Quantitative system performance: computer system analysis using queueing network models
Quantitative system performance: computer system analysis using queueing network models
Performance Guarantees for Web Server End-Systems: A Control-Theoretical Approach
IEEE Transactions on Parallel and Distributed Systems
An Introduction to the Kalman Filter
An Introduction to the Kalman Filter
Xen and the art of virtualization
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Utility-Function-Driven Resource Allocation in Autonomic Systems
ICAC '05 Proceedings of the Second International Conference on Automatic Computing
Appliance-Based Autonomic Provisioning Framework for Virtualized Outsourcing Data Center
ICAC '07 Proceedings of the Fourth International Conference on Autonomic Computing
Macroeconomics based Grid resource allocation
Future Generation Computer Systems
Future Generation Computer Systems
ICAC '09 Proceedings of the 6th international conference on Autonomic computing
ICAC '09 Proceedings of the 6th international conference on Autonomic computing
Automated control in cloud computing: challenges and opportunities
ACDC '09 Proceedings of the 1st workshop on Automated control for datacenters and clouds
Performance model driven QoS guarantees and optimization in clouds
CLOUD '09 Proceedings of the 2009 ICSE Workshop on Software Engineering Challenges of Cloud Computing
Establishing and Monitoring SLAs in Complex Service Based Systems
ICWS '09 Proceedings of the 2009 IEEE International Conference on Web Services
NCA '09 Proceedings of the 2009 Eighth IEEE International Symposium on Network Computing and Applications
An auction method for resource allocation in computational grids
Future Generation Computer Systems
Automatic virtual machine configuration for database workloads
ACM Transactions on Database Systems (TODS)
SLA-Aware Virtual Resource Management for Cloud Infrastructures
CIT '09 Proceedings of the 2009 Ninth IEEE International Conference on Computer and Information Technology - Volume 02
SLA-driven planning and optimization of enterprise applications
Proceedings of the first joint WOSP/SIPEW international conference on Performance engineering
A control-theoretic approach to automated local policy enforcement in computational grids
Future Generation Computer Systems
From infrastructure delivery to service management in clouds
Future Generation Computer Systems
Virtual Organization Clusters: Self-provisioned clouds on the grid
Future Generation Computer Systems
Autonomic metered pricing for a utility computing service
Future Generation Computer Systems
Adaptive resource provisioning for read intensive multi-tier applications in the cloud
Future Generation Computer Systems
SLA design from a business perspective
DSOM'05 Proceedings of the 16th IFIP/IEEE Ambient Networks international conference on Distributed Systems: operations and Management
OPTIMIS: A holistic approach to cloud service provisioning
Future Generation Computer Systems
A workload characterization study of the 1998 World Cup Web site
IEEE Network: The Magazine of Global Internetworking
Optimal Reconfiguration of the Cloud Network for Maximum Energy Savings
CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
Real-time multi-cloud management needs application awareness
Proceedings of the 5th ACM/SPEC international conference on Performance engineering
| Hi-index | 0.00 |
The optimization problem addressed by this paper involves the allocation of resources in a private cloud such that cost to the provider is minimized (through the maximization of resource sharing) while attempting to meet all client application requirements (as specified in the SLAs). At the heart of any optimization based resource allocation algorithm, there are two models: one that relates the application level quality of service to the given set of resources and one that maps a given service level and resource consumption to profit metrics. In this paper we investigate the optimization loop in which each application's performance model is dynamically updated at runtime to adapt to the changes in the system. These changes could be perturbations in the environment that had not been included in the model. Through experimentation we show that using these tracking models in the optimization loop will result in a more accurate optimization and thus result in the generation of greater profit.