Skip to main content
SpringerLink
Log in
Book cover

Transactions on Large-Scale Data- and Knowledge-Centered Systems XXX pp 1–22Cite as

Cloud Computing: Read Before Use

  • Chapter
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((TLDKS,volume 10130))

Abstract

Cloud computing is evolving as a new paradigm in service computing in order to reduce initial infrastructure investment and maintenance cost. Virtualization technology is used to create virtual infrastructure by sharing the physical resources through virtual machine. By using these virtual machines, cloud computing technology enables the effective usage of resources with economical profit for customers. Because of these advantages, scientific community is also thinking to shift from grid and cluster computing to cloud computing. However, this virtualization technology comes with significant performance penalties. Moreover, scientific jobs are different from commercial workload. In order to understand the reliability and feasibility of cloud computing for scientific workload, we have to understand the technology and its performance. In this work, we have evaluated the scientific jobs as well as standard benchmarks on private and public cloud to understand exact performance penalties involved in adoption of cloud computing. These jobs are categorized into CPU, memory, N/W and I/O intensive. We also analyzed the results and compared the private and public cloud virtual machine’s performance by considering execution time as well as price. Results show that the cloud computing technology faces considerable performance overhead because of virtualization technology. Therefore, cloud computing technology needs improvement to execute scientific workload.

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
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

Learn about institutional subscriptions

References

  1. Mell, P., Grance, T.: The NIST definition of cloud computing. Commun. ACM 53(6), 50 (2011)

    Google Scholar 

  2. Zhang, Q., Cheng, L., Boutaba, R.: Cloud computing: state-of-the-art and research challenges. J. Internet Serv. Appl. 1(1), 7–18 (2010)

    Article  Google Scholar 

  3. Foster, I., Zhao, Y., Raicu, I., Lu, S.: Cloud computing and grid computing 360-degree compared. In: Grid Computing Environments Workshop, GCE2008, pp. 1–10. IEEE (2008)

    Google Scholar 

  4. Mergen, M.F., Uhlig, V., Krieger, O., Xenidis, J.: Virtualization for high-performance computing. ACM SIGOPS Oper. Syst. Rev. 40(2), 8–11 (2006)

    Article  Google Scholar 

  5. Huber, N., von Quast, M., Hauck, M., Kounev, S.: Evaluating and modeling virtualization performance overhead for cloud environments. In: CLOSER, pp. 563–573 (2011)

    Google Scholar 

  6. McDougall, R., Anderson, J.: Virtualization performance: perspectives and challenges ahead. ACM SIGOPS Oper. Syst. Rev. 44(4), 40–56 (2010)

    Article  Google Scholar 

  7. Adams, K., Agesen, O.: A comparison of software and hardware techniques for x86 virtualization. ACM SIGPLAN Not. 41(11), 2–13 (2006)

    Article  Google Scholar 

  8. Barker, A., Hemert, J.: Scientific workflow: a survey and research directions. In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Wasniewski, J. (eds.) PPAM 2007. LNCS, vol. 4967, pp. 746–753. Springer, Heidelberg (2008). doi:10.1007/978-3-540-68111-3_78

    Chapter  Google Scholar 

  9. Yu, J., Buyya, R.: A taxonomy of scientific workflow systems for grid computing. ACM Sigmod Rec. 34(3), 44–49 (2005)

    Article  Google Scholar 

  10. Juve, G., Deelman, E., Vahi, K., Mehta, G., Berriman, B., Berman, B.P., Maechling, P.: Data sharing options for scientific workflows on Amazon EC2. In: Proceedings of the 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, pp. 1–9. IEEE Computer Society (2010)

    Google Scholar 

  11. Koomey, J.G.: Estimating total power consumption by servers in the US and the world (2007)

    Google Scholar 

  12. Quang-Hung, N., Thoai, N., Son, N.T.: EPOBF: energy efficient allocation of virtual machines in high performance computing cloud. In: Hameurlain, A., Küng, J., Wagner, R., Dang, T.K., Thoai, N. (eds.) Transactions on Large-Scale Data- and Knowledge-Centered Systems XVI. LNCS, vol. 8960, pp. 71–86. Springer, Heidelberg (2014). doi:10.1007/978-3-662-45947-8_6

