Abstract

Network function virtualization (NFV) provides an effective way to decouple network functions from the proprietary hardware, allowing the network providers to implement network functions as virtual machines running on standard servers. In the NFV environment, an NFV service request is provisioned in the form of a service function chain (SFC). The SFC defines the exact sequence of actions or virtual network functions (VNFs) that the data stream from the service request is subjected to. These actions or VNFs need to be mapped onto specific physical networks to provide network services for end users. In this paper, we investigate the problem of dependence-aware service function chain (D_SFC) design and mapping. We study how to efficiently map users’ service requests over the physical network while taking into consideration the computing resource demand, function dependence of the VNFs, and the bandwidth demand for the service request. We propose an efficient algorithm, namely, Dependence-Aware SFC Embedding With Group Mapping (D_SFC_GM), which integrates the proposed techniques of dependence sorting, independent grouping, adaptive mapping, and tetragon remapping to jointly design and map users’ service requests. The proposed D_SFC_GM algorithm takes advantage of VNF’s dependence relationships and the available resources in the physical network to efficiently design the chain and reserve the computing/bandwidth in the physical network. The extensive performance analysis in both IP and physical networks shows that the proposed D_SFC_GM significantly outperforms the traditional approach based on topological sorting and sequential embedding.

© 2018 Optical Society of America

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