Service Chain Provisioning Model Considering Traffic Amount Changed by Virtualized Network Functions

This paper proposes a service chain provisioning model considering traffic changing effects of virtualized network functions (VNFs) while determining the VNF visit order of each request, routes of requests, and VNF placement. The service chain provisioning problem is formulated as an integer linear programming (ILP) problem. Three methods of limiting the number of VNF visit order patterns considered in the ILP problem are introduced in order to shorten the computation time. These methods select visit order patterns so as to suppress the sum of the traffic amount reserved by each request on its route. Numerical results show that the consumption of network and computation resources becomes more efficient by considering traffic amount changed by VNFs than the case assuming the traffic amount of each request to be constant end-to-end. The results also show that the computation time can be shortened in our examined scenarios while we obtain the objective value larger by at most 0.4% than the optimal value by limiting the number of visit order patterns.