Abstract
Aiming at reducing the link load and improving substrate network resource utilization ratio, we model the virtual network embedding (VNE) problem as an integer linear programming and present a discrete particle swarm optimization based algorithm to solve the problem. The approach allows multiple virtual nodes of the same VN can be embedded into the same physical node as long as there is enough resource capacity. It not only can cut down embedding processes of virtual link and reduce the embedding time, but also can save the physical link cost and make more virtual networks to be embedded at the same time. Simulation results demonstrate that comparing with the existing VNE algorithm, the proposed algorithm performs better for accessing more virtual networks and reducing embedding cost.
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Yuan, Y., Wang, CR., Wan, C., Wang, C., Song, X. (2013). Repeatable Optimization Algorithm Based Discrete PSO for Virtual Network Embedding. In: Guo, C., Hou, ZG., Zeng, Z. (eds) Advances in Neural Networks – ISNN 2013. ISNN 2013. Lecture Notes in Computer Science, vol 7951. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39065-4_41
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DOI: https://doi.org/10.1007/978-3-642-39065-4_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-39064-7
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