The grid: blueprint for a new computing infrastructure
The grid: blueprint for a new computing infrastructure
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
VSched: Mixing Batch And Interactive Virtual Machines Using Periodic Real-time Scheduling
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Comparison of the three CPU schedulers in Xen
ACM SIGMETRICS Performance Evaluation Review
Contextualization: Providing One-Click Virtual Clusters
ESCIENCE '08 Proceedings of the 2008 Fourth IEEE International Conference on eScience
Performance Evaluation of the CPU Scheduler in XEN
ISISE '08 Proceedings of the 2008 International Symposium on Information Science and Engieering - Volume 02
Live migration of virtual machine based on full system trace and replay
Proceedings of the 18th ACM international symposium on High performance distributed computing
Enabling and optimizing pilot jobs using xen based virtual machines for the HPC grid applications
VTDC '09 Proceedings of the 3rd international workshop on Virtualization technologies in distributed computing
VTDC '09 Proceedings of the 3rd international workshop on Virtualization technologies in distributed computing
Toward dependency-aware live virtual machine migration
VTDC '09 Proceedings of the 3rd international workshop on Virtualization technologies in distributed computing
A live storage migration mechanism over wan and its performance evaluation
VTDC '09 Proceedings of the 3rd international workshop on Virtualization technologies in distributed computing
Analyzing the EGEE Production Grid Workload: Application to Jobs Submission Optimization
Job Scheduling Strategies for Parallel Processing
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The primary motivation for uptake of virtualization has been resource isolation, capacity management and resource customization allowing resource providers to consolidate their resources in virtual machines. Various approaches have been taken to integrate virtualization in to scientific Grids especially in the arena of High Performance Computing (HPC) to run grid jobs in virtual machines, thus enabling better provisioning of the underlying resources and customization of the execution environment on runtime. Despite the gains, virtualization layer also incur a performance penalty and its not very well understood that how such an overhead will impact the performance of systems where jobs are scheduled with tight deadlines. Since this overhead varies the types of workload whether they are memory intensive, CPU intensive or network I/O bound, and could lead to unpredictable deadline estimation for the running jobs in the system. In our study, we have attempted to tackle this problem by developing an intelligent scheduling technique for virtual machines which monitors the workload types and deadlines, and calculate the system over head in real time to maximize number of jobs finishing within their agreed deadlines.