Energy Aware Load Balancing Framework for Smart Grid Using Cloud and Fog Computing

Data centers are producing a lot of data as cloud-based smart grids replace traditional grids. The number of automated systems has increased rapidly, which in turn necessitates the rise of cloud computing. Cloud computing helps enterprises offer services cheaply and efficiently. Despite the challenges of managing resources, longer response plus processing time, and higher energy consumption, more people are using cloud computing. Fog computing extends cloud computing. It adds cloud services that minimize traffic, increase security, and speed up processes. Cloud and fog computing help smart grids save energy by aggregating and distributing the submitted requests. The paper discusses a load-balancing approach in Smart Grid using Rock Hyrax Optimization (RHO) to optimize response time and energy consumption. The proposed algorithm assigns tasks to virtual machines for execution and shuts off unused virtual machines, reducing the energy consumed by virtual machines. The proposed model is implemented on the CloudAnalyst simulator, and the results demonstrate that the proposed method has a better and quicker response time with lower energy requirements as compared with both static and dynamic algorithms. The suggested algorithm reduces processing time by 26%, response time by 15%, energy consumption by 29%, cost by 6%, and delay by 14%.

Automated summary

Data centers generate large amounts of data as cloud-based smart grids replace traditional grids. The increase in automated systems has led to the rise of cloud computing, which helps enterprises provide services at low cost and high efficiency. Despite challenges such as resource management, longer response and processing time, and increased energy consumption, cloud computing is being increasingly used. Fog computing, an extension of cloud computing, reduces traffic, improves security, and speeds up processes. Both cloud and fog computing contribute to energy savings in smart grids. The paper proposes a load-balancing approach using Rock Hyrax Optimization (RHO) in Smart Grids to optimize response time and energy consumption. The algorithm assigns tasks to virtual machines and shuts off unused ones, reducing energy consumption. The proposed method shows better and quicker response time, lower energy requirements, and improved performance compared to static and dynamic algorithms. It reduces processing time by 26%, response time by 15%, energy consumption by 29%, cost by 6%, and delay by 14%.