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Virtual Networking with Azure for Hybrid Cloud Computing in Aneka

  • Adel Nadjaran ToosiEmail author
  • Rajkumar Buyya
Chapter

Abstract

Hybrid cloud environments are a highly scalable and cost-effective option for enterprises that need to expand their on-premises infrastructure. In every hybrid cloud solutions, the issue of inter-cloud network connectivity has to be overcome to allow communications, possibly secure, between resources scattered over multiple networks. Network visualization provides the right method for addressing this issue. We present how Azure Virtual Private Network (VPN) services are used to establish an overlay network for hybrid clouds in our Aneka platform. First, we explain how Aneka resource provisioning module is extended to support Azure Resource Manger (ARM) application programming interfaces (APIs). Then, we walk through the process of establishment of an Azure Point-to-Site VPN to provide connectivity between Aneka nodes in the hybrid cloud environment. Finally, we present a case study hybrid cloud in Aneka and we experiment with it to demonstrate the functionality of the system.

Notes

Acknowledgements

We thank Australian Research Council (ARC) Future Fellowship and the Australia-India Strategic Research Fund (AISRF) for their support of our research. We also thank Microsoft for providing access to the Azure IaaS infrastructure.

References

  1. 1.
    Assuno, M. D., Calheiros, R. N., Bianchi, S., Netto, M. A. S., & Buyya, R. (2015). Big data computing and clouds: Trends and future directions. Journal of Parallel and Distributed Computing, 7980, 3–15. Special Issue on Scalable Systems for Big Data Management and Analytics.Google Scholar
  2. 2.
    Belgacem, M. B., & Chopard, B. (2015). A hybrid HPC/cloud distributed infrastructure: Coupling EC2 cloud resources with HPC clusters to run large tightly coupled multiscale applications. Future Generation Computer Systems, 42, 11–21.Google Scholar
  3. 3.
    Brock, M., & Goscinski, A. (2012, July). Execution of compute intensive applications on hybrid clouds (case study with mpiBLAST). In Proceedings of the Sixth International Conference on Complex, Intelligent, and Software Intensive Systems (pp. 995–1000).Google Scholar
  4. 4.
    Brunetti, R. (2011). Windows Azure Step by Step. Microsoft Press.Google Scholar
  5. 5.
    Buyya, R., & Barreto, D. (2015, December) Multi-cloud resource provisioning with Aneka: A unified and integrated utilisation of microsoft azure and amazon EC2 instances. In 2015 International Conference on Computing and Network Communications (CoCoNet) (pp. 216–229).Google Scholar
  6. 6.
    Buyya, R., & Dastjerdi, A. V. (eds.) (2016, May). Internet of Things: Principles and Paradigms. Burlington, Massachusetts, USA: Morgan Kaufmann.Google Scholar
  7. 7.
    Calheiros, R. N., Vecchiola, C., Karunamoorthy, D., & Buyya, R. (2012). The Aneka platform and QoS-driven resource provisioning for elastic applications on hybrid clouds. Future Generation Computer Systems, 28(6), 861–870.CrossRefGoogle Scholar
  8. 8.
    Clemente-Castell, F. J., Nicolae, B., Katrinis, K., Rafique, M. M., Mayo, R.,  & Fernndez, J. C. (2015, December). Enabling big data analytics in the hybrid cloud using iterative mapreduce. In Proceedings of the 8th IEEE/ACM International Conference on Utility and Cloud Computing (UCC) (pp. 290–299).Google Scholar
  9. 9.
    de Assunção, M. D., di Costanzo, A.,  & Buyya, R. (2010). A cost-benefit analysis of using cloud computing to extend the capacity of clusters. Cluster Computing, 13(3), 335–347.Google Scholar
  10. 10.
    Dean, J., & Ghemawat, S. (2008). Mapreduce: Simplified data processing on large clusters. Communication of the ACM, 51(1), 107–113.CrossRefGoogle Scholar
  11. 11.
    Flores, H., Narayana Srirama, S.,  & Paniagua, C. (2011). A generic middleware framework for handling process intensive hybrid cloud services from mobiles. In Proceedings of the 9th International Conference on Advances in Mobile Computing and Multimedia, MoMM ’11, New York, NY, USA (pp. 87–94). ACM.Google Scholar
  12. 12.
    Javadi, B., Abawajy, J., & Buyya, R. (2012). Failure-aware resource provisioning for hybrid cloud infrastructure. Journal of Parallel and Distributed Computing, 72(10), 1318–1331.CrossRefGoogle Scholar
  13. 13.
    Lackermair, G. (2011). Hybrid cloud architectures for the online commerce. Procedia Computer Science, World Conference on Information Technology, 3, 550–555.Google Scholar
  14. 14.
    Mateescu, G., Gentzsch, W., & Ribbens, C. J. (2011). Hybrid computingwhere HPC meets grid and cloud computing. Future Generation Computer Systems, 27(5), 440–453.CrossRefGoogle Scholar
  15. 15.
    Mattess, M., Vecchiola, C., & Buyya, R. (2010, September). Managing peak loads by leasing cloud infrastructure services from a spot market. In Proceedings of the 12th IEEE International Conference on High Performance Computing and Communications (HPCC) (pp. 180–188).Google Scholar
  16. 16.
    Vasile, M.-A., Pop, F., Tutueanu, R.-I., Cristea, V., & Koodziej, J. (2015). Resource-aware hybrid scheduling algorithm in heterogeneous distributed computing. Future Generation Computer Systems, 51, 61–71.CrossRefGoogle Scholar
  17. 17.
    Vecchiola, C., Calheiros, R. N., Karunamoorthy, D., & Buyya, R. (2012). Deadline-driven provisioning of resources for scientific applications in hybrid clouds with Aneka. Future Generation Computer Systems, 28(1), 58–65.CrossRefGoogle Scholar
  18. 18.
    Xu, X., & Zhao, X. (2015, August). A framework for privacy-aware computing on hybrid clouds with mixed-sensitivity data. In Proceedings of the IEEE International Symposium on Big Data Security on Cloud (pp. 1344–1349).Google Scholar
  19. 19.
    Yuan, H., Bi, J., Tan, W., & Li, B. H. (2017). Temporal task scheduling with constrained service delay for profit maximization in hybrid clouds. IEEE Transactions on Automation Science and Engineering, 14(1), 337–348.CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  1. 1.Cloud Computing and Distributed Systems (CLOUDS) Laboratory, School of Computing and Information SystemsThe University of MelbourneMelbourneAustralia

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