With the continuous expansion of the data center network scale, changing network requirements, and increasing pressure on network bandwidth, the traditional network architecture can no longer meet people’s needs. The development of software defined networks has brought new opportunities and challenges to future networks. The data and control separation characteristics of SDN improve the performance of the entire network. Researchers have integrated SDN architecture into data centers to improve network resource utilization and performance. This paper first introduces the basic concepts of SDN and data center networks. Then it discusses SDN-based load balancing mechanisms for data centers from different perspectives. Finally, it summarizes and looks forward to the study on SDN-based load balancing mechanisms and its development trend.
References
[1]
Zhang, J. and Li, N. (2022) Research on Load Optimization of Software-Defined Network Based on Delay and Load. 2022 IEEE 2nd International Conference on Networking, Communications and Information Technology (NetCIT), Manchester, 26-27 December 2022, 254-259.
[2]
Li, S., Xin, Z., Xu, X. and Zhang, Z. (2023) Load Balancing Algorithm of SDN Controller Based on Dynamic Threshold. 2023 IEEE 3rd Asia-Pacific Conference on Communications Technology and Computer Science (ACCTCS), Shenyang, 25-27 February 2023, 517-520. https://doi.org/10.1109/ACCTCS58815.2023.00105
[3]
Liu, Z.P., Ren, S.S., Li, M., Wang, X.P. and Li, X.F. (2021) Software Defines Dynamic Traffic Scheduling Scheme for Network Data Center. Journal of Jilin University: Engineering and Technology Edition, 51, 1040-1047.
[4]
Wang, Y.M., Wang, X., Dong, Y., Zhang, S.H. and Shi, X.L. (2020) Data Center Traffic Scheduling Strategy Based on Fibonacci Tree Optimization Algorithm. Journal on Communications, No. 6, 112-127.
[5]
Hamdan, M., Khan, S., Abdelaziz, A., Sadiah, S., Shaikh-Husin, et al. (2021) DPLBAnt: Improved Load Balancing Technique Based on Detection and Rerouting of Elephant Flows in Software-Defined Networks. Computer Communications, 180, 315-327. https://doi.org/10.1016/j.comcom.2021.10.013
[6]
Abdollahi, S., Deldari, A., Asadi, H., Montazerolghaem, A. and Mazinani, S.M. (2021) Flow-Aware Forwarding in SDN Datacenters Using a Knapsack-PSO-Based Solution. IEEE Transactions on Network and Service Management, 18, 2902-2914. https://doi.org/10.1109/TNSM.2021.3064974
[7]
Khairi, M.H.H., Ariffin, S.H.S., Latiff, N.M.A.A., Yusof, K.M., Hassan, M.K., Al-Dhief, F.T. and Hamzah, M. (2021) Detection and Classification of Conflict Flows in SDN Using Machine Learning Algorithms. IEEE Access, 9, 76024-76037. https://doi.org/10.1109/ACCESS.2021.3081629
[8]
Xie, S.X., Hu, G.Y., Xing, C.Y. and Liu, Y.Q. (2023) Online Elephant Flow Prediction for Load Balancing in Programmable Switch Based DCN. IEEE Transactions on Network and Service Management. https://doi.org/10.1109/TNSM.2023.3318752
[9]
Sun, X. and Yang, G. (2022) Research on Load Balancing Strategy of Data Center Based on Yen Algorithm in SDN. 2022 IEEE 5th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC), Vol. 5, 1243-1247. https://doi.org/10.1109/IMCEC55388.2022.10020139
[10]
Diel, G., Miers, C.C., Pillon, M.A. and Koslovski, G.P. (2023) RSCAT: Towards Zero Touch Congestion Control Based on Actor-Critic Reinforcement Learning and Software-Defined Networking. Journal of Network and Computer Applications, 215, Article ID: 103639. https://doi.org/10.1016/j.jnca.2023.103639
[11]
Liu, Y., Zhang, J., Li, W., Wu, Q. and Li, P. (2021) Load Balancing Oriented Predictive Routing Algorithm for Data Center Networks. Future Internet, 13, Article No. 54. https://doi.org/10.3390/fi13020054
[12]
Begam, G.S., Sangeetha, M. and Shanker, N.R. (2022) Load Balancing in DCN Servers through SDN Machine Learning Algorithm. Arabian Journal for Science and Engineering, 47, 1423-1434. https://doi.org/10.1007/s13369-021-05911-1
[13]
Nougnanke, K.B., Labit, Y., Bruyere, M., Ferlin, S. and Aïvodji, U. (2021) Learning-Based Incast Performance Inference in Software-Defined Data Centers. 2021 24th IEEE Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN), Paris, 1-4 March 2021, 118-125. https://doi.org/10.1109/ICIN51074.2021.9385546
[14]
Hai-Anh, T.R.A.N., Souihi, S. and Mellouk, A. (2021) Towards a Novel Congestion Notification Algorithm for a Software-Defined Data Center Networks. 2021 IFIP/IEEE International Symposium on Integrated Network Management (IM), Bordeaux, 18-20 May 2021, 99-106.
