Review and Experimental Analysis on the Integration of Modern Tools for the Optimization of Data Center Performance
International Journal of Advanced Trends in Computer Science and Engineering · 2025
This study investigates the integration of modern tools such as Artificial Intelligence (AI) and Machine Learning (ML), Internet of Things (IoT), Data Center Infrastructure Management (DCIM) software, Blockchain technology, 5G and Edge Computing, and Sustainability tools to optimize data center performance in practical cloud operations. Leveraging experimental data from four data centers, the study evaluated the impact of these technologies on key performance metrics, including energy efficiency, operational costs, carbon emissions, and real-time responsiveness. Results showed that AI and ML applications improved workload optimization by 25% and reduced predictive maintenance costs by 30%, significantly enhancing system reliability. IoT-enabled monitoring systems achieved a 20% reduction in cooling energy consumption through dynamic adjustments. DCIM tools reduced downtime occurrences by 40% and optimized capacity utilization, while Blockchain technology ensured secure and transparent data management with zero reported breaches. The adoption of 5G and Edge Computing enabled low-latency operations with a 15% increase in data transfer speeds and 10% reduction in latency. Sustainability tools resulted in a 35% decrease in carbon emissions and a 25% reduction in water usage through recycling systems, with payback periods averaging 3 years for renewable energy integration projects. This work underscores the transformative potential of modern tools in achieving operational excellence and sustainability in data centers. The findings provide a data-driven foundation for stakeholders to implement technology-driven strategies, balancing performance optimization with environmental and economic considerations