An Architectural Evaluation of Java TPC-W
HPCA '01 Proceedings of the 7th International Symposium on High-Performance Computer Architecture
Xen and the art of virtualization
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Adaptive control of virtualized resources in utility computing environments
Proceedings of the 2nd ACM SIGOPS/EuroSys European Conference on Computer Systems 2007
VirtualPower: coordinated power management in virtualized enterprise systems
Proceedings of twenty-first ACM SIGOPS symposium on Operating systems principles
Profiling and modeling resource usage of virtualized applications
Proceedings of the 9th ACM/IFIP/USENIX International Conference on Middleware
Automated control of multiple virtualized resources
Proceedings of the 4th ACM European conference on Computer systems
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
SHIP: Scalable Hierarchical Power Control for Large-Scale Data Centers
PACT '09 Proceedings of the 2009 18th International Conference on Parallel Architectures and Compilation Techniques
Towards energy-aware scheduling in data centers using machine learning
Proceedings of the 1st International Conference on Energy-Efficient Computing and Networking
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Virtualization technology enables server and service consolidation to save more power and operational costs of large scale computing systems. However, the consolidation nature of virtualization intensifies the power densities in a rack, thus resulting in higher probability of failures and Service Level Agreements violations under constrained power budget. In this paper, we proposed a power aware resource allocation algorithm, named PaRA, to coordinate and tradeoff the power and performance. In order to provide enough information about power characteristics of individual VM and applications, we use agent for workload characterization and estimation. The real actuation of resource allocation is realized within the Virtual Machines Monitor (VMM). We evaluated our algorithm on a real Xen based virtualization environments with 3 VMs. The results show that the proposed approach can achieve a higher SLA satisfaction rate as 99.6 percent in RUBiS web application, and power consumption savings up to 17.6 percent compared to default Xen resource allocator. The results also show the potential of our algorithm to be used in real virtualization environments.