VLAB-C: Collaborative Virtual Laboratory in Cloud Computing and Its Applications

  • Jianjun Yu
  • Kejun DongEmail author
  • Yihua Zheng
Part of the International Series on Computer Entertainment and Media Technology book series (ISCEMT)


Scientific Virtual Laboratory (SVL) provides an online research environment for inter-disciplinary e-science applications, where researchers can do remote experimentation, create online chat rooms, share costly equipments and resources that otherwise are available to limited number of users due to constraints on time and geographical distances. Whereas traditional SVL may meet issues like access performance, adaptable, extensible and scalable framework adoption when provided to large number of researchers with “Big Data” processing in CAS (Chinese Academy of Science). “Big Data” system usually includes datasets with sizes beyond the ability of commonly-used software tools to capture, manage, and process the data within a tolerable elapsed time. Cloud computing enables “Big Data” processing of all sizes by delivering massive distributed computing and storage capacity as a transparent and centralized service to different communities of inter-disciplinary scientists, which inspires us to develop a SaaS (Software as a Service) cloud for scientific virtual laboratory named VLAB-C. VLAB-C provides three key features: (1) the ability of high performance on massive data processing and large number of communities’ collaboration; (2) elastic computing for collaborative services; (3) extensible open framework for customized service integration through developing the micro-kernel container, the cloud infrastructure, and the open service. We introduce VLAB-C system, its SVL applications, and several experiments on performance, which shows that VLAB-C achieves considerable efficiency with cloud computing technique.


Cloud computing Software as a service (SaaS) Big data Virtual laboratory 



This research is supported by NSFC Grant No. 61202408, CNIC Grant CNIC-PY-1407, and CAS 125 Informatization Project XXH12503.