    Google Scholar 

  13. Greenberg, A., Hamilton, J., Maltz, D.A., Patel, P.: The cost of a cloud: research problems in data center networks. ACM SIGCOMM Comput. Commun. Rev. 39(1), 68–73 (2008)

    Article  Google Scholar 

  14. HTCondor, June 2015. http://research.cs.wisc.edu/htcondor/

  15. Smith, I.C.: Experiences with running MATLAB applications on a power-saving condor pool. http://condor.liv.ac.uk/presentations/cardiff_condor.pdf

  16. KVM, June 2015. http://www.linux-kvm.org/page/Main_Page

  17. Kivity, A., Kamay, Y., Laor, D., Lublin, U., Liguori, A.: KVM: the Linux virtual machine monitor. Proc. Linux Symp. 1, 225–230 (2007)

    Google Scholar 

  18. Chen, W., Lu, H., Shen, L., Wang, Z., Xiao, N., Chen, D.: A novel hardware assisted full virtualization technique. In: The 9th International Conference for Young Computer Scientists, ICYCS 2008, pp. 1292–1297. IEEE (2008)

    Google Scholar 

  19. Xen, June 2015. http://www.xenproject.org/

  20. Barham, P., Dragovic, B., Fraser, K., Hand, S., Harris, T., Ho, A., Neugebauer, R., Pratt, I., Warfield, A.: Xen and the art of virtualization. ACM SIGOPS Oper. Syst. Rev. 37(5), 164–177 (2003)

    Article  Google Scholar 

  21. OpenVZ, June 2015. http://openvz.org/Main_Page

  22. Armbrust, M., Fox, A., Griffith, R., Joseph, A.D., Katz, R., Konwinski, A., Lee, G., et al.: A view of cloud computing. Commun. ACM 53(4), 50–58 (2010)

    Article  Google Scholar 

  23. OpenNebula, June 2015. http://opennebula.org/

  24. OpenStack, June 2015. https://www.openstack.org/

  25. Livny, M., Basney, J., Raman, R., Tannenbaum, T.: Mechanisms for high throughput computing. SPEEDUP J. 11(1), 36–40 (1997)

    Google Scholar 

  26. Raicu, I., Foster, I.T., Zhao, Y.: Many-task computing for grids and supercomputers. In: Workshop on Many-Task Computing on Grids and Supercomputers, MTAGS 2008, pp. 1–11. IEEE (2008)

    Google Scholar 

  27. Apache Benchmark, June 2015. http://httpd.apache.org/docs/2.2/programs/ab.html

  28. LMbench, June 2015. http://www.bitmover.com/lmbench/

  29. IOzone, June 2015. http://www.iozone.org/docs/

  30. nbench, June 2015. http://www.tux.org/~mayer/linux/bmark.html

  31. GSDC, June 2015. http://en.kisti.re.kr/supercomputing/

  32. CDF, June 2015. http://www-cdf.fnal.gov/

  33. Iosup, A., Ostermann, S., Yigitbasi, M.N., Prodan, R., Fahringer, T., Epema, D.H.J.: Performance analysis of cloud computing services for many-tasks scientific computing. IEEE Trans. Parallel Distrib. Syst. 22(6), 931–945 (2011)

    Article  Google Scholar 

  34. Jackson, K.R., Ramakrishnan, L., Muriki, K., Canon, S., Cholia, S., Shalf, J., Wasserman, H.J., Wright, N.J.: Performance analysis of high performance computing applications on the Amazon web services cloud. In: 2010 IEEE Second International Conference on Cloud Computing Technology and Science (CloudCom), pp. 159–168. IEEE (2010)

    Google Scholar 

  35. Saini, S., Heistand, S., Jin, H., Chang, J., Hood, R., Mehrotra, P., Biswas, R.: An application-based performance evaluation of NASA’s nebula cloud computing platform. In: 2012 IEEE 9th International Conference on Embedded Software and Systems (HPCC-ICESS), 2012 IEEE 14th International Conference on High Performance Computing and Communication, pp. 336–343. IEEE (2012)

    Google Scholar 

  36. Li, Z., O’Brien, L., Cai, R., Zhang, H.: Towards a taxonomy of performance evaluation of commercial cloud services. In: 2012 IEEE 5th International Conference on Cloud Computing (CLOUD), pp. 344–351. IEEE (2012)

