Adaptive Request Scheduling for Device Cloud

Han Dong, Enze Xu, Xiang Jing, Huaqian Cai, Gang Huang
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引用次数: 1

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.
设备云的自适应请求调度
如今,越来越多的云测试平台为企业开发人员提供了云设备调试和自动测试的解决方案。如何将到达的请求实时高效地调度到特定的智能设备资源上,是这些云平台面临的巨大挑战。传统的调度算法难以适应数量和行为能力差异较大的应用接口调用请求。为了解决这一问题,我们将这些智能设备集成到一个设备云中,并提出了一种测量组中单个设备服务能力的方法。然后根据单台设备可服务性的特点,建立了自适应调度算法模型,提高了群调度效率。实践表明,自适应调度算法能有效地控制网络流量。最后,通过分析和优化,得到了算法中获得最优参数组合的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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