[15]
Shaikh, M.R.R. (2023) Bayesian Network Based Optimal Load Balancing in Software Defined Networks. 2023 IEEE International Conference on Emerging Smart Computing and Informatics (ESCI), Pune, 1-3 March 2023, 1-5. https://doi.org/10.1109/ESCI56872.2023.10099730
[16]
Wei, Z., Li, Q., Zhu, K., Zhou, J., Zou, L., Jiang, Y. and Xiao, X. (2022) DiffTREAT: Differentiated Traffic Scheduling Based on RNN in Data Centers. IEEE Transactions on Cloud Computing, 3, 2407-2419. https://doi.org/10.1109/TCC.2022.3206593
[17]
Gonzalez-Diaz, S., Marks, R., Rojas, E., De La Oliva, A. and Gazda, R. (2021) Stateless Flow-Zone Switching Using Software-Defined Addressing. IEEE Access, 9, 68343-68365. https://doi.org/10.1109/ACCESS.2021.3077955
[18]
Zhou, Q., Yu, J. and Li, D. (2021) A Dynamic and Lightweight Framework to Secure Source Addresses in the SDN-Based Networks. Computer Networks, 193, Article ID: 108075. https://doi.org/10.1016/j.comnet.2021.108075
[19]
Shen, G., Li, Q., Shi, W., Jiang, Y., Zhang, P., Gu, L. and Xu, M. (2022) Modeling and Optimization of the Data Plane in the SDN-Based DCN by Queuing Theory. Journal of Network and Computer Applications, 207, Article ID: 103481. https://doi.org/10.1016/j.jnca.2022.103481
[20]
Zhang, Q., Chen, J., Gao, D. and Wang, X. (2022) Intent-Based Service Policy Conflict Management Algorithm. 2022 IEEE/CIC International Conference on Communications in China (ICCC), Foshan, 11-13 August 2022, 19-24. https://doi.org/10.1109/ICCC55456.2022.9880783
[21]
Liang, S. and Su, J. (2022) Detection of SDN Flow Rule Conflicts Based on Knowledge Graph. In: Quan, W., Ed., International Conference on Emerging Networking Architecture and Technologies, Springer Nature, Singapore, 93-104. https://doi.org/10.1007/978-981-19-9697-9_8
[22]
Zhu, S.X., Long, Y.F., Sun, G.L. and Li, C.F. (2022) Improved Ant Colony Algorithm for Network Flow Scheduling in SDN Data Center. Journal of Harbin University of Science & Technology, 27, 1-7.
[23]
Zheng, H., Guo, J., Zhou, Q., Peng, Y. and Chen, Y. (2023) Application of Improved Ant Colony Algorithm in Load Balancing of Software-Defined Networks. The Journal of Supercomputing, 79, 7438-7460. https://doi.org/10.1007/s11227-022-04957-8
[24]
Dai, R.R., Li, H.H. and Fu, X.L. (2022) Data Center Flow Scheduling Mechanism based on Differential Evolution and Ant Colony Optimization Algorithm. Journal of Computer Applications, 42, 3863.
[25]
Ma, S.Q., Tang, H., Li, Y. and Lei, Y.J. (2021) A Traffic Scheduling Strategy Based on Particle Swarm Optimization in Data Center Network. Telecommunication Engineering, 61, 865-871.
[26]
Xu, H.L., Yang, G.Q. and Jiang, Z.J. (2021) Data Center Adaptive Multi-Path Load Balancing Algorithm Based on Software Defined Network. Journal of Computer Applications, 41, 1160-1164.
