Dual: Deploy stateful virtual network function chains by jointly allocating data-control traffic

Network Function Virtualization (NFV) allows to deploy network functions at low cost and high flexibility. Usually traffic needs to pass through several network functions in a particular order, which is known as network function chaining. Due to capacity limitation, one instance of a particular network function in the chain usually needs to be scaled to multiple instances when the traffic load increases. Recent studies show that network functions maintain rich internal states, which correlate with flows and determine their processing actions. In order to guarantee network functions to behave the same as before the scaling, these states on multiple instances need to be synchronized. As a result, communication requirement for synchronizing these states arises. Our experimental investigations show that such communication traffic for state synchronization is non-negligible. Unfortunately, to our best knowledge, no existing work for network function chain deployment considered such traffic. In this paper, we consider the problem of allocating both flow traffic and synchronization traffic with the goal to minimize the consumption of network interface card's bandwidth, which is considered as the bottleneck resource of the network. The main challenge is that such two kinds of traffic are correlated and even conflicting. To deal with this challenge, a new graph-based model named Dual (Deploy Stateful Virtual Network Function Chains by Jointly Allocating Data-Control Traffic) is proposed, which characterizes the interaction of data-control traffic in an elegant manner. Based on Dual, the problem mentioned above is formulated through ILP and an approximation algorithm is designed. Extensive simulations show that the proposed approach is effective in terms of reducing server bandwidth usage. (C) 2019 Published by Elsevier B.V.