Dependent Task Scheduling with Artificial Bee Colony Optimization

Cloud computing has become very popular due to its wide range of applications via internet. The service composition based techniques that are conscious from the server selection from the cloud can progress to the cost and efficiency of cloud computing. This paper has focused on the different swarm intelligent based energy efficient techniques called particle swarm optimization, ant colony and artificial bee colony based techniques. In order to overcome constrains of existing techniques a new artificial bee colony algorithm for DAG scheduling in cloud computing environment is proposed to enhance the energy consumption rate further. The comparisons among existing and proposed techniques have clearly shown that the proposed technique outperforms over the available methods.