    Google Scholar 

  37. Khurshid, A., Al-Nayeem, A., Gupta, I.: Performance evaluation of the Illinois cloud computing testbed (2009)

    Google Scholar 

  38. Mei, Y., Ling L., Pu, X., Sivathanu, S.: Performance measurements and analysis of network i/o applications in virtualized cloud. In: 2010 IEEE 3rd International Conference on Cloud Computing (CLOUD), pp. 59–66. IEEE (2010)

    Google Scholar 

  39. Nicolae, B.: On the benefits of transparent compression for cost-effective cloud data storage. In: Hameurlain, A., Küng, J., Wagner, R. (eds.) Transactions on Large-Scale Data and Knowledge-Centered Systems III. LNCS, vol. 6790, pp. 167–184. Springer, Heidelberg (2011). doi:10.1007/978-3-642-23074-5_7

    Chapter  Google Scholar 

  40. Diaz, C.O., Pecero, J.E., Bouvry, P., Sotelo, G., Villamizar, M., Castro, H.: Performance evaluation of an IaaS opportunistic cloud computing. In: 2014 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), pp. 546–547. IEEE (2014)

    Google Scholar 

  41. Frey, S., Reich, C., Lthje, C.: Key performance indicators for cloud computing SLAs. In: The Fifth International Conference on Emerging Network Intelligence, EMERGING 2013, pp. 60–64 (2013)

    Google Scholar 

  42. Wang, H., Wang, F., Liu, J., Groen, J.: Measurement and utilization of customer-provided resources for cloud computing. In: 2012 Proceedings IEEE, INFOCOM, pp. 442–450. IEEE (2012)

    Google Scholar 

  43. Duy, T.V.T., Sato, Y., Inoguchi, Y.: Performance evaluation of a green scheduling algorithm for energy savings in cloud computing. In: 2010 IEEE International Symposium on Parallel and Distributed Processing, Workshops and Phd Forum (IPDPSW), pp. 1–8. IEEE (2010)

    Google Scholar 

  44. Stantchev, V.: Performance evaluation of cloud computing offerings. In: Third International Conference on Advanced Engineering Computing and Applications in Sciences, ADVCOMP 2009, pp. 187–192. IEEE (2009)

    Google Scholar 

  45. Jaikar, A., Dada, H., Kim, G.-R., Noh, S.-Y.: Priority-based virtual machine load balancing in a scientific federated cloud. In: 2014 IEEE 3rd International Conference on Cloud Networking (CloudNet), pp. 248–254. IEEE (2014)

    Google Scholar 

Download references

Acknowledgment

This work was supported by the program of the Construction and Operation for Large-scale Science Data Center (K-16-L01-C06) and by National Research Foundation (NRF) of Korea (N-16-NM-CR01).

Author information

Authors and Affiliations

  1. Grid and Supercomputing Department, Korea University of Science and Technology, Daejeon, 305-350, South Korea

    Amol Jaikar & Seo-Young Noh

  2. National Institute of Supercomputing and Networking, Korea Institute of Science and Technology Information, Daejeon, 305-806, South Korea

    Amol Jaikar & Seo-Young Noh

Authors
  1. Amol Jaikar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Seo-Young Noh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Amol Jaikar .

Editor information

Editors and Affiliations

  1. IRIT, Paul Sabatier University, Toulouse, France

    Abdelkader Hameurlain

  2. FAW, University of Linz, Linz, Austria

    Josef Küng

  3. FAW, University of Linz, Linz, Austria

    Roland Wagner

  4. Software Competence Center Hagenberg, Hagenberg, Austria

    Klaus-Dieter Schewe

  5. Software Competence Center Hagenberg, Hagenberg, Austria

    Karoly Bosa

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer-Verlag GmbH Germany

About this chapter

Cite this chapter

Jaikar, A., Noh, SY. (2016). Cloud Computing: Read Before Use. In: Hameurlain, A., Küng, J., Wagner, R., Schewe, KD., Bosa, K. (eds) Transactions on Large-Scale Data- and Knowledge-Centered Systems XXX. Lecture Notes in Computer Science(), vol 10130. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-54054-1_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-54054-1_1

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-54053-4

  • Online ISBN: 978-3-662-54054-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation