A Task Scheduling Algorithm Based on Big.LITTLE Architecture in Cloud Computing

In recent years, cloud computing has been extensively used in various fields, where task scheduling plays a vital role for task and resource management. Traditionally, all cores in one system-on-chip (SoC) are treated equally for cloud task scheduling. However, the advent of big.LITTLE architecture enables heterogeneous computing in a SoC, thus providing the opportunity for task scheduling at SoC level. In this paper, we propose a task scheduling algorithm that leverages performance features of cores on big.LITTLE architecture. We first characterize the performance of different cores in detail. Then We adopt a decision tree model to predict the execution times of tasks on a single core. Finally we design a task scheduling strategy to speed up the execution speed of big data tasks by comprehensively considering the program characteristics, resource requirements and computing performance on big and LITTLE cores. Experimental results show that our task scheduling algorithm makes more effective use of the computing capabilities of heterogeneous cores, and reduces the running time of big data tasks by 17% on average.