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An SDN-enhanced load-balancing technique in the cloud system

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Abstract

The vast majority of Web services and sites are hosted in various kinds of cloud services, and ordering some level of quality of service (QoS) in such systems requires effective load-balancing policies that choose among multiple clouds. Recently, software-defined networking (SDN) is one of the most promising solutions for load balancing in cloud data center. SDN is characterized by its two distinguished features, including decoupling the control plane from the data plane and providing programmability for network application development. By using these technologies, SDN and cloud computing can improve cloud reliability, manageability, scalability and controllability. SDN-based cloud is a new type cloud in which SDN technology is used to acquire control on network infrastructure and to provide networking-as-a-service (NaaS) in cloud computing environments. In this paper, we introduce an SDN-enhanced Inter cloud Manager (S-ICM) that allocates network flows in the cloud environment. S-ICM consists of two main parts, monitoring and decision making. For monitoring, S-ICM uses SDN control message that observes and collects data, and decision-making is based on the measured network delay of packets. Measurements are used to compare S-ICM with a round robin (RR) allocation of jobs between clouds which spreads the workload equitably, and with a honeybee foraging algorithm (HFA). We see that S-ICM is better at avoiding system saturation than HFA and RR under heavy load formula using RR job scheduler. Measurements are also used to evaluate whether a simple queueing formula can be used to predict system performance for several clouds being operated under an RR scheduling policy, and show the validity of the theoretical approximation.

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References

  1. Al-Jaroodi J, Mohamed N (2011) DDFTP: dual-direction ftp. In: Proceedings of the 2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing. IEEE Computer Society, Newport Beach, CA, USA, pp 504–513

  2. Apostolopoulou D, Gross G, and Güler T (2013) Optimized ftr portfolio construction based on the identification of congested network elements. IEEE Trans Power Syst 28(4):4968–4978

    Article  Google Scholar 

  3. Berl A, Gelenbe E, Di Girolamo M, Giuliani G, De Meer H, Dang MQ, Pentikousis K (2010) Energy-efficient cloud computing. Comput J 53(7):1045–1051

    Article  Google Scholar 

  4. Bhardwaj S, Jain L, Jain S (2010) Cloud computing: a study of infrastructure as a service (iaas). Int J Eng Inf Technol 2(1):60–63

    Google Scholar 

  5. Brandt M, Khondoker R, Marx R, Bayarou K (2014) Security analysis of software defined networking protocolsopenflow, of-config and ovsdb. In: The 2014 IEEE Fifth International Conference on Communications and Electronics (ICCE 2014), DA NANG, Vietnam

  6. Carvalho M, Cirne W, Brasileiro F, Wilkes J (2014) Long-term slos for reclaimed cloud computing resources. In: Proceedings of the ACM Symposium on Cloud Computing. ACM, pp 1–13

  7. Choi J, Lee IW (2015) Energy ict convergence with big data services. J Korean Data Inf Sci Soc 26(5):1141–1154

    Google Scholar 

  8. Clay RW, Wild NR, Bird DJ, Dawson BR, Johnston M, Patrick R, Sewell A (1998) A cloud monitoring system for remote sites. Publ Astron Soc Aust 15(03):332–335

    Article  Google Scholar 

  9. Dixit A, Hao F, Mukherjee S, Lakshman T, Kompella R (2013) Towards an elastic distributed sdn controller. In: ACM SIGCOMM computer communication review, vol 43. ACM, pp 7–12

  10. Fang Y, Wang F, Ge J (2010) A task scheduling algorithm based on load balancing in cloud computing. In: Web information systems and mining. Springer, pp 271–277

  11. Fundation ON (2012) Software-defined networking: the new norm for networks. ONF White Paper

  12. Gelenbe E (2009) Steps toward self-aware networks. Commun ACM 52(7):66–75

    Article  Google Scholar 

  13. Gelenbe E (2012) Energy packet networks: smart electricity storage to meet surges in demand. In: Proceedings of the 5th International ICST Conference on Simulation Tools and Techniques, ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering), pp 1–7

  14. Gelenbe E, Lent R (2012) Trade-offs between energy and quality of service. In: Sustainable internet and ICT for sustainability (SustainIT), 2012. IEEE, pp 1–5

  15. Gelenbe E, Morfopoulou C (2011) A framework for energy-aware routing in packet networks. Comput J 54(6):850–859

    Article  Google Scholar 

  16. Giagkos A, Wilson MS (2013) Swarm intelligence to wireless ad hoc networks: adaptive honeybee foraging during communication sessions. Adapt Behav 21(6):501–515

    Article  Google Scholar 

  17. Guo L, Zhao S, Shen S, Jiang C (2012) Task scheduling optimization in cloud computing based on heuristic algorithm. J Netw 7(3):547–553

    Google Scholar 

  18. Gupta P, Seetharaman A, Raj JR (2013) The usage and adoption of cloud computing by small and medium businesses. Int J Inf Manag 33(5):861–874

