Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Improving Resources Management in Network Virtualization by Utilizing a Software-Based Network

  • 156 Accesses

  • 3 Citations


Network virtualization is a way to simultaneously run multiple heterogeneous architectures on a shared substrate. The main issue in network virtualization is mapping virtual networks to substrate network. How to manage substrate resources in mapping phase will have an effective role in improving the use of infrastructure resources. Using software-based networks in network virtualization which separates control logic from data as a new technology, has led to efficient resource management in this context. In this article a software-based network approach has been presented to network virtualization and manage infrastructure resources efficiently. It optimizes mapping function by dynamic resource management of infrastructure resource. We have added a module in the controller to manage the resources dynamically. An initial mapping will be done for arriving new requests based on number of successful requests and arriving time slots. They will not be finalized by writing the rules in the switches before arriving n requests. If some remapping during the n time window is needed, remapping can be done by the controller and the final results are sent to the switches to write the flow rules. The simulation has been done using NS2 simulator showed based on different evaluation criteria such as acceptance rate, average link utilization, cost and delay.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9


  1. 1.

    Blenk, A., Basta, A., Reisslein, M., & Kellerer, W. (2016). Survey on network virtualization hypervisors for software defined networking. IEEE Communications Surveys & Tutorials, 18(1), 655–685.

  2. 2.

    Kreutz, D., & Ramos, F. (2014). Software-defined networking: A comprehensive survey (pp. 1–61). arXiv preprint. arXiv:1406.0440.

  3. 3.

    Anderson, T., Peterson, L., Shenker, S., & Turner, J. (2005). Overcoming the Internet impasse through virtualization. Computer (Long Beach California), 38(4), 34–41.

  4. 4.

    Bavier, A., Feamster, N., Huang, M., Peterson, L., & Rexford, J. (2006). In VINI Veritas: Realistic and controlled network experimentation. In Proceedings of the 2006 conference on applications, technologies, architectures, and protocols for computer communications (pp. 3–14).

  5. 5.

    Hafeez, T., Ahmed, N., Ahmed, B., & Malik, A. W. (2018). Detection and mitigation of congestion in SDN enabled data center networks: A survey. IEEE Access, 6, 1730–1740.

  6. 6.

    Wickboldt, J. A., De Jesus, W. P., Isolani, P. H., Both, C. B., Rochol, J., & Granville, L. Z. (2015). Software-defined networking: Management requirements and challenges. IEEE Communications Magazine, 53(1), 278–285.

  7. 7.

    Kanagevlu, R., & Aung, K. M. M. (2016). SDN controlled local re-routing to reduce congestion in cloud data center. In Proceedings 2015 international conference on cloud computing research and innovation (ICCCRI 2015) (pp. 80–88).

  8. 8.

    Javadpour, A., & Reza Mohammadi, A. (2016). Improving brain magnetic resonance image (MRI) segmentation via a novel algorithm based on genetic and regional growth. Journal of Biomedical Physics and Engineering, 6(2), 95–108.

  9. 9.

    Karakus, M., & Durresi, A. (2017). Quality of service (QoS) in software defined networking (SDN): A survey. Journal of Network and Computer Applications, 80, 200–218.

  10. 10.

    Mithbavkar, D., Joshi, H., Kotak, H., Gajjar, D., & Perigo, L. (2016). Round robin load balancer using software defined networking (SDN). Capstone Team, Recovery Project.

  11. 11.

    Khondoker, R., Zaalouk, A., Marx, R., & Bayarou, K. (2014). Feature-based comparison of software defined networking (SDN) controllers. In International conference on computers, software and applications, 2014 Proceedings.

  12. 12.

    Qilin, M., & Weikang, S. (2015). A load balancing method based on SDN. In Proceedings of the 2015 7th international conference on measuring technology and mechatronics automation (ICMTMA 2015) (pp. 18–21).

  13. 13.

    Bari, M. F., Roy, A. R., Chowdhury, S. R., Zhang, Q., Zhani, M. F., Ahmed, R., & Boutaba, R. (2013). Dynamic controller provisioning in software defined networks. In 2013 9th international conference on network and service management (CNSM) (pp. 18–25).

  14. 14.

    Mijumbi, R., Serrat, J., Rubio-Loyola, J., Bouten, N., Turck, F. D., & Latré, S. (2014). Dynamic resource management in SDN-based virtualized networks. In 10th international conference on network and service management (CNSM) and Workshop, 2014 (pp. 412–417).

  15. 15.

    Rezaei, S., Radmanesh, H., Alavizadeh, P., Nikoofar, H., & Lahouti, F. (2016). Automatic fault detection and diagnosis in cellular networks using operations support systems data. In NOMS 20162016 IEEE/IFIP network operations and management symposium (pp. 468–473).

  16. 16.

