VMFMAX: Improving Virtual Machine Utilization in VNF Placement

In order to improve the performance of contemporary and prospective technologies grounded in Network Function Virtualization (NFV), it is imperative to concentrate on identifying the most effective strategies for the placement of Virtual Network Functions (VNFs) within NFV frameworks. Consequently, the objective of this study is to present a viable solution for VNF placement. We delve into the significance of factors such as Storage Latency, CPU Model, and Network Packet Dropped, among others, which necessitate careful consideration. These parameters wield substantial influence over Virtual Machines (VMs) and overall VNF placements. Through the judicious selection of suitable VMs for VNFs, our aim is to improve the placements of VNFs, employing our proposed methodology termed VMFMAX. Our findings reveal that VMFMAX has efficient and less time and resource-consuming calculations compared to previous studies. VMFMAX conspicuously impacts the outcomes of the VNF placement process, underscoring its critical role in achieving more precise and accurate calculations.