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Journal of Grid Computing

, Volume 11, Issue 4, pp 699–720 | Cite as

Enhancing Federated Cloud Management with an Integrated Service Monitoring Approach

  • A. Kertesz
  • G. Kecskemeti
  • M. Oriol
  • P. Kotcauer
  • S. Acs
  • M. Rodríguez
  • O. Mercè
  • A. Cs. Marosi
  • J. Marco
  • X. Franch
Article

Abstract

Cloud Computing enables the construction and the provisioning of virtualized service-based applications in a simple and cost effective outsourcing to dynamic service environments. Cloud Federations envisage a distributed, heterogeneous environment consisting of various cloud infrastructures by aggregating different IaaS provider capabilities coming from both the commercial and the academic area. In this paper, we introduce a federated cloud management solution that operates the federation through utilizing cloud-brokers for various IaaS providers. In order to enable an enhanced provider selection and inter-cloud service executions, an integrated monitoring approach is proposed which is capable of measuring the availability and reliability of the provisioned services in different providers. To this end, a minimal metric monitoring service has been designed and used together with a service monitoring solution to measure cloud performance. The transparent and cost effective operation on commercial clouds and the capability to simultaneously monitor both private and public clouds were the major design goals of this integrated cloud monitoring approach. Finally, the evaluation of our proposed solution is presented on different private IaaS systems participating in federations.

