Autonomic computing refers to principles and techniques for designing, building, deploying and managing computing systems with minimal human involvement. An autonomic system should be capable of adapting its behaviour to suit its context of use through methods of self-management, self-tuning, self-configuration, self-diagnosis, and self-healing.

Autonomic approaches are particularly suitable for use in Cloud Computing systems, where rapid scalability is required across a pool of resources to support various unpredictable demands, and where the system should automatically adapt to avoid failures in the underlying hardware impacting on the user experience. Autonomic Clouds emerge as a result of applying autonomic computing techniques to Cloud Computing, resulting into robust, fault tolerant and easy to manage and operate cloud architectures and deployments.

The application of intelligent approaches to Autonomic Clouds is gaining prominence in research and industry. Such intelligent approaches include evolutionary techniques, multi-objective and combinational optimization heuristics, genetic algorithms, neural networks, swarm intelligence, and multi-agents systems. Application of these intelligent approaches to Clouds can improve how computing systems and applications are built, used, managed and optimized, maximizing the benefits for users, applications and systems by reducing the operational, maintenance and usage costs of clouds. The interplay of intelligent approaches and Clouds offers numerous challenges.

The international workshop on Intelligent Techniques and Architectures for Autonomic Clouds (ITAAC 2013) aims to bring together researchers and practitioners across Cloud Computing, Intelligent Systems, and Autonomic Computing to discuss issues at the intersection of these disciplines. Key questions to be addressed include: How do emerging cloud architectures satisfy or contradict the vision of autonomic computing? How does the vision of autonomic computing satisfy the vision of self managing and self healing clouds? How do contemporary and emerging intelligent techniques support and enable both of these? Academics, researchers and practitioners are invited to submit original work on the theory and practice of intelligent and autonomic clouds.

Key topics

Topics of interest include (but are not limited to):

Theory and foundations of Intelligent Clouds
Quality of Service and Intelligent Clouds
(auto)scaling of Clouds
Self-organizing, self-healing and self-managing Cloud systems
Intelligent deployment, configuration and maintenance approaches for Clouds
Agent based techniques for Clouds
Adaptive and Evolutionary Approaches for Clouds
Intelligent Cloud Workflows, Planning and Scheduling
Intelligent Cloud Resource Management and Discovery in Clouds
Autonomic Clouds of Sensors
Intelligent Management and Monitoring for Clouds
Intelligent approaches to Cloud Service Level Agreement satisfaction
Applications, Toolkits and frameworks for Intelligent and Autonomic Clouds
Advances in Intelligent Data Analysis due to Clouds
Submissions that offer position statements, theoretical and industrial perspectives, lessons learned, comparisons, evaluations and technical contributions to intelligent autonomic clouds are also welcome.