    Article  Google Scholar 

  19. Hu J, Gu J, Sun G, Zhao T (2010) A scheduling strategy on load balancing of virtual machine resources in cloud computing environment. In: Parallel Architectures, Algorithms and Programming (PAAP), 2010 Third International Symposium. IEEE, pp 89–96

  20. Jafarian JH, Al-Shaer E, Duan Q (2012) Openflow random host mutation: transparent moving target defense using software defined networking. In: Proceedings of the first workshop on Hot topics in software defined networks. ACM, pp 127–132

  21. Jain R, Paul S (2013) Network virtualization and software defined networking for cloud computing: a survey. IEEE Commun Mag 51(11):24–31

    Article  Google Scholar 

  22. Jain S, Kumar A, Mandal S, Ong J, Poutievski L, Singh A, Venkata S, Wanderer J, Zhou J, Zhu M et al (2013) B4: Experience with a globally-deployed software defined wan. ACM SIGCOMM Comput Commun Rev 43(4):3–14

    Article  Google Scholar 

  23. Joo JY, Ilic M (2014) Distributed scheduling of demand resources in a congested network. In: PES General Meeting—Conference and Exposition, 2014 IEEE. IEEE, pp 1–5

  24. Kang B (2016) Network-based job dispatching in the cloud. In: Information Sciences and Systems 2015. Springer, pp 233–240

  25. Kang B, Choo H (2016a) A cluster-based decentralized job dispatching for the large-scale cloud. EURASIP J Wirel Commun Netw 1:1–8

    Google Scholar 

  26. Kang B, Choo H (2016) A deep-learning-based emergency alert system. ICT Express 2(2):67–70

    Article  Google Scholar 

  27. Kang B, Kwon N, Choo H (2016) Developing route optimization-based pmipv6 testbed for reliable packet transmission. IEEE Access 4:1039–1049

    Article  Google Scholar 

  28. Kang B, Myoung S, Choo H (2016) Distributed degree-based link scheduling for collision avoidance in wireless sensor networks. IEEE Access 4:7452–7468

    Article  Google Scholar 

  29. Kansal NJ, Chana I (2012) Cloud load balancing techniques: a step towards green computing. IJCSI Int J Comput Sci Issues 9(1):238–246

    Google Scholar 

  30. Khinchin AY (1967) The mathematical theory of a stationary queue. Tech. rep, DTIC Document

  31. Kim H, Feamster N (2013) Improving network management with software defined networking. IEEE Commun Mag 51(2):114–119

    Article  Google Scholar 

  32. Kingman J (2009) The first erlang century-and the next. Queueing Syst 63(1–4):3–12

    Article  MathSciNet  Google Scholar 

  33. Kolb L, Thor A, Rahm E (2012) Load balancing for mapreduce-based entity resolution. In: Data Engineering (ICDE), 2012 IEEE 28th International Conference. IEEE, pp 618–629

  34. Koponen T, Casado M, Gude N, Stribling J (2014) Distributed control platform for large-scale production networks. US Patent 8,830,823

  35. Lara A, Kolasani A, Ramamurthy B (2014) Network innovation using openflow: a survey. IEEE Commun Surv Tutor 16(1):493–512

    Article  Google Scholar 

  36. Lee R, Jeng B (2011) Load-balancing tactics in cloud. In: Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), 2011 International Conference. IEEE, pp 447–454

  37. Li H, Xue Z, Ellmore TM, Frye RE, Wong ST (2014) Network-based analysis reveals stronger local diffusion-based connectivity and different correlations with oral language skills in brains of children with high functioning autism spectrum disorders. Hum Brain Mapp 35(2):396–413

    Article  Google Scholar 

  38. Li JF, Peng J (2011) Task scheduling algorithm based on improved genetic algorithm in cloud computing environment. Jisuanji Yingyong J Comput Appl 31(1):184–186

    MathSciNet  Google Scholar 

  39. Li K, Xu G, Zhao G, Dong Y, Wang D (2011) Cloud task scheduling based on load balancing ant colony optimization. In: Chinagrid Conference (ChinaGrid), 2011 Sixth Annual. IEEE, pp 3–9

  40. Lu X, Gao S, Ben-Elia E, Pothering R (2014) Travelers’ day-to-day route choice behavior with real-time information in a congested risky network. Math Popul Stud 21(4):205–219

    Article  MathSciNet  Google Scholar 

  41. Mehta H, Kanungo P, Chandwani M (2011) Decentralized content aware load balancing algorithm for distributed computing environments. In: Proceedings of the International Conference and Workshop on Emerging Trends in Technology. ACM, pp 370–375

  42. Nakai AM, Madeira E, Buzato LE (2011) Load balancing for internet distributed services using limited redirection rates. In: Dependable Computing (LADC), 2011 5th Latin-American Symposium. IEEE, pp 156–165

  43. Nakrani S, Tovey C (2004) On honey bees and dynamic server allocation in internet hosting centers. Adapt Behav 12(3–4):223–240