    Trivisonno, R., Vaishnavi, I., Guerzoni, R., Despotovic, Z., Hecker, A., Beker, S., & Soldani, D. (2013). Virtual links mapping in future SDN-enabled networks. In: 2013 IEEE SDN for future networks and services (SDN4FNS) (pp. 1–5).

  17. 17.

    Mijumbi, R., Serrat, J., & Gorricho, J.-L. (2015). Autonomic resource management in virtual networks. CoRR. arXiv:1503.04576.

  18. 18.

    Yu, M., Yi, Y., Rexford, J., & Chiang, M. (2008). Rethinking virtual network embedding: Substrate support for path splitting and migration. SIGCOMM Computer Communication Review, 38(2), 17–29.

  19. 19.

    Chowdhury, M., Rahman, M. R., & Boutaba, R. (2012). ViNEYard: Virtual network embedding algorithms with coordinated node and link mapping. IEEE/ACM Transactions on Networking, 20(1), 206–219.

  20. 20.

    Bhuiyan, M. Z. A., Wu, J., Wang, G., Wang, T., & Hassan, M. M. (2017). e-Sampling: Event-sensitive autonomous adaptive sensing and low-cost monitoring in networked sensing systems. ACM Transactions on Autonomous and Adaptive Systems, 12(1), 11–129.

  21. 21.

    Zhu, Y., & Ammar, M. (2006). Algorithms for assigning substrate network resources to virtual network components. In Proceedings IEEE INFOCOM 2006. 25TH IEEE international conference on computer communications, 2006 (pp. 1–12).

  22. 22.

    Demirci, M., & Ammar, M. (2014). Design and analysis of techniques for mapping virtual networks to software-defined network substrates. Computer Communications, 45(Supplement C), 1–10.

  23. 23.

    Qin, K., Huang, C., Ganesan, N., Liu, K., & Chen, X. (2018). Minimum cost multi-path parallel transmission with delay constraint by extending openflow. China Communications, 15(3), 15–26.

  24. 24.

    Mijumbi, R., Rubio-Loyola, J., Bouten, N., & De Turck, F. (2014). Dynamic resource management in SDN-based virtualized networks. In 10th international conference on network and service management (CNSM) and workshop (pp. 412–417).

  25. 25.

    Javadpour, A., Kazemi Abharian, S., & Wang, G. (2017). Feature selection and intrusion detection in cloud environment based on machine learning algorithms. In 2017 IEEE international symposium on parallel and distributed processing with applications, 2017 IEEE international conference on ubiquitous computing and communications (pp. 1417–1421).

  26. 26.

    Javadpour, A., Memarzadeh-Tehran, H., & Saghafi, F. (2015). A temperature monitoring system incorporating an array of precision wireless thermometers. In 2015 international conference on smart sensors and application (ICSSA) (pp. 155–160).

  27. 27.

    Javadpour, A., & Memarzadeh-Tehran, H. (2015). A wearable medical sensor for provisional healthcare. In 2015 2nd international symposium on physics and technology of sensors (ISPTS) (pp. 293–296).

  28. 28.

    Houidi, I., Louati, W., Zeghlache, D., Papadimitriou, P., & Mathy, L. (2014). Adaptive virtual network provisioning. In Proceedings of the second ACM SIGCOMM workshop on virtualized infrastructure systems and architectures, 2010 (pp. 41–48).

  29. 29.

    Haider, A., Potter, R., & Nakao, A. (2009). Challenges in resource allocation in network virtualization. In 20th ITC specialist seminar, No. May, 2009.

  30. 30.

    Feng, T., Bi, J., & Wang, K. (2014). Joint allocation and scheduling of network resource for multiple control applications in SDN. In 2014 IEEE network operations and management symposium (NOMS) (pp. 1–7).

  31. 31.

    Issariyakul, T., & Hossain, E. (2012). Introduction to network simulator NS2. In Introduction to network simulator NS2 (pp. 1–510).

  32. 32.

    Abdelmoniem, A. M., & Bensaou, B. (2016). Efficient switch-assisted congestion control for data centers: An implementation and evaluation. In Proceedings of the IPCCC 2016.

Download references


This work is supported in part by the National Natural Science Foundation of China under Grants 61632009 and 61472451, in part by the Guangdong Provincial Natural Science Foundation under Grant 2017A030308006 and High-Level Talents Program of Higher Education in Guangdong Province under Grant 2016ZJ01.

Author information

Correspondence to Amir Javadpour.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Javadpour, A. Improving Resources Management in Network Virtualization by Utilizing a Software-Based Network. Wireless Pers Commun 106, 505–519 (2019). https://doi.org/10.1007/s11277-019-06176-6

Download citation


  • Network virtualization
  • Software based network
  • Virtual network mapping
  • Substrate network
  • Virtual network