Recent research in DVFS-aware Server Consolidation in Cloud Computing focuses on integrating Dynamic Voltage and Frequency Scaling (DVFS) with intelligent server consolidation strategies to minimize energy consumption while maintaining application performance and Service Level Agreements (SLAs). These studies combine workload prediction, VM migration, and adaptive frequency scaling to dynamically adjust CPU performance according to real-time demands. By consolidating virtual machines onto fewer active servers and scaling down underutilized ones, significant power savings are achieved without degrading system responsiveness. Advanced approaches employ hybrid optimization algorithms and reinforcement learning models to determine optimal consolidation and DVFS policies. Overall, DVFS-aware consolidation has emerged as a key energy management mechanism, effectively balancing computational efficiency, energy savings, and thermal stability in modern cloud data centers.