  1. 1.
    M.L. Bote-Lorenzo, L.M. Vaquero-Gonzlez, G. Vega-Gorgojo, J.I. Asensioprez, E. Gmez-Snchez, Y.A. Dimitriadis, GRIDCOLE: A Grid Collaborative Learning Environment, in Proceedings of IEEE International Symposium on Cluster Computing and the Grid (CCGrid‘04) Google Scholar
  2. 2.
    L.M. Vaquero, EduCloud: PaaS versus IaaS cloud usage for an advanced computer science course. IEEE Trans. Educ. 54(4), 590–598 (2011)CrossRefGoogle Scholar
  3. 3.
    B. Hayes, Cloud computing. Commun. ACM 51(7), 9–11 (2008)CrossRefGoogle Scholar
  4. 4.
    M.A. Beyer, D. Laney, The Importance of ‘Big Data’: A Definition (Gartner, Stamford, CT, 2012)Google Scholar
  5. 5.
    NSF-Cyberinfrastructure-Council, NSF’s Cyberinfrastructure Vision for 21st Century Discovery, v5.pdf
  6. 6.
    H. Tony, E. Trefethen Anne, Cyberinfrastructure for e-science. Science 308(5723), 817–821 (2005)CrossRefGoogle Scholar
  7. 7.
    G. Wenzhuang, What is e-science. eScience Technol. Appl. 1(1), 1–7 (2008)Google Scholar
  8. 8.
    N. Wilkins-Diehr, D. Gannon, G. Klimeck, S. Oster, S. Pamidighantam, TeraGrid science gateways and their impact on science. Computer 41(11), 32–41 (2008)CrossRefGoogle Scholar
  9. 9.
    D.D. Roure, C. Goble, R. Stevens, The design and realisation of the virtual research environment for social sharing of workflows. Future Gener. Comput. Syst. 25(5), 561–567 (2009)CrossRefGoogle Scholar
  10. 10.
    W. Funika, D. Harlak, D. Krl, M. Bubak, Environment for Collaborative Development and Execution of Virtual Laboratory Applications, in Proceedings of 8th International Conference on Computational Science (ICCS‘08) Google Scholar
  11. 11.
    P.-B. Josep, A.-M. Joan, H.-J. Jordi, An integrated structure for a virtual networking laboratory. IEEE Trans. Ind. Electron. 55(6), 2334–2342 (2008)CrossRefGoogle Scholar
  12. 12.
    C.A. Jara, F.A. Candelas, F. Torres, S. Dormido, F. Esquembre, O. Reinoso, Real-time collaboration of virtual laboratories through the internet. Comput. Educ. 52(1), 126–140 (2009)CrossRefGoogle Scholar
  13. 13.
    D. Tsovaltzi, N. Rummel, B.M. McLaren, N. Pinkwart, O. Scheuer, A. Harrer, I. Braun, Extending a virtual chemistry laboratory with a collaboration script to promote conceptual learning. Int. J. Technol. Enhanc. Learn. 2(1), 91–110 (2010)CrossRefGoogle Scholar
  14. 14.
    S.D. Olabarriaga, T. Glatard, P.T. De Boer, A virtual laboratory for medical image analysis. IEEE Trans. Inform. Technol. Biomed. 14(4), 979–985 (2010)CrossRefGoogle Scholar
  15. 15.
    P.R.C. Da Silveira, M.N. Valdez, R.M. Wenzcovitch et al., Virtual Laboratory for Planetary Materials (vlab): An Updated Overview of System Service Architecture, in Proceedings of 2011 TeraGrid Conference: Extreme Digital Discovery (TG‘11) Google Scholar
  16. 16.
    S. Wesner, K. Wulf, M. Muller, How Grid Could Improve E-learning in the Environmental Science Domain, in Proceedings of 1st LEGE-WG International Conference on Educational Models for GRID Based Services (LeGE-WG‘02) Google Scholar
  17. 17.
    A. Bagnasco, A.M. Scapolla, A Grid of Remote Laboratory for Teaching Electronics, in Proceedings of the 2005 Conference on Towards the Learning Grid: Advances in Human Learning Services Google Scholar
  18. 18.
    G. Bourguin, A. Derycke, Integrating the CSCL Activities into Virtual Campuses: Foundations of a New Infrastructure for Distributed Collective Activities, in Proceedings of Euro-CSCL‘01 Google Scholar
  19. 19.
    P. Mell, T. Grance, The NIST definition of cloud computing. Comput. Inform. Sci. 5(6), 50 (2009)Google Scholar
  20. 20.
    J. Dittrich, J.-A. Quian-Ruiz, Efficient big data processing in Hadoop MapReduce. Proc. VLDB Endowment 5(12), 2014–2015 (2012)CrossRefGoogle Scholar
  21. 21.
    L.-J. Zhang, Q. Zhou, CCOA: Cloud Computing Open Architecture, in Proceedings of IEEE International Conference on Web Services (ICWS‘09) Google Scholar
  22. 22.
    M.D. De Assuno, A. Di Costanzo, R. Buyya, Evaluating the Cost-Benefit of Using Cloud Computing to Extend the Capacity of Clusters, in Proceedings of 18th ACM International Symposium on High Performance Distributed Computing (HPDC‘09) Google Scholar
  23. 23.
    J. Matthews, T. Garfinkel, C. Hoff, J. Wheeler, Virtual Machine Contracts for Datacenter and Cloud Computing Environments, in Proceedings of 1st workshop on Automated control for datacenters and clouds (ACDC‘09) Google Scholar
  24. 24.
    A. Rosenthal, P. Mork, M.H. Li, J. Stanford, D. Koester, S.P. Reynold, Cloud computing: a new business paradigm for biomedical information sharing. J. Biomed. Inform. 43(2), 342–353 (2010)CrossRefGoogle Scholar
  25. 25.
    J.W. Park, Y.W. Lee, C.H. Yun, H.K. Park, S.I. Chang, I.P. Lee, H.S. Jung, Cloud Computing for Online Visualization of GIS Applications in Ubiquitous City, in Proceedings of IEEE International Conference on Cloud Computing (CLOUD‘10) Google Scholar
  26. 26.
    M. Olson, K.M. Chandy, Performance Issues in Cloud Computing for Cyberphysical Applications, in Proceedings of IEEE International Conference on Cloud Computing (CLOUD‘11) Google Scholar
  27. 27.
    M. Hajjat, X. Sun, Y.-W.E. Sung et al., Cloudward Bound: Planning for Beneficial Migration of Enterprise Applications to the Cloud, in Proceedings of the ACM SIGCOMM 2010 Conference Google Scholar
  28. 28.
    S. Strauch, V. Andrikopoulos, T. Bachmann, Migrating Application Data to the Cloud using Cloud Data, in Proceedings of 3rd International Conference on Cloud Computing and Service Science (CLOSER‘13) Google Scholar
  29. 29.
    A. Thakar, A. Szalay, Migrating a (Large) Science Database to the Cloud, in Proceedings of 19th ACM International Symposium on High Performance Distributed Computing (HPDC‘10) Google Scholar
  30. 30.
    Y. Kwon, E. Tilevich, Cloud refactoring: automated transitioning to cloud-based services. Autom. Softw. Eng. 21(3), 345–372 (2014)CrossRefGoogle Scholar
  31. 31.
    H. Jamjoom, VirtualWire: System Support for Live Migrating Virtual Networks Across Clouds, in Proceedings of 7th International Workshop on Virtualization Technologies in Distributed Computing (VTDC‘13) Google Scholar
  32. 32.
    L. Zhang, M. Liu, Z. Shi, X. Ma, Research on Virtual Basic Laboratory and Experimental Teaching Resources Platform based on Cloud Computing, in Proceedings of 9th International Symposium on Linear Drives for Industry Applications (LDIA‘14) Google Scholar
  33. 33.
    S. Chen, The view of scientific inquiry conveyed by simulation-based virtual laboratories. Comput. Educ. 55(3), 1123–1130 (2010)CrossRefGoogle Scholar
  34. 34.
    R.C. Correia, J.M. Fonseca, A. Donellan, Euronet Lab a Cloud based Laboratory Environment, in Proceedings of 2012 I.E. Global Engineering Education Conference (EDUCON‘12) Google Scholar
  35. 35.
    R. Dinita, G. Wilson, A. Winckles, M. Cirstea, A Cloud-Based Virtual Computing Laboratory for Teaching Computer Networks, in Proceedings of 13th International Conference on Optimization of Electrical and Electronic Equipment (OPTIM‘12) Google Scholar
  36. 36.
    Y. Simmhan, R. Barga, C. Van Ingen, E. Lazowska, A. Szalay, On Building Scientific Workflow Systems for Data Management in the Cloud, in Proceedings of Fourth IEEE International Conference on eScience (e-Science‘08) Google Scholar
  37. 37.
    J. Erickson, S. Spence, M. Rhodes, D. Banks, J. Rutherford, E. Simpson, G. Belrose, R. Perry, Content-centered collaboration spaces in the cloud. IEEE Internet Comput. 13(5), 34–42 (2009)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Computer Network Information CenterChinese Academy of SciencesBeijingChina

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