ENERGY OPIMIZATION IN CLOUD COMPUTING ENVIRONMENT

Cloud computing has changed how people and organizations use computing resources by providing fast and flexible access to storage, applications, and processing power over the internet. However, this growth has caused cloud data centers to consume large amounts of energy, which leads to high operational costs and environmental problems. This study focuses on finding ways to reduce energy use in cloud computing without affecting performance and reliability. The research reviewed different techniques such as virtualization, server consolidation, dynamic voltage and frequency scaling (DVFS), energy-aware task scheduling, and the use of renewable energy sources. Each method was examined based on how well it reduces energy, how easy it is to implement, and its effect on system performance. The study used a comparative research approach, relying on existing data from journals, technical reports, and case studies. The findings show that no single method can fully solve the energy problem. However, combining several techniques—like using smart scheduling with virtualization and DVFS—can lead to better energy savings. Using renewable energy also helps reduce the environmental impact of cloud data centers. In conclusion, the study recommends a combined approach to energy optimization in cloud computing. This will help cloud service providers reduce energy costs and support global efforts to protect the environment, while still maintaining good system performance and user experience.