Formal requirements for virtualizable third generation architectures
Communications of the ACM
Virtual Machines: Versatile Platforms for Systems and Processes (The Morgan Kaufmann Series in Computer Architecture and Design)
Aneka: Next-Generation Enterprise Grid Platform for e-Science and e-Business Applications
E-SCIENCE '07 Proceedings of the Third IEEE International Conference on e-Science and Grid Computing
The definitive guide to the xen hypervisor
The definitive guide to the xen hypervisor
HPCC '08 Proceedings of the 2008 10th IEEE International Conference on High Performance Computing and Communications
Future Generation Computer Systems
The Eucalyptus Open-Source Cloud-Computing System
CCGRID '09 Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid
Virtual Infrastructure Management in Private and Hybrid Clouds
IEEE Internet Computing
A Heuristic for Mapping Virtual Machines and Links in Emulation Testbeds
ICPP '09 Proceedings of the 2009 International Conference on Parallel Processing
Rule-Based Mapping of Virtual Machines in Clouds
PDP '11 Proceedings of the 2011 19th International Euromicro Conference on Parallel, Distributed and Network-Based Processing
Evaluation of gang scheduling performance and cost in a cloud computing system
The Journal of Supercomputing
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Virtual machine allocation problem is one of the challenges in cloud computing environments, especially for the private cloud design. In this environment, each virtual machine is mapped unto the physical host in accordance with the available resource on the host machine. Specifically, quantifying the performance of scheduling and allocation policy on a Cloud infrastructure for different application and service models under varying performance metrics and system requirement is an extremely challenging and difficult problem to resolve. In this paper, the authors present a Virtual Computing Laboratory framework model using the concept of private cloud by extending the open source IaaS solution Eucalyptus. A rule based mapping algorithm for Virtual Machines VMs which is formulated based on the principles of set theoretic is also presented. The algorithmic design is projected towards being able to automatically adapt the mapping between VMs and physical hosts' resources. The paper, similarly presents a theoretical study and derivations of some performance evaluation metrics for the chosen mapping policies, these includes determining the context switching, waiting time, turnaround time, and response time for the proposed mapping algorithm.