Optimizing Network Function Virtualization: A Comprehensive Performance Analysis of Hardware- Accelerated Solutions
Authors: Kumbum Praveen Kumar , Adari Vijay Kumar , Chunduru Vinay , Gonepally Srinivas , Amuda Kishor Kumar 
Published: November 2024

Network Function Virtualization (NFV) heralds a transformative shift in the realm of network infrastructure, moving away from the rigid
confines of specialised hardware appliances towards nimble, software-driven solutions that operate on off-the-shelf hardware. This transition holds
the tantalising promise of substantial reductions in both capital and operational expenditures. However, the deployment and orchestration of virtual
network functions pose formidable challenges, particularly concerning the optimisation of performance and judicious allocation of resources.
The significance of this research lies in its targeted approach to the pressing necessity for a thorough performance evaluation of diverse NFV
implementations. By furnishing organisations with vital insights for strategic infrastructure planning, this study embarks on a comparative journey
through various NFV architectures, juxtaposed with traditional hardware-centric solutions. It delves into the intricacies of practical deployment
considerations while rigorously examining critical performance metrics, aiming to illuminate the path forward in this rapidly evolving landscape.
The research methodology utilises the EDAS (Evaluation based on Distance from Average Solution) approach, a nuanced and multifaceted decisionmaking framework adept at assessing alternatives through their proximity to average solutions. This investigation delves into four pivotal evaluation
parameters: scalability, resource utilisation, latency, and energy consumption. In total, five alternative implementations are scrutinised: traditional
hardware, NFV with software acceleration, NFV leveraging GPU acceleration, NFV employing FPGA acceleration, and cloud-based NFV.The findings
reveal that NFV with GPU acceleration emerges as the frontrunner, attaining an impressive appraisal score of 0.9626, indicative of its exceptional
performance across all evaluated metrics. Hot on its heels, NFV with FPGA acceleration secures a noteworthy score of 0.9474, particularly excelling
in the domain of resource utilisation. In contrast, NFV with software acceleration (0.7614) and cloud-based NFV (0.4675) exhibit moderate efficacy,
while traditional hardware languishes at the bottom of the hierarchy, registering a dismal score of 0.0000.The findings illuminate that hardwareaccelerated Network Functions Virtualization (NFV) solutions, especially those harnessing the power of Graphics Processing Unit (GPU) technology,
deliver an optimal and nuanced performance tailored to the demands of contemporary networking landscapes. This research significantly enriches
the discourse on NFV implementation, shedding light on the intricate trade-offs involved, while offering empirical guidance for organisations
making the pivotal shift from traditional hardware infrastructures to virtualised network functions. The results underscore that, although hardware
acceleration markedly boosts NFV performance, the selection of implementation strategies must be meticulously aligned with the unique needs and
operational constraints of each organisation.
Keywords: Network Function Virtualization (NFV), Hardware Acceleration, Performance Benchmarking, EDAS Methodology, Resource
Optimization and Virtualized Network Infrastructure.