Keywords

Cloud computing Cloud federation Service monitoring Cloud brokering 

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References

  1. 1.
    Bernstein, D., Ludvigson, E., Sankar, K., Diamond, S., Morrow, M.: Blueprint for the intercloud—protocols and formats for cloud computing interoperability. In: Proceedings of the 4th International Conference on Internet and Web Applications and Services, pp. 328–336 (2008)Google Scholar
  2. 2.
    Badidi, E., Esmahi, L., Serhani, M.A., Elkoutbi, M.: WS-QoSM: A Broker-based Architecture for Web Services QoS Management. Innovations in Information Technology, pp. 1–5 (2006)Google Scholar
  3. 3.
    Baresi, L., Guinea, S.: Self-supervising BPEL processes. In: IEEE Transactions on Software Engineering. IEEE Computer Society Digital Library (2010)Google Scholar
  4. 4.
    Baur, T., Breu, R., Kalman, T., Lindinger, T., Milbert, A., Poghosyan, G., Reiser, H., Romberg, M.: An interoperable Grid information system for integrated resource monitoring based on virtual organizations. J. Grid Computing 7(3), 319–333 (2009)CrossRefGoogle Scholar
  5. 5.
    Buyya, R., Yeo, C.S., Venugopal, S., Broberg, J., Brandic, I.: Cloud computing and emerging it platforms: vision, hype, and reality for delivering computing as the 5th utility. Future Gener. Comput. Syst. 25(6), 599–616 (2009)CrossRefGoogle Scholar
  6. 6.
    Buyya, R., Ranjan, R., Calheiros, R.N.: InterCloud: utility-oriented federation of cloud computing environments for scaling of application services. Lecture Notes in Computer Science: Algorithms and Architectures for Parallel Processing, vol. 6081 (2010)Google Scholar
  7. 7.
    Cabrera, O., Franch, X.: A quality model for analysing web service monitoring tools. In: Proc. of the 6th IEEE International Conference on Research Challenges in Information Science (RCIS’12), Valencia, Spain (2012)Google Scholar
  8. 8.
    Carlini, E., Coppola, M., Dazzi, P., Ricci, L., Righetti, G.: Cloud Federations in Contrail. Euro-Par 2011 Workshops, LNCS 7155, pp. 159–168 (2012)Google Scholar
  9. 9.
    Celesti, A., Tusa, F., Villari, M., Puliafito, A.: How to enhance cloud architectures to enable cross-federation. In: IEEE 3rd Conference on Cloud Computing (CLOUD) (2010)Google Scholar
  10. 10.
    Cuomo, A., Di Modica, G., Distefano, S., Puliafito, A., Rak, M., Tomarchio, O., Venticinque, S., Villano, U.: An SLA-based broker for cloud infrastructures. J. Grid Computing 11(1), 1–25 (2013)CrossRefGoogle Scholar
  11. 11.
    Di Nitto, E., Ghezzi, C., Metzger, A., Papazoglou, M., Pohl, K.: A journey to highly dynamic, self-adaptive servicebased applications. Autom. Softw. Eng. 15, 313–341 (2008)CrossRefGoogle Scholar
  12. 12.
    Exposito, R.R., Taboada, G.L., Ramos, S., Gonzalez-Dominguez, J., Tourino, J., Doallo, R.: Analysis of I/O performance on an amazon EC2 cluster compute and high I/O platform. J. Grid Computing (2013). doi: 10.1007/s10723-013-9250-y Google Scholar
  13. 13.
    Ferrer, A.J., et al.: OPTIMIS: a holistic approach to cloud service provisioning. Future Gener. Comput. Syst. 28, 66–77 (2012)CrossRefGoogle Scholar
  14. 14.
    Kecskemeti, G., Terstyanszky, G., Kacsuk, P., Nemeth, Z.: An approach for virtual appliance distribution for service deployment. Future Gener. Comput. Syst. 27(3) 280–289 (2011)CrossRefGoogle Scholar
  15. 15.
    Kecskemeti, G., Terstyanszky, G., Kacsuk, P., Nemeth, Z.: Towards efficient virtual appliance delivery with minimal manageable virtual appliances. IEEE Trans. Serv. Comput. (2013) doi: 10.1109/TSC.2013.12 Google Scholar
  16. 16.
    Keller, A., Ludwig, H.: The WSLA framework: specifying and monitoring service level agreements for web services. J. Netw. Syst. Manag. 11(1), 57–81 (2003)CrossRefGoogle Scholar
  17. 17.
    Kertesz, A., Kacsuk, P.: GMBS: a new middleware service for making Grids interoperable. Future Gener. Comput. Syst. 26, 542–553 (2010)CrossRefGoogle Scholar
  18. 18.
    Li, Z., Jin, Y., Han, J.: A runtime monitoring and validation framework for web service interactions. In: Proc. of Australian Software Engineering Conference (2006)Google Scholar
  19. 19.
    Marosi, A.C., Kacsuk, P.: Workers in the clouds. In: Cotronis, Y., Danelutto, M., Papadopoulos, G.A. (eds.) PDP2011, pp. 519–26. IEEE Computer Society (2011)Google Scholar
  20. 20.
    Marosi, A.C., Kecskemeti, G., Kertesz, A., Kacsuk, P.: FCM: an architecture for integrating IaaS cloud systems. In: Proc. of the 2nd International Conference on Cloud Computing, GRIDs, and Virtualization (Cloud Computing 2011), IARIA, Rome, Italy, pp. 7–12 (2011)Google Scholar
  21. 21.
    Montes, J., Sanchez, A., Memishi, B., Perez, M., Antoniu, G.: GMonE: a complete approach to cloud monitoring. Future Gener. Comput. Syst. (2013). doi: 10.1016/j.future.2013.02.011 Google Scholar
  22. 22.
    Rimal, B.P., Jukan, A., Katsaros, D., Goeleven, Y.: Architectural requirements for cloud computing systems: an enterprise cloud approach. J. Grid Computing 9(1), 3–26 (2011)CrossRefGoogle Scholar
  23. 23.
    Muller, C., Oriol, M., Rodriguez, M., Franch, X., Marco, J., Resinas, M., Ruiz-Cortes, A.: SALMonADA: a platform for monitoring and explaining violations of WS-agreement-compliant documents. In: Proc. of the 4th International Workshop on Principles of Engineering Service-Oriented Systems (PESOS’12) (2012)Google Scholar
