Robust service provisioning of service function chain under demand uncertainty

Abstract

In network function virtualization, resource allocation is one of the key techniques to ensure the QoS of service requests in face of the uncertain traffic demand and traffic fluctuation of user services. The previous related works usually assume that the traffic demand is a deterministic value and then reallocate substrate resources to deal with the demand uncertainty and traffic fluctuation during operation. In response to performance degradation caused by demand uncertainty and traffic fluctuation, the paper models the service function chain orchestration under demand uncertainty as a robust optimization problem, where the parameter Γ is introduced to control the conservativeness of the solution. On this basis, the strong duality theory is used to transform the original problem into a mixed-integer linear programming, and then devise an exact Robust Service Provisioning (RSP) algorithm. The simulation evaluation demonstrates that the proposed algorithm could achieve different levels of robustness and make a trade-off between robustness and cost. The impact of Γ value on the realized robustness and price of robustness is also analysed. Thus, the algorithm proposed could get an effective service function chain orchestration scheme under uncertain traffic demands and provide a reference of the total cost.