CloudControl6 2014 : CFP: 6th Cloud Control Workshop (CloudControl6)

Country: United Kingdom

City: London

Abstr. due: 25.07.2014

Dates: 08.12.14 — 11.12.14

Area Of Sciences: Law; Computer science;

Organizing comittee e-mail:

Organizers: Umeå University,


Cloud computing has become the dominant paradigm to fulfill compute and storage needs while hiding the underlying complexity of resource management. However, under the hood, many parameters at both software and hardware level need to be controlled to ensure the reliability, performance, and energy efficiency of cloud applications. Furthermore, workload variability and software heterogeneity make optimal parameter selection complex, which combined with the large scale of clouds call for distributed resource management solutions.

The workshop is aimed to foster multidisciplinary research in Cloud Control, leveraging expertise in areas such as distributed systems, control theory, autonomic computing, systems management, mathematical statistics, energy management, and performance management. By providing an understanding of the research challenges ahead and by enabling multi-disciplinary research collaborations, the ambition is to shape the future of cloud management.

The 6th Cloud Control Workshop is held in conjunction with the 7th IEEE/ACM Conference on Utility and Cloud Computing (UCC 2014). Expected attendees are leading researchers from any scientific discipline with potential to contribute to this multidisciplinary topic.

Workshop Format. For the first time in the workshop series, the workshop is open for contributed papers. The workshop will include invited and contributed presentations as well as discussion sessions.


Relevant topics are cloud management methods, systems, and principles including any methods from other disciplines supporting the realization of management systems. Target clouds include the whole range of architectures, spanning from single cloud datacenters to highly distributed telecom or mobile clouds. Examples topics are:

* Management of cloud resources (compute, storage, network, etc)
* Cloud scheduling
* Scalability and capacity autoscaling (elasticity management)
* Differentiated quality of service
* Resource overbooking
* High availability and reliability
* Managing complex cloud applications
* Cloud simulation
* Cloud workload modeling, prediction, and generation
* Performance management and QoS
* Energy-efficient resource provisioning
* Control theory for cloud management
* Autonomic computing for cloud management
* Machine learning for cloud management

Conference Web-Site: