QAC 2016 - Second International Workshop on Quality of Service Assurance in the Cloud (QAC 2016)

Cloud computing offers a computational model where network, storage, and compute domains can be
abstracted into virtual resources offered on demand. While these abstractions offer opportunities to
significantly simplify the management and optimize the use of resources, they impose additional
challenges on assuring the quality of service (QoS).
In the context of multi‐tenancy, the same physical resources are shared by different users that do not
necessarily share the same service level agreements; hence the QoS distinction has to be enforced at a
finer grain. Moreover, certain attributes of the QoS may contradict with others, for instance, high
availability favors replication and distributed redundancy while energy efficiency favors de-duplication
and consolidation. The multi-layered architecture of the distributed cloud requires not only a thorough
orchestration between layers to ensure the required QoS, but also makes the root cause analysis even
more complicated in case of the SLA violation. Continuous changes and migrations of the resources
allocated at all layers of abstraction pose further challenges to detecting problems, identifying their
location and reasoning about causality.
The aim of this workshop is to raise awareness of the challenges of the QoS assurance in the cloud, and
bring together practitioners and researchers to discuss potential solutions.
Topics
The workshop solicits high‐quality papers authored by both industry and academic contributors that address (but not limited to) the following topics:
Security assurance, and regulations compliance in the Cloud
Multi-level isolation orchestration for the Cloud tenants
High Availability and fault tolerance approaches and techniques in the Cloud
Dynamic performance assessment and prediction
Telemetry and smart metering in the Cloud
Managing Carbon Footprint versus QoS trade-?‐offs
Requirement modeling and specification for the QoS
Orchestration and refinement for cloud QoS policies
Dynamic verification and validation of cloud service quality
Automated generation of multi-layer QoS test cases
Autonomic approaches for assurance of cloud service quality
Real-time analytics integration with QoS control loops
Evaluations of cloud QoS impact on application or service QoE
Automatic generation of workflows related to assuring QoS in cloud
Machine learning and data mining techniques for optimizing QoS assurance processes
The effect of virtualization (VMs vs. Containers, NFV vs. specialized HW) on QoS