Capacity planning and performance modeling: from mainframes to client-server systems
Capacity planning and performance modeling: from mainframes to client-server systems
httperf—a tool for measuring web server performance
ACM SIGMETRICS Performance Evaluation Review
Formal requirements for virtualizable third generation architectures
Communications of the ACM
Virtualizing I/O Devices on VMware Workstation's Hosted Virtual Machine Monitor
Proceedings of the General Track: 2002 USENIX Annual Technical Conference
Architecture of virtual machines
Proceedings of the workshop on virtual computer systems
A Case For Grid Computing On Virtual Machines
ICDCS '03 Proceedings of the 23rd International Conference on Distributed Computing Systems
Xen and the art of virtualization
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Intel Virtualization Technology
Computer
Virtualization for high-performance computing
ACM SIGOPS Operating Systems Review
Adaptive control of virtualized resources in utility computing environments
Proceedings of the 2nd ACM SIGOPS/EuroSys European Conference on Computer Systems 2007
Autonomic Live Adaptation of Virtual Computational Environments in a Multi-Domain Infrastructure
ICAC '06 Proceedings of the 2006 IEEE International Conference on Autonomic Computing
Paravirtualization for HPC systems
ISPA'06 Proceedings of the 2006 international conference on Frontiers of High Performance Computing and Networking
Proceedings of the 3rd ACM Workshop on System-level Virtualization for High Performance Computing
HPC performance domains on multi-core processors with virtualization
ARCS'12 Proceedings of the 25th international conference on Architecture of Computing Systems
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This work aims to achieve better management of physical resources by dynamically reallocating and adjusting local resources according to demand. The research contribution should be measured through three aspects: administrative with a delegation mechanism to help in the management of Virtual Machine (VM) based large-scale systems, fine-grain allocation with an approach to improve the use of physical resources, and intelligent management with a configurable self-adapting engine aware of the application-level requirements. We take into account that each application has different behavior and requires different hardware and software. These dynamic features in a cluster of VM-based resource providers present a challenge to assign properly, according to certain optimization criteria, the physical resources to the VMs. We evaluate, as a case study of resources management, the automated management of CPU in multiprocessor machines.