Energy efficient aware computational load balancing framework algorithm for fog-cloud data centers

Abstract

Data centers form the foundation of Cloud computing systems. The overall operational costs are directly influenced by the resource management algorithms that assign virtual machines (VMs) to physical servers and the ability to relocate them in emergencies, such as power losses due to excessive heating. This paper presents a hierarchical SLA-based distributed-based resource provisioning and optimization framework algorithm. This framework considers constraints like energy consumption, cooling-related energy consumption, and scalability issues. We also include a load-balancing algorithm to minimize the operational costs of the distributed data center cloud system. Simulation results demonstrate that this approach, together with load balancing, significantly reduces the operational costs of the entire cloud system. This reduction is significantly pronounced when considering dynamic energy tariffs from integrating renewable power sources to supply server power.