[27]
Ye, Z., Sun, G. and Guizani, M. (2023) ILBPS: An Integrated Optimization Approach Based on Adaptive Load-Balancing and Heuristic Path Selection in SDN. IEEE Internet of Things Journal. https://doi.org/10.1109/JIOT.2023.3309832
[28]
Perepelkin, D. and Nguyen, T. (2022) Research of Multipath Routing and Load Balancing Processes in Software Defined Networks Based on Artificial Bee Colony Algorithm. 2022 IEEE ELEKTRO (ELEKTRO), Krakow, 23-26 May 2022, 1-6. https://doi.org/10.1109/ELEKTRO53996.2022.9803416
[29]
Perepelkin, D., Ivanchikova, M. and Nguyen, T. (2023) Research of Multipath Routing and Load Balancing Processes in Software Defined Networks Based on Bird Migration Algorithm. 2023 IEEE International Russian Smart Industry Conference (SmartIndustryCon), Sochi, 27-31 March 2023, 247-252. https://doi.org/10.1109/SmartIndustryCon57312.2023.10110788
[30]
Balakiruthiga, B. and Deepalakshmi, P. (2021) (ITMP)-Intelligent Traffic Management Prototype Using Reinforcement Learning Approach for Software Defined Data Center (SDDC). Sustainable Computing: Informatics and Systems, 32, Article ID: 100610. https://doi.org/10.1016/j.suscom.2021.100610
[31]
Gao, Y., Gao, X. and Chen, G. (2022) MetisRL: A Reinforcement Learning Approach for Dynamic Routing in Data Center Networks. In: Bhattacharya, A., et al., Eds., International Conference on Database Systems for Advanced Applications, Springer International Publishing, Cham, 615-622. https://doi.org/10.1007/978-3-031-00126-0_44
[32]
Yang, W., Qin, Y. and Yang, Z. (2022) A Reinforcement Learning Based Data Storage and Traffic Management in Information-Centric Data Center Networks. Mobile Networks and Applications, 27, 266-275. https://doi.org/10.1007/s11036-020-01629-w
[33]
Zeng, X., Wu, L., Li, Z. and Jing, Y. (2021) Deep Reinforcement Learning with Graph Convolutional Networks for Load Balancing in SDN-Based Data Center Networks. 2021 IEEE 18th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP), Chengdu, 17-19 December 2021, 344-352.
[34]
Liu, W.X., Cai, J., Chen, Q.C. and Wang, Y. (2021) DRL-R: Deep Reinforcement Learning Approach for Intelligent Routing in Software-Defined Data-Center Networks. Journal of Network and Computer Applications, 177, Article ID: 102865. https://doi.org/10.1016/j.jnca.2020.102865
[35]
Xu, Z., Lu, Y., Li, J., Ma, X. and Qian, L. (2022) Tailor: Datacenter Load Balancing for Accelerating Distributed Deep Learning. 2021 IEEE 9th International Conference on Advanced Cloud and Big Data (CBD), Xi’an, 15-17 October 2021, 45-50. https://doi.org/10.1109/CBD54617.2021.00017
[36]
Zhao, C., Ye, M., Xue, X., Lv, J., Jiang, Q. and Wang, Y. (2022) DRL-M4MR: An Intelligent Multicast Routing Approach Based on DQN Deep Reinforcement Learning in SDN. Physical Communication, 55, Article ID: 101919. https://doi.org/10.1016/j.phycom.2022.101919
[37]
Sharma, A., Tokekar, S. and Varma, S. (2023) Meta-Reinforcement Learning Based Resource Management in Software Defined Networks Using Bayesian Network. 2023 IEEE 3rd International Conference on Technology, Engineering, Management for Societal Impact Using Marketing, Entrepreneurship and Talent (TEMSMET), Mysuru, 10-11 February 2023, 1-6. https://doi.org/10.1109/TEMSMET56707.2023.10150107
[38]
Gao, M., Pan, T., Song, E., Yang, M., Huang, T. and Liu, Y. (2022) Power-Aware Traffic Engineering for Data Center Networks via Deep Reinforcement Learning. GLOBECOM 2022-2022 IEEE Global Communications Conference, Rio de Janeiro, 4-8 December 2022, 6055-6060. https://doi.org/10.1109/GLOBECOM48099.2022.10001013
[39]
Wu, G. (2022) Deep Reinforcement Learning Based Multi-Layered Traffic Scheduling Scheme in Data Center Networks. Wireless Networks, 1-12. https://doi.org/10.1007/s11276-021-02883-w
