Leveraging Software-Defined Networks for Load Balancing in Data Centre Networks using Linear Programming

Authors

  • Vani Kurugod Aswathanarayana Reddy
  • Ramamohan Babu Kasturi Nagappasetty

DOI:

https://doi.org/10.47839/ijc.22.3.3237

Keywords:

Software-defined networking, Quality of Service, Load balancing, Open Flow, Data Centre

Abstract

A rapid increase in the number of online applications has led to exponential growth in traffic. In data centers, it is hard to dynamically balance such huge amounts of traffic while keeping track of server data. A load-balancing strategy is an effective solution for distributing such huge amounts of traffic. The major contribution of this research work is to improve the performance of the network by designing a dynamic load balancing algorithm based on server data using SDN, reduction of controller overhead and optimizing energy consumption in a server pool. The problem is formulated using a Linear Programming mathematical model. In order to demonstrate the effectiveness and feasibility of the proposed technique, the experimental setup is deployed using real hardware components such as a Zodiac-Fx switch, Ryu controller and various web servers in the data center network. This proposed scheme is compared with round-robin and random load balancing mechanisms. The experimental results show that the performance is improved by 87.4% while saving 78% of the energy.

References

G. Kumar et al., “Swift: Delay is simple and effective for congestion control in the datacenter,” Proceedings of the ACM SIGCOMM, 2020, pp. 514–528. https://doi.org/10.1145/3387514.3406591.

A. Saeed et al., “Annulus: A dual congestion control loop for datacenter and WAN traffic aggregates,” Proceedings of the 2020 Annu. Conf. ACM Spec. Interes. Gr. Data Commun. Appl. Technol. Archit. Protoc. Comput. Commun. SIGCOMM 2020, pp. 735–749, 2020, https://doi.org/10.1145/3387514.3405899.

S. Hu et al., “Aeolus: A building block for proactive transport in datacenter networks,” IEEE/ACM Trans. Netw., vol. PP, no. January, pp. 1–15, 2021, https://doi.org/10.1109/TNET.2021.3119986.

T. Zhang et al., “Rethinking fast and friendly transport in data center networks,” IEEE/ACM Trans. Netw., vol. 28, no. 5, pp. 2364–2377, 2020, https://doi.org/10.1109/TNET.2020.3012556.

G. Zeng et al., “Congestion control for cross-datacenter networks,” Proceedings of the Int. Conf. Netw. Protoc. ICNP, vol. 2019 October, no. January, 2019, https://doi.org/10.1109/ICNP.2019.8888042.

M. Karakus and A. Durresi, “Quality of Service (QoS) in Software Defined Networking (SDN): A survey,” J. Netw. Comput. Appl., vol. 80, pp. 200–218, 2017, https://doi.org/10.1016/j.jnca.2016.12.019.

M. M. Tajiki, B. Akbari, and N. Mokari, “Optimal Qos-aware network reconfiguration in software defined cloud data centers,” Comput. Networks, vol. 120, pp. 71–86, 2021, https://doi.org/10.1016/j.comnet.2017.04.003.

N. Feamster, J. Rexford, and E. Zegura, “The road to SDN: An intellectual history of programmable networks,” Comput. Commun. Rev., vol. 44, pp. 87–98, 2014, https://doi.org/10.1145/2602204.2602219.

P. Göransson, C. Black, and T. Culver, The OpenFlow Specification. 2017. https://doi.org/10.1016/B978-0-12-804555-8.00005-3.

S. Huang, J. Griffioen, and K. L. Calvert, “Network hypervisors: Enhancing SDN infrastructure,” in Computer Communications, June 2014, vol. 46, pp. 87–96. https://doi.org/10.1016/j.comcom.2014.02.002.

M. Hamdan et al., “A comprehensive survey of load balancing techniques in software-defined network,” J. Netw. Comput. Appl., vol. 174, no. October 2020, p. 102856, 2021, https://doi.org/10.1016/j.jnca.2020.102856.

