Resource-Aware Service Function Chain Deployment in Cloud-Edge Environment
Hao Li, Xin Li, Zhuzhong Qian, Xiaolin Qin
Abstract
With the development of network technology, Network Function Virtualization (NFV) provides a good paradigm of sharing network resources, aiming to transfer network functions from hardware-based devices to software-defined Virtual Network Function (VNF) instances. Each type of VNF is mostly multi-instance, and different VNF instances require to be chained in a predefined sequence to form Service Function Chain (SFC) to provide network services. However, due to the resource capacity constraints of edge nodes and the high latency of cloud edge links in cloud-edge system, it is crucial and challengeable to deploy SFC in NFV-enabled networks. In our paper, we study the SFC deployment (SFC-D) problem in cloud-edge environment. We formulate the SFC-D as an Integer Linear Programming (ILP) model aiming to minimize the deployment cost, and propose a resource-aware deployment algorithm (RADA). According to our extensive evaluations, compared with the state-of-the-art counterpart algorithm, RADA performs better in the remaining available resources of nodes, and the average acceptance rate increases by 15%.