Skip to main content
SpringerLink
Log in

MAP-SDN: a metaheuristic assignment and provisioning SDN framework for cloud datacenters

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

Software-defined networking (SDN) introduces a new method in networking that by offering programmability and centralization, it can dynamically control and configure networks. In traditional networks, data plane did the whole forwarding process, but SDN decouples data plane and control plane by using programmable software controllers for deciding how to forward different flows. By implementing control plane in a software-based independent layer, the network management will become much easier and new policies can be applied to the network by changing a few lines of code. Since the resource allocation and meeting the required service-level agreement are really important in large-scale networks such as cloud datacenters, using SDN can be very useful. In these networks, one logically centralized controller cannot handle the whole network traffic and it will become network bottleneck. Therefore, multiple distributed controllers should be allocated in different regions of the network. Since the request rate of switches varies in time, by dynamic allocation of controllers, network resources will be allocated efficiently and this approach can also reduce power consumption. In this paper, we are going to propose a framework for provisioning software controllers in cloud datacenters by using metaheuristic algorithms. These algorithms can be less accurate compared to other kinds, but their main characteristics like simplicity, flexibility, derivation free, and local optimum avoidance make them a good nominee for solving controller provisioning problem and controller placement problem. Our framework improves computation time and reaches better results compared to other allocation techniques, but it is less accurate in some scenarios. Therefore, we believe metaheuristic approach can be very useful in developing new technologies for SDN in the future.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  1. Kreutz D, Ramos FMV, Verssimo PE, Rothenberg CE, Azodolmolky S, Uhlig S (2015) Software-defined networking: a comprehensive survey. Proc IEEE 103(1):14–76

    Article  Google Scholar 

  2. Open networking foundation, openflow switch specification, v1.3.4, March, 27, 2014. https://www.opennetworking.org/ja/sdn-resources-ja/onf-specifications/openflow

  3. Ciscos one platform kit (onepk). http://www.cisco.com/en/US/prod/iosswrel/onepk.html

  4. Hinrichs TL, Gude NS, Casado M, Mitchell JC, Shenker S (2009) Practical declarative network management. In: Proceedings of the 1st ACM Workshop on Research on Enterprise Networking, ser. WREN’09. ACM, New York, NY, pp 1–10

  5. Fielding RT, Taylor RN (2000) Principled design of the modern web architecture. In: Proceedings of the 22nd International Conference on Software Engineering, ICSE’00, ACM, New York, pp 407–416

  6. Gubbi J, Buyya R, Marusic S, Palaniswami M (2013) Internet of Things (IoT): a vision, architectural elements, and future directions. Future Gener Comput Syst 29(7):1645–1660. ISSN 0167-739X

    Article  Google Scholar 

  7. Bernardos CJ et al (2014) An architecture for software defined wireless networking. In: IEEE Wireless Communications, vol 21, no 3, pp 52–61, June 2014

  8. Kang S, Yoon W (2016) SDN-based resource allocation for heterogeneous LTE and WLAN multi-radio networks. J Supercomput 72:1342–1362

    Article  Google Scholar 

  9. Kim Y-h, Lim H-k, Kim K-h, Han Y-H (2016) A SDN-based distributed mobility management in LTE/EPC network. J Supercomput, pp 1–15. doi:10.1007/s11227-016-1724-9

  10. Duan X, Akhtar AM, Wang X (2015) Software-defined networking-based resource management: data offloading with load balancing in 5G HetNet. EURASIP J Wirel Commun Netw, pp 1–13. doi:10.1186/s13638-015-0405-3

  11. Akyildiz Ian F, Wang P, Shih-Chun L (2015) SoftAir: a software defined networking architecture for 5G wireless systems. Comput Netw 85:1–18. ISSN 1389-1286

    Article  Google Scholar 

  12. Hong W, Wang K, Hsu YH (2013) Application-aware resource allocation for SDN-based cloud datacenters. In: 2013 International Conference on Cloud Computing and Big Data (CloudCom-Asia), pp 106–110

  13. Heller B, Sherwood R, McKeown N (2012) The controller placement problem. In: Proceedings of the First Workshop on Hot Topics in Software Defined Networks, HotSDN’12, ACM, New York, pp 7–12

  14. Hassas Yeganeh S, Ganjali Y (2012) Kandoo: a framework for efficient and scalable offloading of control applications. In: Proceedings of the First Workshop on Hot Topics in Software Defined Networks, HotSDN’12, ACM, New York, pp 19–24

