An Early Evaluation and Comparison of Three Private Cloud Computing Software Platforms

Cloud computing, after its success as a commercial infrastructure, is now emerging as a private infrastructure. The software platforms available to build private cloud computing infrastructure vary in their performance for management of cloud resources as well as in utilization of local physical resources. Organizations and individuals looking forward to reaping the benefits of private cloud computing need to understand which software platform would provide the efficient services and optimum utilization of cloud resources for their target applications. In this paper, we present our initial study on performance evaluation and comparison of three cloud computing software platforms from the perspective of common cloud users who intend to build their private clouds. We compare the performance of the selected software platforms from several respects describing their suitability for applications from different domains. Our results highlight the critical parameters for performance evaluation of a software platform and the best software platform for different application domains.

[1]  Gabriel Antoniu,et al.  A performance evaluation of Azure and Nimbus clouds for scientific applications , 2012, CloudCP '12.

[2]  John Shalf,et al.  Performance Analysis of High Performance Computing Applications on the Amazon Web Services Cloud , 2010, 2010 IEEE Second International Conference on Cloud Computing Technology and Science.

[3]  Constantinos Evangelinos,et al.  Cloud Computing for parallel Scientific HPC Applications: Feasibility of Running Coupled Atmosphere- , 2008 .

[4]  Jeffrey Shafer,et al.  I/O virtualization bottlenecks in cloud computing today , 2010 .

[5]  G. Bruce Berriman,et al.  Scientific workflow applications on Amazon EC2 , 2010, 2009 5th IEEE International Conference on E-Science Workshops.

[6]  Lv Aili,et al.  Research of High Performance Computing With Clouds , 2010 .

[7]  Rajkumar Buyya,et al.  A framework for ranking of cloud computing services , 2013, Future Gener. Comput. Syst..

[8]  Thomas Fahringer,et al.  Optimizing execution time predictions of scientific workflow applications in the Grid through evolutionary programming , 2013, Future Gener. Comput. Syst..

[9]  Alexandru Iosup,et al.  Performance Analysis of Cloud Computing Services for Many-Tasks Scientific Computing , 2011, IEEE Transactions on Parallel and Distributed Systems.

[10]  Xiaowei Yang,et al.  CloudCmp: comparing public cloud providers , 2010, IMC '10.

[11]  G. Bruce Berriman,et al.  Data Sharing Options for Scientific Workflows on Amazon EC2 , 2010, 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis.

[12]  Yi Liang,et al.  In Cloud, Can Scientific Communities Benefit from the Economies of Scale? , 2010, IEEE Transactions on Parallel and Distributed Systems.

[13]  Muli Ben-Yehuda,et al.  Quantitative Comparison of Xen and KVM , 2008 .

[14]  Edward Walker,et al.  Benchmarking Amazon EC2 for High-Performance Scientific Computing , 2008, login Usenix Mag..

[15]  G. Bruce Berriman,et al.  An Evaluation of the Cost and Performance of Scientific Workflows on Amazon EC2 , 2012, Journal of Grid Computing.

[16]  Indranil Gupta,et al.  Performance Evaluation of the Illinois Cloud Computing Testbed , 2009 .

[17]  Simson L. Garfinkel,et al.  An Evaluation of Amazon's Grid Computing Services: EC2, S3, and SQS , 2007 .

[18]  Sanjay P. Ahuja,et al.  The State of High Performance Computing in the Cloud , 2012 .

[19]  Alexandru Iosup,et al.  A Performance Analysis of EC2 Cloud Computing Services for Scientific Computing , 2009, CloudComp.

[20]  Abhishek Gupta,et al.  Evaluation of HPC Applications on Cloud , 2011, 2011 Sixth Open Cirrus Summit.

[21]  Marin Orlic,et al.  An Early Comparison of Commercial and Open-Source Cloud Platforms for Scientific Environments , 2012, KES-AMSTA.

[22]  Calton Pu,et al.  Understanding Performance Interference of I/O Workload in Virtualized Cloud Environments , 2010, 2010 IEEE 3rd International Conference on Cloud Computing.

[23]  Chris Rose,et al.  A Break in the Clouds: Towards a Cloud Definition , 2011 .

[24]  Alan Jay Smith,et al.  Analysis of benchmark characteristics and benchmark performance prediction , 1996, TOCS.

[25]  Vladimir Stantchev,et al.  Performance Evaluation of Cloud Computing Offerings , 2009, 2009 Third International Conference on Advanced Engineering Computing and Applications in Sciences.

[26]  Matei Ripeanu,et al.  Amazon S3 for science grids: a viable solution? , 2008, DADC '08.

[27]  Lakshmi Rajamani,et al.  Evaluation of Different Hypervisors Performance in the Private Cloud with SIGAR Framework , 2014 .

[28]  Rajkumar Buyya,et al.  High-Performance Cloud Computing: A View of Scientific Applications , 2009, 2009 10th International Symposium on Pervasive Systems, Algorithms, and Networks.

[29]  Osamu Tatebe,et al.  The Gfarm File System on Compute Clouds , 2011, 2011 IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum.

[30]  Dmitrii Zagorodnov,et al.  Eucalyptus: an open-source cloud computing infrastructure , 2009 .

[31]  Ranko Popovic,et al.  A comparison and security analysis of the cloud computing software platforms , 2011, 2011 10th International Conference on Telecommunication in Modern Satellite Cable and Broadcasting Services (TELSIKS).