CTS-SOS: Cloud Task Scheduling Based on the Symbiotic Organisms Search

Cloud task scheduling affects the overall operating efficiency of the cloud platform. Thus, how to effectively use resources in the cloud environment and make massive tasks to implement a reasonable and efficient scheduling becomes more crucial. Firstly, the mathematical model of cloud task computing was reconstructed by adding the expected completion time to the task. Secondly, on the basis of the completion time as the fitness function, the task priority was dynamically adjusted by user satisfaction, which was added to reduce the user’s completion time and improve the user’s satisfaction. Thirdly, aiming at the continuous search space, a cloud task scheduling algorithm based on the Symbiotic Organisms Search (CTS-SOS) was proposed. Not only does the CTS-SOS have fewer specific parameters, but also take a little time complexity. Through using the CloudSim toolkit package, the CTS-SOS algorithm was compared with Round Robin algorithm of the CloudSim and ACO algorithm. Experimental results show that CTS-SOS can provide a better optimization and scheduling of resources, reduce the makespan effectively, and improve the efficiency of processing tasks and user’s satisfaction.