Abstract
Virtual network embedding (VNE) is helpful for effective sharing the underlying physical substrate network resources. In the existing particle swarm optimization-based VNE algorithms, the particle position initialization phase will produce a lot of resources fragment and prevent the underlying substrate network from receiving more resource requests. In order to improve the utilization rate and load balancing of the substrate network as well as accelerate the mapping efficiency of VNE algorithm, this paper presents a particle swarm optimization based load balancing VNE algorithm. A particle position initialization strategy is introduced by reducing the candidate substrate nodes to reject the inaccuracy caused by the random selection in position initialization. Simulation results show that the proposed algorithm can effectively increase the acceptance rate of virtual network requests and improve the long-term average revenue to cost ratio of the substrate network.
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
Similar content being viewed by others
References
Chowdhury, N.M., Boutaba, R.: Network virtualization: state of the art and research challenges. Commun. Mag. IEEE 47(7), 20–26 (2009)
Fischer, A., Botero, J.F., Till Beck, M., De Meer, H., Hesselbach, X.: Virtual network embedding: a survey. Commun. Surv. Tutorials IEEE 15(4), 1888–1906 (2013)
Fischer, A., Beck, M.T., De Meer, H.: An approach to energy-efficient virtual network embeddings. In: 2013 IFIP/IEEE International Symposium on Integrated Network Management (IM 2013), pp. 1142–1147. IEEE, May 2013
Kennedy, J., Eberhart, R.C.: A discrete binary version of the particle swarm algorithm. In: 1997 IEEE International Conference on Systems, Man, and Cybernetics, Computational Cybernetics and Simulation, vol. 5, pp. 4104–4108. IEEE, October 1997
Djojo, M.A., Karyono, K.: Computational load analysis of Dijkstra, A*, and Floyd-Warshall algorithms in mesh network. In: 2013 IEEE International Conference on Robotics, Biomimetics, and Intelligent Computational Systems (ROBIONETICS), pp. 104–108. IEEE, November 2013
Lischka, J., Karl, H.: A virtual network mapping algorithm based on subgraph isomorphism detection. In: Proceedings of the 1st ACM Workshop on Virtualized Infrastructure Systems and Architectures, pp. 81–88. ACM, August 2009
Cheng, X., Zhang, Z.B., Su, S., Yang, F.C.: Virtual network embedding based on particle swarm optimization. Dianzi Xuebao (Acta Electronica Sinica) 39(10), 2240–2244 (2011)
Acknowledgment
This work was supported in part by the following funding agencies of China: National Natural Science Foundation of China (61300195, 61402094), Natural Science Foundation of Hebei Province (F2014501078), The Research Fund for the Doctoral Program of Higher Education of China (Grant no. 20120042120009), and the Science and Technology Support Program of Northeastern University at Qinhuangdao (Grant no. XNK201401).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Wang, C., Liu, Y., Yuan, Y., Li, G., Wang, Q. (2016). A DPSO-Based Load Balancing Virtual Network Embedding Algorithm with Particle Initialization Strategy. In: Tan, Y., Shi, Y., Li, L. (eds) Advances in Swarm Intelligence. ICSI 2016. Lecture Notes in Computer Science(), vol 9713. Springer, Cham. https://doi.org/10.1007/978-3-319-41009-8_33
Download citation
DOI: https://doi.org/10.1007/978-3-319-41009-8_33
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-41008-1
Online ISBN: 978-3-319-41009-8
eBook Packages: Computer ScienceComputer Science (R0)