Planning of jobs in cloud computing is a NP-hard enhancement issue. Load adjusting of non-pre-emptive autonomous jobs on virtual machines (VMs) is an imperative part of job planning in clouds. At whatever point certain VMs are over-burdened and remaining VMs are lightly loaded with jobs for processing. The workload must be adjusted to accomplish ideal machine usage. In this paper, we propose an efficient artificial bee colony based load balancing which intends to accomplish well-adjusted workload across all virtual machines thereby improving response time and throughput. © 2016 International Science Press.