Optimizing Energy-Efficient Resource Allocation in SDN/NFV Environments: A Comprehensive Investigation Using WASPAS Method

The rapid proliferation of Software-Defined Networking (SDN) and Network Function Virtualization (NFV) technologies has transformed the landscape of network management. As the demand for enhanced connectivity and computational resources continues to escalate, so does the energy consumption and carbon footprint of data centers and communication networks. The exponential growth of digital infrastructure has led to an unprecedented surge in energy consumption by data centers and communication networks. This surge not only strains power resources but also contributes substantially to carbon emissions, exacerbating the global challenge of climate change. Addressing this issue through optimized resource allocation strategies holds the potential to significantly reduce energy consumption and minimize the carbon footprint, aligning with international efforts to combat climate change and meet environmental goals. This article delves into the critical realm of energy-efficient resource allocation within SDN/NFV environments, aiming to explore innovative strategies that mitigate power consumption and environmental impact. By harnessing the Weighted Aggregated Sum Product Assessment (WASPAS) method, this study investigates novel avenues to optimize resource allocation, thereby paving the way for a more sustainable and ecologically responsible digital future. This research evaluates energy-efficient resource allocation across diverse network paradigms: Legacy Network Infrastructure, SDN with fixed/dynamic allocation, and NFV with fixed/dynamic allocation. It assesses Reduced Power Consumption and Lower Carbon Emissions, vital for sustainability. Network Performance impact and Hardware Dependencies are also analyzed. The examination demonstrates that dynamic resource allocation, notably within the NFV architecture, presents noteworthy enhancements in energy efficiency within SDN/NFV landscapes. The consistent superiority of NFV with dynamic allocation becomes evident, delivering decreased power usage and diminished carbon emissions compared to other tactics. The application of the Weighted Aggregated Sum Product Assessment (WASPAS) method enriches the precision of this assessment. Remarkably, the dynamic approach sustains, and in some instances, even enhances network performance, concurrently mitigating environmental repercussions. This investigation accentuates the significance of amalgamating technological and ecological considerations in resource allocation decisions, shedding light on NFV's potential to redefine energy-efficient network administration.