Skip to main content

YML-PC: A Reference Architecture Based on Workflow for Building Scientific Private Clouds

  • Chapter
  • First Online:
Cloud Computing

Part of the book series: Computer Communications and Networks ((CCN))

Abstract

Cloud computing platforms such as Amazon EC2 provide customers flexible, on-demand resources at low cost. However, while the existing offerings are useful for providing basic computation and storage resources, they fail to consider factors such as security, custom, and policy. So, many enterprises and research institutes would not like to utilize those public Clouds. According to investigations on real requirements from scientific computing users in China, the project YML-PC has been started to build private Clouds and hybrid Clouds for them. In this paper, we will focus on the first step of YML-PC to present a reference architecture based on the workflow framework YML for building scientific private Clouds. Then, some key technologies such as trust model, data persistence, and schedule mechanisms in YML-PC are discussed. Finally, some experiments are carried out to testify that the solution presented in this paper is more efficient.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Ostermann S et al Early cloud computing evaluation. http://www.pds.ewi.tudelft.nl/_iosup/

  2. Armbrust M, Fox A, Griffith R, Joseph A, Katz R, Konwinski A, Lee G, Patterson D, Rabkin A, Stoica I, Zaharia M (2009, Feb 10) Above the clouds: a Berkeley view of cloud computing. Technical Report, University of California, Berkley, USA

    Google Scholar 

  3. Garfinkel SL (Aug 2007) An evaluation of Amazon’s grid computing services: EC2, S3 and SQS. Technical Report TR-08-07, Harvard University

    Google Scholar 

  4. de Assuncao MD, di Costanzo A, Buyya R (2009) Evaluating the cost-benefit of using cloud computing to extend the capacity of clusters. HPDC ‘09, ACM, pp 141–150

    Google Scholar 

  5. Ibrahim S, Jin H, Lu L, Qi L, Wu S, Shi X (2009) Evaluating MapReduce on virtual machines: The Hadoop case. CloudCom 2009, pp 519–528

    Google Scholar 

  6. David P (2006) Anderson, Gilles Fedak: the computational and storage potential of volunteer computing. CCGRID 2006, pp 73–80

    Google Scholar 

  7. Heien EM, Anderson DP (2009) Computing low latency batches with unreliable workers in volunteer computing environments. J Grid Comput 7(4):501–518

    Article  Google Scholar 

  8. Javadi B, Kondo D, Vincent JM, Anderson DP (Sept 2009) Mining for statistical models of availability in large scale distributed systems: an empirical study of SETI@home. 17th IEEE/ACM MASCOTS 2009, London, UK

    Google Scholar 

  9. Ma X, Vazhkudai SS, Zhang Z (December 2009) Improving data availability for better access performance: a study on caching scientific data on distributed desktop workstations. J Grid Comput 7(4):419–438

    Article  Google Scholar 

  10. Kondo D, Javadi B, Malecot P, Cappello F, Anderson DP (2009) Cost-benefit analysis of Cloud Computing versus desktop grids. ipdps, pp 1–12

    Google Scholar 

  11. Andrzejak A, Kondo D, Anderson DP (2010) Exploiting non-dedicated resources for cloud computing. In the 12th IEEE/IFIP (NOMS 2010), Osaka, Japan, 19–23 April 2010

    Google Scholar 

  12. Domingues P, Araujo F, Silva L (2009) Evaluating the performance and intrusiveness of virtual machines for desktop grid computing, IPDPS, 23–29 May 2009, pp 1–8

    Google Scholar 

  13. Vincenzo D (2009) Cunsolo, Salvatore Distefano, Antonio Puliafito, Marco Scarpa: Cloud@Home: bridging the gap between volunteer and cloud computing. ICIC (1):423–432

    Google Scholar 

  14. Delannoy O, Emad N, Petiton SG (2006) Workflow global computing with YML. In: The 7th IEEE/ACM international conference on grid computing, pp 25–32

