Theory and Practice in Parallel Job Scheduling
IPPS '97 Proceedings of the Job Scheduling Strategies for Parallel Processing
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Xen and the art of virtualization
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
The workload on parallel supercomputers: modeling the characteristics of rigid jobs
Journal of Parallel and Distributed Computing
Diagnosing performance overheads in the xen virtual machine environment
Proceedings of the 1st ACM/USENIX international conference on Virtual execution environments
On the Distribution of Sequential Jobs in Random Brokering for Heterogeneous Computational Grids
IEEE Transactions on Parallel and Distributed Systems
A comprehensive model of the supercomputer workload
WWC '01 Proceedings of the Workload Characterization, 2001. WWC-4. 2001 IEEE International Workshop
GRENCHMARK: A Framework for Analyzing, Testing, and Comparing Grids
CCGRID '06 Proceedings of the Sixth IEEE International Symposium on Cluster Computing and the Grid
Experiences with the KOALA co-allocating scheduler in multiclusters
CCGRID '05 Proceedings of the Fifth IEEE International Symposium on Cluster Computing and the Grid (CCGrid'05) - Volume 2 - Volume 02
Proactive fault tolerance for HPC with Xen virtualization
Proceedings of the 21st annual international conference on Supercomputing
Amazon S3 for science grids: a viable solution?
DADC '08 Proceedings of the 2008 international workshop on Data-aware distributed computing
The cost of doing science on the cloud: the Montage example
Proceedings of the 2008 ACM/IEEE conference on Supercomputing
Database systems on virtual machines: How much do you lose?
ICDEW '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering Workshop
C-Meter: A Framework for Performance Analysis of Computing Clouds
CCGRID '09 Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid
An Efficient Resource Management System for On-Line Virtual Cluster Provision
CLOUD '09 Proceedings of the 2009 IEEE International Conference on Cloud Computing
A Categorisation of Cloud Computing Business Models
CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
Design and Implementation of an Efficient Two-Level Scheduler for Cloud Computing Environment
CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
Dynamic Auction Mechanism for Cloud Resource Allocation
CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
Profit-Driven Service Request Scheduling in Clouds
CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
User Requirements for Cloud Computing Architecture
CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
Performance Analysis of Cloud Computing Services for Many-Tasks Scientific Computing
IEEE Transactions on Parallel and Distributed Systems
Modeling user runtime estimates
JSSPP'05 Proceedings of the 11th international conference on Job Scheduling Strategies for Parallel Processing
Evolution of the IBM cloud: enabling an enterprise cloud services ecosystem
IBM Journal of Research and Development
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Performance analysis and evaluation are considered as key infrastructures for distributed computing platforms, such as clusters and grids. Recently, cloud computing has become an emerging commercial infrastructure paradigm, which promises to eliminate the need for maintaining expensive computing facilities by companies and institutes. However, few efforts are taken to address the issue of performance evaluation in cloud environments. In this paper, we present a configurable performance evaluation analysis and evaluation framework, which is aiming to provide users and researchers an easy-to-use toolkit to evaluate their cloud system's runtime performance, or compare the performance when different resource management policy and task scheduling algorithms are taken into account. Extensive experiments are conducted to investigate the effectiveness of the system implementation, and the results indicate that its configurable feature is of significantly usefulness when conducting performance comparing under different scenarios.