Queue-Aware Dynamic Placement of Virtual Network Functions in 5G Access Network

With the development of network function virtualization technology, virtual network functions (VNFs) can be chained to provide different services for users in fifth generation access networks. Under the condition of a large number of various user service requests reach the network in a short time, dynamic placement of VNFs is essential to achieve efficient physical resource allocation, while ensuring network stability. Unlike queue models in current works, we design a dynamic scheduling model of two-stage queue to perceive the status of current queue backlog and schedule the queue dynamically. In particular, we formulate a VNF placement cost minimization problem, taking the network stability into account. Owing to that the problem belongs to an NP-hard problem, we transform it into the minimization of the upper bound of the drift-plus-penalty function by the Lyapunov optimization technique. Then, we decompose the reformulated problem into a service function chain (SFC) scheduling problem and an SFC mapping problem, corresponding to our designed dynamic scheduling model of two-stage queue. For the abovementioned two problems, we present a queue-aware dynamic placement of virtual network functions algorithm. It includes a genetic algorithm-based heuristic SFC scheduling algorithm (first stage) and a genetic algorithm-based heuristic SFC mapping algorithm (second stage). Simulation results demonstrate that our placement algorithm can guarantee less placement cost while significantly enhancing network stability, compared with the existing algorithm.