Load Balancing in tasks using Honey bee Behavior Algorithm in Cloud Computing

Proper scheduling of tasks on cloud is a crucial optimization concern. Load balancing between deterrent dependent tasks on virtual machines (VMs) in cloud datacenters is a significant feature of task arrangement procedure in the cloud environment. In this paper, the new task scheduling model has been proposed, which utilizes the honey bee inspired algorithm for the load balancing which maximize the throughput of virtual machines in the cloud and optimize the execution time of assigned dependent tasks for the proper utilization of resources in the least possible cost. The proposed model balances the load between the jobs on VM's in a way that the overall waiting time of tasks in the queue is minimized. The proposed model is designed to calculate the CPU time in terms of earliest finish time (EFT). The load is calculated on the basis of resource usage percentage whereas the communication cost is evaluated by using process memory allocation, memory requirement, and data size, which is further used for final decision making by comparing the communication cost with the process cost. The experimental results have proven the effectiveness of the proposed model in comparison with the existing models.