    Google Scholar 

  15. Delannoy O (Sept 2008) YML: a scientific workflow for high performance computing. Ph.D. thesis, Versailles

    Google Scholar 

  16. Delannoy O, Petiton S (2004) A peer to peer computing framework: design and performance evaluation of YML. In: third international workshop on HeterPar 2004, IEEE Computer Society Press, pp 362–369

    Google Scholar 

  17. Choy L, Delannoy O, Emad N, Petiton SG (2009) Federation and abstraction of heterogeneous global computing platforms with the YML framework, cisis, pp 451–456. In: The international conference on complex, intelligent and software intensive systems, 2009

    Google Scholar 

  18. Caron E, Desprez F, Loureiro D, Muresan A (2009) Cloud computing resource management through a grid middleware: a case study with DIET and eucalyptus. Cloud, pp 151–154

    Google Scholar 

  19. Sato M, Boku T, Takahashi D (2003) OmniRPC: a Grid RPC system for parallel programming in cluster and grid environment. In: the 3rd IEEE international symposium on cluster computing and the grid, pp 206–213

    Google Scholar 

  20. Germain C, eri VN′, Fedak G, Cappello F (2000) Xtremweb: building an experimental platform for global computing. In: Buyya R, Baker M (eds) GRID, ser. lecture notes in Computer Science, vol 1971. Springer, Heidelberg, pp 91–101

    Google Scholar 

  21. Wang L, Tao J, Kunze M, Castellanos AC, Kramer D, Karl W (2008) Scientific cloud computing: early definition and experience. In the 10th IEEE international conference on HPCC, pp 825–830

    Google Scholar 

  22. Foster I, Zhao Y, Raicu I, Lu S (2008) Cloud computing and grid computing 360-degree compared. In Grid computing environments workshop, pp 1–10

    Google Scholar 

  23. Vecchiola C, Pandey S, Buyya R (2009) High-performance cloud computing: a view of scientific applications. In the 10th international symposium on pervasive systems, algorithms and networks (I-SPAN 2009), Kaohsiung, Taiwan, December 2009

    Google Scholar 

  24. Jha S, Merzky A, Fox G ( June 2009) Using clouds to provide grids with higher levels of abstraction and explicit support for usage modes. Concurr Comput Pract Exper 21(8):1087–1108

    Article  Google Scholar 

  25. Shang L, Wang Z, Zhou X, Huang X, Cheng Y (2007) Tm-dg: a trust model based on computer users’ daily behavior for desktop grid platform. In CompFrame ’07: proceedings of the 2007 symposium on component and framework technology in high-performance and scientific computing, ACM, New York, USA, pp 59–66

    Google Scholar 

  26. Smets P (1990) The transferable belief model and other interpretations of Dempster-Shafer’s model. In the proceedings of the sixth annual conference on uncertainty in artificial intelligence, pp 375–384, 27–29 July 1990

    Google Scholar 

  27. Shang L, Wang Z, Petiton SG (2008) Solution of large scale matrix inversion on cluster and grid. In proceedings of the 2008 seventh international conference on grid and cooperative computing (GCC), 24–26 October 2008, pp 33–40

    Google Scholar 

  28. Shang L, Petiton S, Hugues M (2009) A new parallel paradigm for block-based Gauss-Jordan algorithm (gcc). In the eighth international conference on grid and cooperative computing, pp 193–200

    Google Scholar 

  29. Cappello F et al (2005) Grid’5000: a large scale and highly reconfigurable grid experimental testbed. In the 6th IEEE/ACM international conference on grid computing, pp 99–106

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ling Shang .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer London

About this chapter

Cite this chapter

Shang, L., Petiton, S., Emad, N., Yang, X. (2010). YML-PC: A Reference Architecture Based on Workflow for Building Scientific Private Clouds. In: Antonopoulos, N., Gillam, L. (eds) Cloud Computing. Computer Communications and Networks. Springer, London. https://doi.org/10.1007/978-1-84996-241-4_9

Download citation

  • DOI: https://doi.org/10.1007/978-1-84996-241-4_9

  • Published:

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84996-240-7

  • Online ISBN: 978-1-84996-241-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics