Task Scheduling Algorithm Based on Load Balancing Ant Colony Optimization in Cloud Computing

Reasonable virtual machine allocating and efficient task scheduling is a key problem in the cloud computing. A pheromone adjustment factor is given out according to the load of virtual machines, and a LBACO(Load Balancing Ant Colony Optimization) algorithm is proposed to solve the load imbalance of virtual machine in the process of task scheduling. The LBACO algorithm can adapt to the dynamic cloud environment. The new scheduling strategy was simulated on the CloudSim platform. The results show that the proposed LBACO algorithm not only shorten the makespan of task scheduling, but also maintain the load balance of virtual machines in the data center.