B. P. Mulla, C. Rama Krishna, and R. K. Tickoo, “Load balancing algorithm for efficient VM allocation in heterogeneous cloud,” Int. J. Comput. Networks Commun., vol. 12, no. 1, pp. 83–96, 2020, https://doi.org/10.5121/ijcnc.2020.12106.

Z. Benlalia, K. Abouelmehdi, A. Beni-hssane, and A. Ezzati, “Comparing load balancing algorithms for web application in cloud environment,” Indones. J. Electr. Eng. Comput. Sci., vol. 17, no. 2, p. 1104, 2020, https://doi.org/10.11591/ijeecs.v17.i2.pp1104-1108.

T. E. Ali, A. H. Morad, and M. A. Abdala, “Load balance in data center SDN networks,” Int. J. Electr. Comput. Eng., vol. 8, no. 5, pp. 3084–3091, 2018, https://doi.org/10.11591/ijece.v8i5.pp3084-3091.

A. A. Alkhatib, A. Alsabbagh, R. Maraqa, and S. Alzubi, “Load balancing techniques in cloud computing: Extensive review,” Adv. Sci. Technol. Eng. Syst. J., vol. 6, no. 2, pp. 860–870, 2021, https://doi.org/10.25046/aj060299.

M. R. Belgaum, S. Musa, M. M. Alam, and M. M. Su’Ud, “A systematic review of load balancing techniques in software-defined networking,” IEEE Access, vol. 8, pp. 98612–98636, 2020, https://doi.org/10.1109/ACCESS.2020.2995849.

S. Kaur, J. Singh, K. Kumar, and N. S. Ghumman, “Round-robin based load balancing in software defined networking,” Proceedings of the 2015 Int. Conf. Comput. Sustain. Glob. Dev. INDIACom 2015, pp. 2136–2139, 2015.

F. Rhamdani, N. A. Suwastika, and M. A. Nugroho, “Equal-cost multipath routing in data center network based on software defined network,” Proceedings of the 2018 6th International Conference on Information and Communication Technology (ICoICT), 2018, pp. 222–226. https://doi.org/10.1109/ICoICT.2018.8528730.

H. Zhong, Y. Fang, and J. Cui, “LBBSRT: An efficient SDN load balancing scheme based on server response time,” Futur. Gener. Comput. Syst., vol. 68, pp. 183–190, 2017, https://doi.org/10.1016/j.future.2016.10.001.

K. Soleimanzadeh, M. Ahmadi, and M. Nassiri, “SD-WLB: An SDN-aided mechanism for web load balancing based on server statistics,” ETRI J., vol. 41, no. 2, pp. 197–206, 2019, https://doi.org/10.4218/etrij.2018-0188.

S. Wilson Prakash and P. Deepalakshmi, “DServ-LB: Dynamic server load balancing algorithm,” Int. J. Commun. Syst., vol. 32, no. 1, pp. 1–11, 2019, https://doi.org/10.1002/dac.3840.

V. Koryachko, D. Perepelkin, and V. Byshov, “Approach of dynamic load balancing in software defined networks with QoS,” Proceedings of the 2017 6th Mediterranean Conference on Embedded Computing (MECO), 2017, pp. 1–5. https://doi.org/10.1109/MECO.2017.7977237.

A. S. AbdelRahman and A. B. El-Sisi, “Dynamic load balancing technique for software defined Wi-Fi networks,” Proceedings of the 2017 12th International Conference on Computer Engineering and Systems (ICCES), Cairo, Egypt, 2017, pp. 289-294, https://doi.org/10.1109/ICCES.2017.8275321.

H. Long, Y. Shen, M. Guo, and F. Tang, “LABERIO: Dynamic load-balanced Routing in OpenFlow-enabled Networks,” Proceedings of the 2013 IEEE 27th International Conference on Advanced Information Networking and Applications (AINA), 2013, pp. 290–297. https://doi.org/10.1109/AINA.2013.7.

