A multi-objective non-dominated sorting genetic algorithm for VNF chains placement

We propose a meta-heuristic based on the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to address the NP-Hard service function chain placement problem. This work considers the minimization of the mapping cost and of the physical links utilization for virtualized network functions (VNF) chaining. The proposed NSGA-II based algorithm finds a Pareto front to select solutions that meet the multiple objectives and performance tradeoffs of providers. Simulation results and comparison with a multi-stage algorithm and a matrix based heuristic from the literature, highlight the efficiency and usefulness of the proposed NSGA-II-based approach.

[1]  Djamal Zeghlache,et al.  Virtualized network functions chaining and routing algorithms , 2017, Comput. Networks.

[2]  Djamal Zeghlache,et al.  Scalable and cost-efficient algorithms for VNF chaining and placement problem , 2017, 2017 20th Conference on Innovations in Clouds, Internet and Networks (ICIN).

[3]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[4]  Holger Karl,et al.  Specifying and placing chains of virtual network functions , 2014, 2014 IEEE 3rd International Conference on Cloud Networking (CloudNet).

[5]  Jorge Lobo,et al.  Experimental results on the use of genetic algorithms for scaling virtualized network functions , 2015, 2015 IEEE Conference on Network Function Virtualization and Software Defined Network (NFV-SDN).

[6]  Lawrence Davis,et al.  Applying Adaptive Algorithms to Epistatic Domains , 1985, IJCAI.