  15. Yeganeh SH, Ganjali Y (2014) Beehive: towards a simple abstraction for scalable software-defined networking. In: Proceedings of the 13th ACM Workshop on Hot Topics in Networks, HotNets-XIII, ACM, New York, pp 13:1–13:7

  16. Tootoonchian A, Ganjali Y (2010) Hyperflow: a distributed control plane for openflow, In: Proceedings of the 2010 Internet Network Management Conference on Research on Enterprise Networking, INM/WREN’10, USENIX Association, Berkeley, pp 3–3

  17. Berde P, Gerola M, Hart J, Higuchi Y, Kobayashi M, Koide T, Lantz B, O’Connor B, Radoslavov P, Snow W, Parulkar G (2014) ONOS: Towards an open, distributed SDN OS. In: Proceedings of the Third Workshop on Hot Topics in Software Defined Networking, HotSDN’14, ACM, New York, pp 1–6

  18. Koponen T, Casado M, Gude N, Stribling J, Poutievski L, Zhu M, Ramanathan R, Iwata Y, Inoue H, Hama T, Shenker S (2010) Onix: a distributed control platform for large-scale production networks. In: Proceedings of the 9th USENIX Conference on Operating Systems Design and Implementation, OSDI’10, USENIX Association, Berkeley, pp 351–364

  19. Bari MF, Roy AR, Chowdhury SR, Zhang Q, Zhani MF, Ahmed R, Boutaba R (2013) Dynamic controller provisioning in software defined networks. In: Proceedings of the 9th International Conference on Network and Service Management (CNSM 2013), pp 18–25

  20. Rath HK, Revoori V, Nadaf SM, Simha A (2014) Optimal controller placement in software defined networks (SDN) using a non-zero-sum game. In: 2014 IEEE 15th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), pp 1–6

  21. Hu Y, Wendong W, Gong X, Que X, Shiduan C (2013) Reliability-aware controller placement for software-defined networks, In: 2013 IFIP/IEEE International Symposium on Integrated Network Management (IM 2013), pp 672–675

  22. Sallahi A, St-Hilaire M (2015) Optimal model for the controller placement problem in software defined networks. IEEE Commun Lett 19(1):30–33

    Article  Google Scholar 

  23. Lange S, Gebert S, Zinner T, Tran-Gia P, Hock D, Jarschel M, Hoffmann M (2015) Heuristic approaches to the controller placement problem in large scale SDN networks. IEEE Trans Netw Serv Manag 12(1):4–17

    Article  Google Scholar 

  24. Bennani MN, Menasce DA (2005) Resource allocation for autonomic data centers using analytic performance models. In: Proceedings of the Second International Conference on Automatic Computing, ICAC’05, IEEE Computer Society, Washington, pp 229–240

  25. Paton N, de Aragão MAT, Lee K, Fernandes AAA, Sakellariou R (2009) Optimizing utility in cloud computing through autonomic workload execution. Bull Tech Comm Data Eng 32(1):51–58

    Google Scholar 

  26. Anuradha VP, Sumathi D (2014) A survey on resource allocation strategies in cloud computing. In: 2014 International Conference on Information Communication and Embedded Systems (ICICES), Chennai, pp 1–7

  27. Minarolli D, Freisleben B (2011) Utility-based resource allocation for virtual machines in cloud computing. In: 2011 IEEE Symposium on Computers and Communications (ISCC), Kerkyra, pp 410–417

  28. Goudarzi H, Pedram M (2011) Maximizing profit in cloud computing system via resource allocation. In: 2011 31st International Conference on Distributed Computing Systems Workshops, Minneapolis, MN, pp 1–6

  29. Rogers J, Papaemmanouil O, Cetintemel U (2010) A generic auto-provisioning framework for cloud databases. In: 2010 IEEE 26th International Conference on Data Engineering Workshops (ICDEW), Long Beach, CA, pp 63–68

  30. Li C, Li L (2012) A resource selection scheme for QoS satisfaction and load balancing in ad hoc grid. J Supercomput 59:499–525

    Article  Google Scholar 

  31. Abawajy J, Fudzee MF, Hassan MM, Alrubaian M (2015) Service level agreement management framework for utility-oriented computing platforms. J Supercomput 71:4287–4303

    Article  Google Scholar 

  32. Kianfar K, Moslehi G, Yahyapour R (2015) A novel metaheuristic algorithm and utility function for QoS based scheduling in user-centric grid systems. J Supercomput 71:1143–1162

