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A Link Load Balancing Algorithm Based on Ant Colony Optimization in Data Center Network

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Communications and Networking (ChinaCom 2020)

Abstract

With the continuous increase of types of services and data volume in data center, the traffic loads of some links are excessive, and how to balance the link load and ensure the quality of network service have become research hotpots. However, the traditional link load balancing mechanisms ignore the complexity of network and the Quality of Service (QoS) requirement of the flow when calculating the forwarding paths. Therefore, we propose a link load balancing algorithm based on Ant Colony Optimization (LLBA) in data center network. The algorithm redefines the heuristic function according to the number of elephant flows on the link and the real-time load of links, and updates the pheromones according to the path length. Then, the algorithm customizes the optimal path determination rule according to the path transmission delay and the real-time loads, so as to find a best forwarding path for the current flow under the multiple constraints including the path length, link load, and transmission delay. The experiment results show that, the proposed algorithm improves the link utilization and network throughput effectively, and also reduces the delay and delay jitter to some extent, as compared with the traditional mechanisms.

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References

  1. Wang, Y., You, S.: An efficient route management framework for load balance and overhead reduction in SDN-based data center networks. IEEE Trans. Netw. Serv. Manage. 15(4), 1422–1434 (2018)

    Article  Google Scholar 

  2. Cong, L., Yong-Hao, W.: Strategy of data manage center network traffic scheduling based on SDN. In: 2016 International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS), Changsha, pp. 29–34 (2016)

    Google Scholar 

  3. Wang, J.M., Wang, Y., Dai, X., Bensaou, B.: SDN-based multi-class QoS guarantee in inter-data center communications. IEEE Trans. Cloud Comput. 7(1), 116–128 (2019)

    Google Scholar 

  4. Wang, W., Sun, Y., Zheng, K., Kaafar, M.A., Li, D., Li, Z.: Freeway: adaptively isolating the elephant and mice flows on different transmission paths. In: 2014 IEEE 22nd International Conference on Network Protocols, Raleigh, NC, pp. 362–367 (2014)

    Google Scholar 

  5. Zhang, H., Guo, X., Yan, J., Liu, B., Shuai, Q.: SDN-based ECMP algorithm for data center networks. In: 2014 IEEE Computers, Communications and IT Applications Conference, Beijing, pp. 13–18 (2014)

    Google Scholar 

  6. Truong, T., Fu, Q., Lorier, C.: FlowMap: Improving network management with SDN. In: NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium, Istanbul, pp. 821-824 (2016)

    Google Scholar 

  7. Qiu, S., Yu, X., Wang, K., Gu, H.: MiFlO: a scheduling algorithm based on mice flows optimization in hybrid data center network. In: 2017 16th International Conference on Optical Communications and Networks (ICOCN), Wuzhen, pp. 1–3 (2017)

    Google Scholar 

  8. Al-Fares, M., et al.: Hedera: dynamic flow scheduling for data center networks. In: Proceedings of the 7th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2010, 28–30 April 2010, San Jose, CA, USA DBLP (2010)

    Google Scholar 

  9. Curtis, A.R., Kim, W., Yalagandula, P.: Mahout: low-overhead datacenter traffic management using end-host-based elephant detection. In: 2011 Proceedings IEEE INFOCOM, Shanghai, pp. 1629–1637 (2011)

    Google Scholar 

  10. Long, L., Binzhang, F., Lixin, C.: Nimble: a fast flow scheduling strategy for OpenFlow networks. Chin. J. Comput. 38(5), 1056–1068 (2015)

    Google Scholar 

  11. Hu, W., Liu, J., Huang, T., Liu, Y.: A completion time-based flow scheduling for inter-data center traffic optimization. IEEE Access 6, 26181–26193 (2018)

    Article  Google Scholar 

  12. Kanthimathi, M., Vijayakumar, D.: An enhanced approach of genetic and ant colony based load balancing in cloud environment. In: 2018 International Conference on Soft-computing and Network Security (ICSNS), Coimbatore, pp. 1–5 (2018)

    Google Scholar 

  13. Dorigo, M., Stützle, T.: Ant colony optimization: overview and recent advances. In: Gendreau, M., Potvin, J.-Y. (eds.) Handbook of Metaheuristics. ISORMS, vol. 272, pp. 311–351. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-91086-4_10

    Chapter  Google Scholar 

  14. Wang, C., Zhang, G., Xu, H., Chen, H.: An ACO-based link load-balancing algorithm in SDN. In: 2016 7th International Conference on Cloud Computing and Big Data (CCBD), Macau, pp. 214–218 (2016)

    Google Scholar 

  15. Mininet. http://www.mininet.org/

  16. Ryu. https://github.com/osrg/ryu

  17. Al-Fares, M., Loukissas, A., Vahdat, A.: A scalable, commodity data center network architecture. ACM SIGCOMM Comput. Commun. Rev. 38(4), 63–74 (2008)

    Article  Google Scholar 

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Acknowledgment

This work was supported by Program for Changjiang Scholars and Innovative Research Team in university (IRT_16R72).

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Correspondence to Shuqing Ma .

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Ma, S., Tang, H., Wang, X. (2021). A Link Load Balancing Algorithm Based on Ant Colony Optimization in Data Center Network. In: Gao, H., Fan, P., Wun, J., Xiaoping, X., Yu, J., Wang, Y. (eds) Communications and Networking. ChinaCom 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 352. Springer, Cham. https://doi.org/10.1007/978-3-030-67720-6_33

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  • DOI: https://doi.org/10.1007/978-3-030-67720-6_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-67719-0

  • Online ISBN: 978-3-030-67720-6

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