A Hybrid Virtual Network Function Placement Strategy for Maximizing the Profit of Network Service Deployment over Dynamic Workload

Abstract

The emergence of network function virtualization~(NFV) has revolutionized the infrastructure and service management of network architecture by reducing the cost and complexity of network service deployment. However, finding the optimal placement of virtual network functions (VNFs) is an NP-complete problem. Existing solutions base on either Integer Linear Programming~(ILP), or greedy algorithms. But, solving ILP can be time consuming and the approximation of greedy is not bounded. Hence, neither of them can make quick and accurate placement decisions, especially under dynamic traffic workload. Therefore, we propose a hybrid method that combines the two approaches together to achieve up to 45% service profit improvement with less computation time comparing to the traditional static ILP approach.