Journal of Computers, Vol 6, No 8 (2011), 1789-1796, Aug 2011
doi:10.4304/jcp.6.8.1789-1796

A Cloud Computing Infrastructure on Heterogeneous Computing Resources

Baomin XU, Ning Wang, Chunyan Li

Abstract


Cloud computing is a state-of-the-art distributed computing paradigm which can support on-demand service sharing with flexibility and scalability. Cloud computing provides sharable heterogeneous computing resources using internet and data storage on a third party server. In order to use the heterogeneous computing resources in a much more efficient, scalable and flexible way, a Cloud computing infrastructure HCCloud (Heterogeneous Computing Cloud) has developed. With HCCloud, users no longer have to manually setup machine, or determine where and when to schedule their tasks. By pooling together clusters all over the network, resources are used more efficiently as the infrastructure is self-adaptive to the resources changes, and tasks distribution is fully automated with the best match between task requirements and compute capacity which deployed across a variety physical resources. In this paper we introduce the basic principles of the HCCloud design, and discuss some techniques that have made in order to allow HCCloud to be easily accessed over the Web. The main intention of HCCloud is to decrease the configuration scale of the cluster system through heterogeneous workloads, while increasing the number of requests for parallel workload by provisioning enough resources


Keywords


Infrastructure, Resource Selection, Cloud Computing, Ontology, Computing Resources

References


[1] F.Berman, G. Fox, and T. Hey, The Grid: Past, present, and future. In F. Berman, G. C. Fix, and A. J. G. Hey, editors, Grid Computing: Making the Global Infrastructure a Reality, Wiley, 2003, pp.9-50.

[2] C. H. Constantinos Evangelinos, Cloud Computing for parallel Scientific HPC Applications: Feasibility of Running Coupled Atmosphere-Ocean Climate Models on Amazon’s EC2, the First Workshop on Cloud Computing and its Applications, Chicago, IL, Oct. 2008.

[3] Daniel Nurmi, Rich Wolski, Chris Grzegorczy, etc, The Eucalyptus Open-source Cloud-computing System, the First Workshop on Cloud Computing and its Applications, Chicago, IL, Oct. 2008.

[4] Daniel Nurmi, Rich Wolski, Chris Grzegorczyk, etc, Eucalyptus: A Technical Report on an Elastic Utility Computing Archietcture Linking Your Programs to Useful Systems, UCSB Computer Science Tech.Rep. 2008-10.

[5] Amazon,elastic compute cloud(EC2).http://aws.amazo n. com/ec2/

[6] Rajkumar Buyya, Chee Shin Yeo, Srikumar Venugopal, Market-oriented cloud computing: vision, hype, and reality for delivering IT services as computing utilities. Proceedings of the 10th IEEE International Conference on High Performance Computing and Communications, Washington: IEEE Computer Society, 2008,pp.5-13

[7] David De Roure, Nicholas R. Jennings, Nigel R. Shadbolt, The Semantic Grid: Past, Present, and Future, Proceedings of the IEEE. Washington: IEEE Computer Society, 2005.pp. 669-681

[8] Resource Description Framework:www.w3.org/RDF/

[9] Extensible Markup Language: www.w3.org/XML/

[10] OWL Web Ontology Language Overview: www.w3.org/TR/owl-features/

[11] Noy NF, Crubezy M, Fergerson RW,etc.,Protégé-2000: an open-source ontology-development and knowledge-acquisition environment, AMIA Annual Symposium Proceedings (2003).

[12] Sirin, E., Parsia, B., Grau, B. C., Kalyanpur,A., and Katz, Y. Pellet: A practical owl-dl, reasoned, Tech. Rep. 2005-68, Maryland, USA, 2005.

[13] Rafael A. Moreno, Job Scheduling and Resource Management Techniques in Dynamic Grid Environments, Vol. 2970 of LNCS., Springer (2004), pp.25-32.

[14] AlexandreC.T.Vidal,Sergio Takeo Kofuji,Semantics Based Grid Resource Management, in Proceedings of the 5th international workshop on Middleware for grid computing, Newport Beach, California, Nov.26-30, 2007

[15] Sun Grid Engine,www.sun.com/software/gridware/

[16] Hayes, B.,Cloud Computing, Communications of the ACM, Vol. 51(7), July 2008, pp. 9-11.

[17] Jonathan Strickland, How Cloud Storage Works, http://communication.howstuffworks.com/cloudstorage3.htm.

[18] Google App Engine, http://appengine.google.com.

[19] Windows Azure Platform, http://www.microsoft.com/azure/s ervices.mspx.

[20] Paul Watson, Jim Austin, CARMEN: a Scalable Science Cloud, Seattle, Google Scalability Conference, June 2008.

[21] OpenSSH:http://www.openssh.com.

[22] David Hilley,Cloud Computing: A Taxonomy of Platform and Infrastructure-level Offerings, Technical Reports,GIT-CERCS-09-13,Georgia Institute of Technology,April 2009.

[23] David Cheppal,A Short Introduction Cloud Platforms – An Enterprise Oriented View, Technical Report, August 2008.

[24] Jinesh Varia, Cloud Architectures,Technology Evangelist. Amazon Web Services, 2008.

[25] Liang-Jie Zhang, Qun Zhou: CCOA: Cloud Computing Open Architecture. IEEE International Conference on Web Services, Los Angeles, CA, USA, July 2009,pp 607-616.

[26] Christian VECCHIOLA, Xingchen CHU, Rajkumar BUYYA, Aneka: A Software Platform for .NET-based Cloud Computing, Technical Report No. GRIDS-TR-2009-4, The University of Melbourne, Australia, May 25, 2009.

[27] Michael Armbrust, Armando Fox et al., Above the Clouds: A Berkeley View of Cloud Computing, Technical Report No. UCB/EECS-2009-28, University of California at Berkley, USA, Feb. 10, 2009.

[28] I. Foster Yong Zhao, Ioan Raicu, Shiyong Lu, Cloud Computing and Grid Computing 360-Degree Compared, Grid Computing Environments Workshop, Texas,USA,Nov. 2008, pp. 1-10.
http://dx.doi.org/10.1109/GCE.2008.4738445

[29] Daniel Nurmi, Rich Wolski et al, The Eucalyptus Open-source Cloud-computing System, Cloud Computing and Its Applications, October 2008.

[30] Jithesh Moothoor,Vasvi A Bhatt,A Cloud Computing Solution in Universities:Virtual computing lab,2009.


Full Text: PDF


Journal of Computers (JCP, ISSN 1796-203X)

Copyright @ 2006-2012 by ACADEMY PUBLISHER – All rights reserved.