[40]
Kandil, M., Awad, M.K., Alotaibi, E.M. and Mohammadi, R. (2022) Q-Learning and Simulated Annealing-Based Routing for Software-Defined Networks. 2022 IEEE International Conference on Computer and Applications (ICCA), Cairo, 20-22 December 2022, 1-10. https://doi.org/10.1109/ICCA56443.2022.10039651
[41]
Yang, X., et al. (2020) An Effective Routing Mechanism Based on Fuzzy Logic for Software-Defined Data Center Networks. 2020 IEEE 6th International Conference on Computer and Communications (ICCC), Chengdu, 11-14 December 2020, 1793-1798. https://doi.org/10.1109/ICCC51575.2020.9344964
[42]
Huang, B. and Dong, S. (2020) An Enhanced Scheduling Framework for Elephant Flows in SDN-Based Data Center Networks. 2020 IEEE Symposium on Computers and Communications (ISCC), Rennes, 7-10 July 2020, 1-7. https://doi.org/10.1109/ISCC50000.2020.9219688
[43]
Chang, Y.K., Wang, H.Y. and Lin, Y.H. (2021) A Congestion Aware Multi-Path Label Switching in Data Centers Using Programmable Switches. 2021 IEEE International Conference on Networking, Architecture and Storage (NAS), Riverside, 24-26 October 2021, 1-8. https://doi.org/10.1109/NAS51552.2021.9605422
[44]
Li, Y, Tang, H, and Ma, S.Q. (2021) Multi-Path Scheduling Algorithm Based on Segment Routing in SDN. Application Research of Computers, 38, 1514-1519.
[45]
Zhou, J.X., Zhang, Z.P. and Zhou, N. (2020) Load Balancing Technology of Segment Routing Based on CKSP. Computer Science, 47, 256.
[46]
Gao, X.C., Liu, W., Wang, Q.L. and Zhang, X. (2023) SDN-Based Hybrid Segmented Routing Probabilistic Flow Scheduling Mechanism. Application Research of Computers, 40, 3382-3387.
[47]
Liu, Y., Gu, H., Zhou, Z. and Wang, N. (2022) RSLB: Robust and Scalable Load Balancing in Software-Defined Data Center Networks. IEEE Transactions on Network and Service Management, 19, 4706-4720. https://doi.org/10.1109/TNSM.2022.3192133
[48]
Ha, N.V., Tuan, T.A. and Nguyen, T.T.T. (2022) Fairness Enhanced Dynamic Routing Protocol in Software-Defined Networking. 2022 9th IEEE NAFOSTED Conference on Information and Computer Science (NICS), Ho Chi Minh City, 31 October-1 November 2022, 111-116. https://doi.org/10.1109/NICS56915.2022.10013394
[49]
Zaher, M., Alawadi, A.H. and Molnár, S. (2021) Sieve: A Flow Scheduling Framework in SDN Based Data Center Networks. Computer Communications, 171, 99-111. https://doi.org/10.1016/j.comcom.2021.02.013
[50]
Zuo, P. and Shu, Y.A. (2021) Dynamic Multi-Path Load Balancing Method Based on Feedforward Neural in DCN. Computer Engineering, 47, 113-119.
[51]
Gutiérrez, S.A., Botero, J.F. and Branch-Bedoya, J.W. (2023) An Adaptable and Agnostic Flow Scheduling Approach for Data Center Networks. Journal of Network and Systems Management, 31, Article No. 12. https://doi.org/10.1007/s10922-022-09701-4
[52]
Tang, Q., Yang, R. and Guo, Y. (2023) Reinforcement Learning with Contrastive Unsupervised Representations for Traffic Engineering in Hybrid SDN. 2023 IEEE 15th International Conference on Communication Software and Networks (ICCSN), Shenyang, 21-23 July 2023, 118-122. https://doi.org/10.1109/ICCSN57992.2023.10297329
[53]
Ahmad, S. and Mir, A.H. (2023) Protection of Centralized SDN Control Plane from High-Rate Packet-In Messages. International Journal of Information Security, 22, 1197-1206. https://doi.org/10.1007/s10207-023-00685-z
[54]
Liu, S., Liu, J. and Xia, B. (2023) Adaptive Timescale Load Balancing Routing Algorithm for LEO Satellite Network. 2023 IEEE/CIC International Conference on Communications in China (ICCC), Dalian, 10-12 August 2023, 1-5. https://doi.org/10.1109/ICCC57788.2023.10233496
