Adaptive Request Scheduling for Device Cloud

Han Dong, Enze Xu, Xiang Jing, Huaqian Cai, Gang Huang

Abstract: Nowadays, more and more cloud testing platforms provide enterprise developers with solutions for cloud device debugging and automatic testing. It is a great challenge for these cloud platforms to schedule the arriving requests to run on the specific smart device resources in real-time and efficiently. The traditional scheduling algorithm is difficult to adapt to the application interface call request with a vast difference in volume and behaviour ability. To solve this problem, we integrate these smart devices into a device cloud and propose a measurement method of the service capability of a single device in the group. Then we build an adaptive scheduling algorithm model according to the characteristics of the serviceability of a single device to improve the scheduling efficiency of the group. Practice shows that the adaptive scheduling algorithm can effectively control the network traffic. Finally, through the analysis and optimization, we get the method of obtaining the optimal parameter combination in the algorithm.