Throughput Optimization VNF Placement in Cloud Datacenter Considering Time-Varying Workload and Multi-Tenancy
Yi Yue, Shiding Sun, Zhiyan Zhang, Xiongyan Tang, Wencong Yang, Xuebei Zhang · 2023
Network service providers benefit greatly from Network Function Virtualization (NFV), which allows them to outsource their Network Functions (NFs) to cloud data centers flexibly. This paper focuses on the Virtual Network Function (VNF) placement in cloud data centers while maximizing the network’s accepted Service Function Chain Requests (SFCRs). To optimize resource utilization, we consider two key factors that are often overlooked: time-varying workloads and VNF sharing based on multi-tenancy technology. We formulate the VNF placement problem as an Integer Linear Programming (ILP) model. To solve the ILP, we devise a Throughput Optimization Heuristic Solution (TOHS). Finally, we conduct a detailed numerical simulation and compare our results with contrasting schemes in the existing literature. Our evaluation shows that the performance of TOHS is near to results derived by ILP solver for small-scale problems. In addition, TOHS outperforms other solutions in various scenarios, resulting in higher network throughput and better utilization of network resources.