Effective Resource Allocation and Load Balancing in Green Cloud Computing

This paper provides a comprehensive overview of effective resource allocation and load balancing strategies in the context of green cloud computing. It highlights the significance of green cloud computing in addressing environmental concerns and enhancing resource efficiency in data centres. By exploring various resource allocation techniques, including dynamic VM provisioning, consolidation and scheduling algorithms, the paper demonstrates how optimization of resource utilization can lead to reduced energy consumption and carbon emissions. This study investigates the applications of various load balancing algorithms in cloud computing environments. The primary focus is on their effectiveness in distributing workloads efficiently across available cloud resources. Additionally, the research aims to evaluate the impact of these strategies on energy consumption and overall system performance. Emerging trends and future research directions, such as integrating machine learning for optimization and incorporating edge computing principles, are identified. Overall, the paper underscores the importance of effective resource allocation and load balancing in green cloud computing for achieving environmental sustainability goals while meeting the increasing demands for computational resources.