Our research in power and energy management is focused on pioneering strategies to optimize power consumption and energy efficiency in computing environments. A key aspect of our work involves leveraging Dynamic Voltage and Frequency Scaling (DVFS) techniques. Through careful analysis and experimentation, we aim to identify optimal voltage and frequency configurations that balance performance and energy consumption, enabling systems to adapt resource usage according to workload variations. Additionally, we are committed to developing robust power and energy metering approaches tailored for consolidated virtual machines. By accurately measuring power usage at the virtual machine level, we enable precise monitoring and management of energy consumption in multi-tenant virtualized environments. Our research also explores Hardware/Software co-design techniques to ensure Quality-of-Service (QoS) guarantees while maintaining low power and energy consumption. This includes the development of innovative algorithms, protocols, and mechanisms that dynamically allocate resources to meet performance targets while minimizing energy use. Overall, our goal is to contribute to the creation of energy-efficient computing systems that deliver high performance while prioritizing sustainable power and energy management, aligning with the growing demand for environmentally conscious and economically viable computing solutions.