F. S. Fizi and S. Askar, “A novel load balancing algorithm for software defined network based datacenters,” Proceedings of the 2016 International Conference on Broadband Communications for Next Generation Networks and Multimedia Applications, CoBCom 2016, 2016, pp. 1–6. https://doi.org/10.1109/COBCOM.2016.7593506.

Y. Gao and L. Yu, “Energy-aware load balancing in heterogeneous cloud data centers,” Proceedings of the ACM Int. Conf. Proceeding Ser., 2017, pp. 80–84, https://doi.org/10.1145/3034950.3035000.

T. Malbasic, P. D. Bojovic, Z. Bojovic, J. Suh, and D. Vujosevic, “Hybrid SDN networks: A multi-parameter server load balancing scheme,” J. Netw. Syst. Manag., vol. 30, no. 2, pp. 1–28, 2022, https://doi.org/10.1007/s10922-022-09642-y.

B. B. Rodrigues, A. C. Riekstin, G. C. Januario, V. T. Nascimento, T. C. M. B. Carvalho, and C. Meirosu, “GreenSDN: Bringing energy efficiency to an SDN emulation environment,” Proceedings of the 2015 IFIP/IEEE Int. Symp. Integr. Netw. Manag. IM 2015, pp. 948–953, 2015, https://doi.org/10.1109/INM.2015.7140416.

Y. H. Chen, T. L. Chin, C. Y. Huang, S. H. Shen, and R. Y. Huang, “Time efficient energy-aware routing in software defined networks,” Proceedings of the 2018 IEEE 7th Int. Conf. Cloud Networking, CloudNet 2018, pp. 1–7, 2018, https://doi.org/10.1109/CloudNet.2018.8549457.

J. Light, “Green networking: A simulation of energy efficient methods,” Procedia Comput. Sci., vol. 171, no. 2019, pp. 1489–1497, 2020, https://doi.org/10.1016/j.procs.2020.04.159.

S. Rout, K. S. Sahoo, S. S. Patra, B. Sahoo, and D. Puthal, “Energy efficiency in software defined networking: A survey,” SN Comput. Sci., vol. 2, no. 4, pp. 1–15, 2021, https://doi.org/10.1007/s42979-021-00659-9.

Y. Narimani, E. Zeinali, and A. Mirzaei, “QoS-aware resource allocation and fault tolerant operation in hybrid SDN using stochastic network calculus,” Phys. Commun., vol. 53, Aug. 2022, https://doi.org/10.1016/j.phycom.2022.101709.

S. S. Patra, R. Govindaraj, S. Chowdhury, M. A. Shah, R. Patro, and S. Rout, “Energy efficient end device aware solution through SDN in edge-cloud platform,” IEEE Access, vol. 10, no. November, pp. 115192–115204, 2022, https://doi.org/10.1109/ACCESS.2022.3218328.

S. Asadollahi, B. Goswami, and M. Sameer, “Ryu controller’s scalability experiment on software defined networks,” Proceedings of the 2018 IEEE International Conference on Current Trends in Advanced Computing, ICCTAC 2018, 2018, pp. 1–5. https://doi.org/10.1109/ICCTAC.2018.8370397.

S. Wang, K. G. Chavez, S. Kandeepan, and P. Zanna, “The smallest software defined network testbed in the world: Performance and security,” Proceedings of the IEEE/IFIP Network Operations and Management Symposium: Cognitive Management in a Cyber World, NOMS 2018, 2018, pp. 1–2. https://doi.org/10.1109/NOMS.2018.8406116.

A. Chakib-Belgaid, “pyRAPL,” 2019. [Online]. Available at: https://pyrapl.readthedocs.io/en/latest/#

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Published

2023-10-01

How to Cite

Reddy, V. K. A., & Nagappasetty, R. B. K. (2023). Leveraging Software-Defined Networks for Load Balancing in Data Centre Networks using Linear Programming. International Journal of Computing, 22(3), 404-411. https://doi.org/10.47839/ijc.22.3.3237

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