    Article  Google Scholar 

  33. Greenberg A, Hamilton JR, Jain N, Kandula S, Kim C, Lahiri P, Maltz DA, Patel P, Sengupta S (2009) VL2: a scalable and flexible data center network. SIGCOMM Comput Commun Rev ACM 39:51–62

    Article  Google Scholar 

  34. Al-Fares M, Loukissas A, Vahdat A (2008) A scalable, commodity data center network architecture. SIGCOMM Comput Commun Rev ACM 38:63–74

    Article  Google Scholar 

  35. Gross D, Shortle JF, Thompson JM, Harris CM (2008) Fundamentals of Queueing Theory, 4th edn. Wiley-Interscience, New York

    Book  MATH  Google Scholar 

  36. Jain R, Chiu D-M, Hawe WR (1984) A quantitative measure of fairness and discrimination for resource allocation in shared computer system. Eastern Research Laboratory, Digital Equipment Corporation, Hudson

    Google Scholar 

  37. Guo Z, Su M, Xu Y, Duan Z, Wang L, Hui S, Chao HJ (2014) Improving the performance of load balancing in software-defined networks through load variance-based synchronization. Comput. Networks 68:95–109 Communications and Networking in the Cloud

    Article  Google Scholar 

  38. Mirjalili S, Hashim SZM (2010) A new hybrid PSOGSA algorithm for function optimization. In: 2010 International Conference on Computer and Information Application (ICCIA), pp 374–377

  39. Mirjalili S, Lewis A (2016) The whale optimization algorithm. Adv Eng Softw 95:51–67

    Article  Google Scholar 

  40. Kirkpatrick S (1984) Optimization by simulated annealing: quantitative studies. J Stat Phys 34:975–986

    Article  MathSciNet  Google Scholar 

  41. Černý V (1985) Thermodynamical approach to the traveling salesman problem: an efficient simulation algorithm. J Optim Theory Appl 45:41–51

    Article  MathSciNet  MATH  Google Scholar 

  42. Glover F (1986) Applications of integer programming future paths for integer programming and links to artificial intelligence. Comput Oper Res 13(5):533–549. ISSN 0305-0548

    Article  MathSciNet  MATH  Google Scholar 

  43. Eiben AE, Raué PE, Ruttkay Z, Davidor Y, Schwefel H-P, Männer R (eds.) (1994) Genetic algorithms with multi-parent recombination. In: Parallel Problem Solving from Nature—PPSN III: International Conference on Evolutionary Computation The Third Conference on Parallel Problem Solving from Nature Jerusalem, Oct 9–14, 1994 Proceedings. Springer, Berlin, pp 78–87

  44. Colorni A, Dorigo M, Maniezzo V (1991) Distributed optimization by ant colonies. In: European Conference on Artificial Life, pp 134–142

  45. Kennedy J, Sammut C, Webb GI (eds) (2010) Particle swarm optimization encyclopedia of machine learning. Springer, New York, pp 760–766

    Google Scholar 

  46. Curtis AR, Mogul JC, Tourrilhes J, Yalagandula P, Sharma P, Banerjee S (2011) DevoFlow: scaling flow management for high-performance networks. In: Proceedings of the ACM SIGCOMM 2011 Conference, SIGCOMM’11, ACM, New York, NY, pp 254–265

  47. Cheng TY, Wang M, Jia X (2015) Qos-guaranteed controller placement in SDN. In: 2015 IEEE Global Communications Conference (GLOBECOM), pp 1–6

  48. Tavakoli A, Casado M, Koponen T, Shenker S (2009) Applying NOX to the datacenter. In: HotNets

  49. The Internet Traffic Archive. http://ita.ee.lbl.gov/index.html

  50. Floodlight project. http://www.projectfloodlight.org/floodlight/

  51. Mininet. http://mininet.org/

Download references

Author information

Authors and Affiliations

  1. Department of Electrical Engineering, Amirkabir University of Technology, Tehran, 15914, Iran

    Alireza Farshin & Saeed Sharifian

Authors
  1. Alireza Farshin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Saeed Sharifian
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Saeed Sharifian.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Farshin, A., Sharifian, S. MAP-SDN: a metaheuristic assignment and provisioning SDN framework for cloud datacenters. J Supercomput 73, 4112–4136 (2017). https://doi.org/10.1007/s11227-017-2001-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-017-2001-2

Keywords

Search

Navigation