A task scheduling algorithm based on qos and complexity-aware optimization in cloud computing

Currently, in cloud computing, the issue about how to get the higher QoS (quality of service) by the lower service cost is increasingly attracting the attention. In this paper, we study the system service cost and the task scheduling algorithms of the optimizing resource. Meanwhile, we consider the affecting factors, including the cloud service cost, node´s load rate, bandwidth utilization, network delay, and task computation complexity. Besides, the mathematical model of the dynamic service-quality cost (DSC) which can real-time synthetically measure service cost and node´s service performance in cloud computing is proposed. Furthermore, we present the task scheduling algorithm of complexity-aware optimization based on the discussion. Finally, our experimental results demonstrate the reasonability and effectiveness of our algorithm. It can achieve not only the lower service cost but also the higher service quality by more reasonably assigning the tasks to the nodes for calculation in cloud computing. And the results are consistent with the theoretical analysis.