    Article  Google Scholar 

  44. Ni J, Huang Y, Luan Z, Zhang J, Qian D (2011) Virtual machine mapping policy based on load balancing in private cloud environment. In: Cloud and Service Computing (CSC), 2011 International Conference. IEEE, pp 292–295

  45. Nishant K, Sharma P, Krishna V, Gupta C, Singh KP, Nitin N, Rastogi R (2012) Load balancing of nodes in cloud using ant colony optimization. In: Computer Modelling and Simulation (UKSim), 2012 UKSim 14th International Conference. IEEE, pp 3–8

  46. Nunes BAA, Mendonca M, Nguyen XN, Obraczka K, Turletti T (2014) A survey of software-defined networking: past, present, and future of programmable networks. IEEE Commun Surv Tutor 16(3):1617–1634

    Article  Google Scholar 

  47. Pollaczek F (1930) Über eine aufgabe der wahrscheinlichkeitstheorie. i. Mathematische Zeitschrift 32(1):64–100

    Article  MathSciNet  Google Scholar 

  48. Radojevic B, Zagar M (2011) Analysis of issues with load balancing algorithms in hosted (cloud) environments. In: MIPRO, 2011 proceedings of the 34th international convention. IEEE, pp 416–420

  49. Randles M, Lamb D, Taleb-Bendiab A (2010) A comparative study into distributed load balancing algorithms for cloud computing. In: Advanced Information Networking and Applications Workshops (WAINA), 2010 IEEE 24th International Conference. IEEE, pp 551–556

  50. Ren X, Lin R, Zou H (2011) A dynamic load balancing strategy for cloud computing platform based on exponential smoothing forecast. In: Cloud Computing and Intelligence Systems (CCIS), 2011 IEEE International Conference. IEEE, pp 220–224

  51. Rodero-Merino L, Vaquero LM, Gil V, Galán F, Fontán J, Montero RS, Llorente IM (2010) From infrastructure delivery to service management in clouds. Future Gener Comput Syst 26(8):1226–1240

    Article  Google Scholar 

  52. Sakata M, Noguchi S, Oizumi J (1971) An analysis of the m/g/1 queue under round-robin scheduling. Oper Res 19(2):371–385

    Article  Google Scholar 

  53. Selvarani S, Sadhasivam GS (2010) Improved cost-based algorithm for task scheduling in cloud computing. In: Computational Intelligence and Computing Research (ICCIC), 2010 IEEE International Conference. IEEE, pp 1–5

  54. Sezer S, Scott-Hayward S, Chouhan PK, Fraser B, Lake D, Finnegan J, Viljoen N, Miller M, Rao N (2013) Are we ready for sdn? implementation challenges for software-defined networks. IEEE Commun Mag 51(7):36–43

    Article  Google Scholar 

  55. Shao J, Wei H, Wang Q, Mei H (2010) A runtime model based monitoring approach for cloud. In: Cloud Computing (CLOUD), 2010 IEEE 3rd International Conference. IEEE, pp 313–320

  56. Sotomayor B, Montero RS, Llorente IM, Foster I (2009) Virtual infrastructure management in private and hybrid clouds. Internet Comput IEEE 13(5):14–22

    Article  Google Scholar 

  57. Venkata Krishna P (2013) Honey bee behavior inspired load balancing of tasks in cloud computing environments. Appl Soft Comput 13(5):2292–2303

    Article  Google Scholar 

  58. Wang SC, Yan KQ, Liao WP, Wang SS (2010) Towards a load balancing in a three-level cloud computing network. In: Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference, vol 1. IEEE, pp 108–113

  59. Wu TY, Lee WT, Lin YS, Lin YS, Chan HL, Huang JS (2012) Dynamic load balancing mechanism based on cloud storage. In: Computing, Communications and Applications Conference (ComComAp), 2012. IEEE, pp 102–106

  60. Xuejie Z, Zhijian W, Feng X (2013) Reliability evaluation of cloud computing systems using hybrid methods. Intell Autom Soft Comput 19(2):165–174

    Article  Google Scholar 

  61. Zhang Z, Zhang X (2010) A load balancing mechanism based on ant colony and complex network theory in open cloud computing federation. In: Industrial Mechatronics and Automation (ICIMA), 2010 2nd International Conference, vol 2. IEEE, pp 240–243

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Acknowledgements

This work was supported by the G-ITRC Program under Grant IITP-2015R6812-15-0001, ICT R&D program under Grant B0101-15-1366, and the NRF Korea under Grant 2010-0020210.

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  1. Department of Computer Science and Engineering, Sungkyunkwan University, Suwon, 440-746, Korea

    Byungseok Kang & Hyunseung Choo

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  1. Byungseok Kang
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Correspondence to Byungseok Kang.

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Kang, B., Choo, H. An SDN-enhanced load-balancing technique in the cloud system. J Supercomput 74, 5706–5729 (2018). https://doi.org/10.1007/s11227-016-1936-z

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