ICCAC 2016 - 2016 IEEE International Conference on Cloud and Autonomic Computing (ICCAC)

Enterprise-scale cloud platforms and services systems present common and cross-cutting challenges in maximizing power efficiency and performance while maintaining predictable and reliable behavior, and at the same time responding appropriately to environmental and system changes such as hardware failures and varying workloads. Autonomic computing systems address the challenges in managing these environments by integrating monitoring, decision-processing and actuation capabilities to autonomously manage resources and applications based on high-level policies.
Research in cloud and autonomic computing spans a variety of areas, from distributed systems, computer architecture, middleware services, databases and data-stores, networks, machine learning, and control theory. The purpose of the Fourth International Conference on Cloud and Autonomic Computing (ICCAC) is to bring together researchers and practitioners across these disciplines to address the multiple facets of cloud and autonomic computing.
Papers are solicited on a broad array of topics of relevance to cloud and autonomic computing and their intersections, including those that bear on connections and relationships among different research areas or report on prototype systems or experiences. The goal is to continue our international forum focused on the latest research, applications, and technologies aimed at making cloud and autonomic computing systems and services easy to design, to deploy, and to implement, while also being self-manageable, self-regulating and scalable with little involvement of humans or system administrators.
Topics of interest include, but are not limited to:
Autonomic Cloud Computing
Self-managing cloud services
Autonomic resource and energy management in cloud computing
Autonomic cloud applications and services
Autonomic virtual cloud resources and services
Cloud workload characterization and prediction
Monitoring, modeling and analysis of cloud resources and services
Anomaly behavior analysis of autonomic systems and services
Autonomics for Extreme Scales
Large scale autonomic systems
Self-optimizing and self-healing at peta-computing scale
Self-managing middleware and tools for extreme scales
Experiences in autonomic systems and applications at extreme scales (peta/exa-computing)
Autonomic Computing Foundations and Design Methods
Evaluation, validation and quality and correctness assessment of autonomic loops
Theoretical frameworks for modeling and analyzing autonomic computing systems, control and decision theory
Model-based design, software engineering, formal methods, testing, programming languages and environments support
Knowledge representation and visualization of behavior of autonomic systems and services
Autonomic Computing Systems, Tools and Applications
Self-protection techniques of computing systems, networks and applications
Stochastic analysis and prediction of autonomic systems and applications
Benchmarks and tools to evaluate and compare different architectures to implement autonomic cloud systems
High performance autonomic applications
Self-* applications in science and engineering
Self-* Human Machine Interface