Cloud computing task scheduling method of artificial bee colony particle swarm algorithm based on Levy flight

The invention discloses a cloud computing task scheduling model based on service revenue and power dissipation and a cloud computing task scheduling method of an artificial bee colony particle swarm algorithm based on Levy flight. A multi-QoS scheduling model with introduced processor power dissipation and task scheduling revenue is provided for achieving a green cloud computing thinking. The artificial bee colony particle swarm algorithm based on Levy flight is provided for achieving multi-QoS cloud computing task scheduling. An artificial bee colony local search strategy is introduced in the particle swarm algorithm to improve the local search precision of the algorithm. Levy operation is conducted on the global optimum to avoid local optimum, and therefore the convergence precision is improved. The method can effectively increase the revenue of the cloud computing task scheduling, and can shorten user waiting time and can reduce processor power dissipation.