Abstract
In the software-defined network and network function virtualization environment, most service chain mapping methods only deploy single instance in proper place in the network. It is difficult to balance load balancing and network utilization. This paper proposes a service chain mapping method based on load balancing. In this paper, the replication of VNF instances is added to the process of service chain mapping to maintain network load balancing and minimize delay. A multi-objective optimization model is established. Aiming at this multi-objective optimization problem, this paper uses a service chain mapping method based on particle swarm optimization algorithm and redefines the particle parameters and related operations according to the service chain mapping problem. The simulation results show that compared with other random mapping methods, the proposed algorithm can effectively maintain load balancing, reduce delay, and reduce resource consumption by up to 30% in the mapping process.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Park, C., Shin, D.: VNF management method using VNF group table in network function virtualization. In: 2017 19th International Conference on Advanced Communication Technology (ICACT), Bongpyeong, pp. 210–212 (2017)
Jahromi, N.T., Kianpisheh, S., Glitho, R.H.: Online VNF placement and chaining for value-added services in content delivery networks. In: 2018 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN), Washington, DC, pp. 19–24 (2018)
Wang, B., Odini, M.: Short paper: lightweight VNF manager solution for virtual functions. In: 2015 18th International Conference on Intelligence in Next Generation Networks, Paris, pp. 148–150 (2015)
Zhou, R.: An online placement scheme for VNF chains in geo-distributed clouds. In: 2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS), Banff, AB, Canada, pp. 1–2 (2018)
Yang, Z., Chen, B., Dai, M., Su, G., Lin, R.: VNF placement for service chaining in IP over WDM networks. In: 2018 Asia Communications and Photonics Conference (ACP), Hangzhou, pp. 1–3 (2018)
Shi, J., Wang, J., Huang, H., Shen, L., Zhang, J., et al.: Joint optimization of stateful VNF placement and routing scheduling in software-defined networks. In: 2018 IEEE International Conference on Parallel & Distributed Processing with Applications, Ubiquitous Computing & Communications, Big Data & Cloud Computing, Social Computing & Networking, Sustainable Computing & Communications (ISPA/IUCC/BDCloud/SocialCom/SustainCom), Melbourne, Australia, pp. 9–14 (2018)
Soualah, O., Mechtri, M., Ghribi, C., Zeghlache, D.: Energy efficient algorithm for VNF placement and chaining. In: 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), Madrid, pp. 579–588 (2017)
Quang, P.T.A., Bradai, A., Singh, K.D., Picard, G., Riggio, R.: Single and multi-domain adaptive allocation algorithms for VNF forwarding graph embedding. IEEE Trans. Netw. Serv. Manage. 16(1), 98–112 (2019)
Acknowledgements
This work was supported by the science and technology project of Guangdong power grid (036000KK52160025).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Shi, Z., Wu, Z., Zeng, Y. (2021). A Method of Service Function Chain Arrangement for Load Balancing. In: Liu, Q., Liu, X., Li, L., Zhou, H., Zhao, HH. (eds) Proceedings of the 9th International Conference on Computer Engineering and Networks . Advances in Intelligent Systems and Computing, vol 1143. Springer, Singapore. https://doi.org/10.1007/978-981-15-3753-0_4
Download citation
DOI: https://doi.org/10.1007/978-981-15-3753-0_4
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-3752-3
Online ISBN: 978-981-15-3753-0
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)