Balancer Genetic Algorithm—A Novel Task Scheduling Optimization Approach in Cloud Computing

Task scheduling is one of the core issues in cloud computing. Tasks are heterogeneous, and they have intensive computational requirements. need to be scheduled on Virtual Machines (VMs), which resources a environment. Due immensity search space for possible mappings tasks VMs, meta-heuristics introduced task scheduling. In makespan load balancing, Quality Service (QoS) parameters crucial. This research contributes novel balancing scheduler, namely Balancer Genetic Algorithm (BGA), presented improve balancing. Insufficient can cause an overhead utilization resources, as some remain idle. BGA inculcates mechanism, where actual terms million instructions assigned VMs considered. A opt multi-objective optimization improvement also emphasized. Skewed, normal uniform distributions workload different batch sizes used experimentation. has exhibited significant compared with various state-of-the-art approaches makespan, throughput