  24. 24.
    Oriol, M., Franch, X., Marco, J., Ameller, D.: Monitoring adaptable soa-systems using salmon. In: Workshop on Service Monitoring, Adaptation and Beyond (Mona+), pp. 19–28 (2008)Google Scholar
  25. 25.
    Marshall, P., Keahey, K., Freeman, T.: Elastic site: using clouds to elastically extend site resources. T. IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2010), Melbourne, Australia (2010)Google Scholar
  26. 26.
    Petcu, D., Craciun, C., Neagul, M., Rak, M., Lazcanotegui, I.: Building an interoperability API for sky computing. In: Proc. of the 2nd International Workshop on Cloud Computing Interoperability and Services (InterCloud 2011), IEEE CS, pp. 405–412 (2011)Google Scholar
  27. 27.
    Rochwerger, B., Breitgand, D., Levy, E., Galis, A., Nagin, K., Lloriente, I., Montero, R., Wolfsthal, Y., Elmroth, E., Caceres, J., Ben-Yehuda, M., Emmerich, W., Galan, F.: The RESERVOIR model and architecture for open federated cloud computing. IBM J. Res. Dev. 53(4), 1–11 (2009)CrossRefGoogle Scholar
  28. 28.
    Rochwerger, B., Breitgand, D., Epstein, A., Hadas, D., Loy, I., Nagin, K., Tordsson, J., Ragusa, C., Villari, M., Clayman, S., Levy, E., Maraschini, A., Massonet, P., Munoz, H., Toffetti, G.: Reservoir–when one cloud is not enough. Computer 44(3), 44–51 (2011)CrossRefGoogle Scholar
  29. 29.
    Schmidt, M., Fallenbeck, N., Smith, M., Freisleben, B.: Efficient distribution of virtual machines for cloud computing. In: Proceedings of the 2010 18th Euromicro Conference on Parallel, Distributed and Network-based Processing, pp. 567–574. IEEE Computer Society (2010)Google Scholar
  30. 30.
    Silberstein, M., Sharov, A., Geiger, D., Schuster, A.: GridBot, execution of bags of tasks in multiple Grids. In: Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis (SC’09) (2009)Google Scholar
  31. 31.
    Sotomayor, B., Montero, R.S., Llorente, I.M., Foster, I.: Virtual infrastructure management in private and hybrid clouds. IEEE Internet Comput. 13(5), 14–22 (2009)CrossRefGoogle Scholar
  32. 32.
    Truong, H., Fahringer, T., Dustdar, S.: Dynamic instrumentation, performance monitoring and analysis of Grid scientific workflows. J. Grid Computing (JOGC) 3, 1–18 (2005)CrossRefGoogle Scholar
  33. 33.
    Vaquero, L.M., Rodero-Merino, L., Caceres, J., Lindner, M.: A break in the clouds: towards a cloud definition. SIGCOMM Comput. Commun. Rev. 39(1), 50–55 (2008)CrossRefGoogle Scholar
  34. 34.
    Wang, X., Wang, H., Wang, Y.: A monitoring framework for multi-cluster environment using enterprise service bus. International Conference on Management and Service Science (2009)Google Scholar
  35. 35.
    Yigitbasi, N., Iosup, A., Epema, D., Ostermann, S.: C-Meter: a framework for performance analysis of computing clouds. In: The International Workshop on Cloud Computing (Cloud 2009) (2009)Google Scholar
  36. 36.
    Zhang, P., Li, B., Muccini, H., Sun, M.: An approach to monitor scenario-based temporal properties in web service compositions. In: Advanced Web and Network Technologies, and Applications (2008)Google Scholar
  37. 37.
    Zhou, C., Chia, L.T., Lee, B.S.: DAML-QoS ontology for web services. In: IEEE International Conference on Web Services, pp. 472–479 (2004)Google Scholar
  38. 38.
  39. 39.
    CESNET Czech academic network operator. http://www.ces.net/about/ (2012). Accessed 12 Sep 2012
  40. 40.
    SZTAKI Cloud. http://cloud.sztaki.hu/en/home (2012). Accessed 15 Aug 2012
  41. 41.
    Amazon CloudWatch. http://aws.amazon.com/cloud-watch/ (2009). Accessed 18 June 2009
  42. 42.
    Amazon Web Services LLC. Amazon elastic compute cloud. http://aws.amazon.com/ec2/ (2009). Accessed 18 June 2009
  43. 43.
    Cerebrata Azure Diagnostics Manager. http://www.cere-brata.com/Products/AzureDiagnosticsManager (2011). Accessed 5 Oct 2011
  44. 44.
    Eucalyptus cloud. http://www.eucalyptus.com/ (2011). Accessed 5 Oct 2011
  45. 45.
    LPDS laboratory website. http://www.lpds.sztaki.hu (2012). Accessed 10 July 2012
  46. 46.
    Nagios XI monitoring solution. http://www.nagios.com/products/nagiosxi/ (2012). Accessed 10 July 2012
  47. 47.
    OpenNebula cloud. http://opennebula.org/ (2011). Accessed 10 Dec 2011
  48. 48.
    Rackspace Cloud. http://www.rackspace.com/cloud/ (2011). Accessed 10 Dec 2011
  49. 49.
    The World Wide Web Consortium. http://www.w3.org/TR/wsdl (2009). Accessed 14 Jan 2009
  50. 50.
    Windows Azure Platform. http://www.windowsazure.com (2012). Accessed 20 Feb 2012
  51. 51.
    Video demonstration of the monitoring capability integrated to FCM. http://www.youtube.com/watch?v=uIewqw_FJQc (2013). Accessed 30 Apr 2013

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • A. Kertesz
    • 1
  • G. Kecskemeti
    • 2
  • M. Oriol
    • 3
  • P. Kotcauer
    • 1
  • S. Acs
    • 1
  • M. Rodríguez
    • 3
  • O. Mercè
    • 3
  • A. Cs. Marosi
    • 1
  • J. Marco
    • 3
  • X. Franch
    • 3
  1. 1.MTA SZTAKIBudapestHungary
  2. 2.Universität InnsbruckInnsbruckAustria
  3. 3.Universitat Politècnica de CatalunyaBarcelonaSpain

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