Scheduling model for simultaneous update of multiple service function chains with state consistency

Abstract

Network function virtualization (NFV) enables network providers to provide functions of network services as virtual machines. Software-defined network (SDN) enables the network providers to control a network quickly and flexibly in a centralized manner. Service chaining is realized by utilizing NFV and SDN. Service chaining concatenates virtual network functions (VNFs) in the network to automatically process packets in an appropriate order. Routes of service function chains (SFCs) need to be updated to achieve users’ requirements, such as keeping the VNFs up-to-date, suppressing packet losses and processing delays, and continuing to provide services in case of VNF failure. States of VNF instances that make up the SFC need to be kept consistent when updating the SFC routes; otherwise, the accuracy of the processing in the VNF instance after the update can be reduced. Multiple SFCs need to be updated at the same time in some situations, such as security updates of VNFs. Existing models update SFCs one by one. If these models are adopted to the update of multiple SFCs, the total time required to update all SFCs can be long; problems such as leaving VNFs out-of-date can occur. This paper proposes a model that determines the update schedule of multiple SFCs guaranteeing state consistency. SFCs to be updated and where to update them are given in this model. The proposed model is formulated as an integer linear programming (ILP) problem. The objective function is minimizing the total time required to update all SFCs. The decision problem of the proposed model is proved to be NP-complete. We develop a heuristic algorithm since the optimal solution may not be obtained in a practical time when the number of requests increases. Numerical results show that the total time required to update all SFCs can be shortened by updating multiple SFCs at the same time. The numerical results also show that the total time can be shortened by dividing a large buffer into an adequate number of small buffers. The heuristic algorithm can reduce the computation time compared to the ILP approach with suppressing the total update time.