Provides detailed discussions on key research challenges and open research issues that are of great importance to graduate students and practitioners who intend to do research and contribute to the achievement of the goal of autonomic computing and networking
Serves as a guideline and gives insights to professional and industrial standards organizations for developing future standards in autonomic computing, communications and networking
Provides valuable information on existing experimental studies including case studies, simulation tools and implementation testbeds in industry and academia that can be used for validation of theories and analytical results by researchers and practitioners at various levels
Contains illustrative figures enabling easy reading.