淤地坝监测场景下边缘计算协作式任务调度方法  

Collaborative Task Scheduling Strategy for Mobile Edge Computing in Dam Monitoring

作　　者：章新川[1] 胡炜 王怀军[2] 安洋 李军怀[2] ZHANG Xin-Chuan;HU Wei;WANG Huai-Jun;AN Yang;LI Jun-Huai(Department of Water Resources,Shaanxi Province,Xi’an 710048,China;Faculty of Computer Science and Engineering,Xi’an University of Technology,Xi’an 710048,China)

机构地区：[1]陕西省水利厅,西安710048 [2]西安理工大学计算机科学与工程学院,西安710048

出　　处：《计算机系统应用》2021年第9期271-278,共8页Computer Systems & Applications

基　　金：陕西水利科技项目(2020slkj-17);国家自然科学基金(61971347);西安市科技计划(2020KJRC0093)。

摘　　要：针对目前我国西北地区淤地坝实时监测问题,研究了淤地坝监测与预警任务的调度方法.为避免淤地坝坝体隐患发现不及时,提高预警系统的时效性,本文考虑了任务卸载至边缘服务器的平均等待时间,提出了一种淤地坝监测场景下边缘计算协作式任务调度方法.根据任务计算量、边缘服务器计算能力等信息建立计算任务完成时间模型,然后采用模拟退火算法优化计算任务卸载位置,设计了一种多个边缘计算服务器相互协作的任务调度策略.实验结果表明,该方法有效降低了监测任务的计算时间,提高了监测预警的时效性.Concerning the real-time monitoring problem of warping dams in northwest China,this work studies the scheduling method of warping dam monitoring and early warning tasks.To avoid the delay in discovering the hidden trouble of warping dams and improve the timeliness of the warning system,this study considers the average waiting time from task unloading to edge servers and proposes a collaborative task scheduling method based on edge computing in warping dam monitoring.A task completion time model is built according to the task computation,computing power of edge servers,and other information.Then,a simulated annealing algorithm is used to optimize the unloading position of computing tasks.A task scheduling strategy is designed in which multiple edge computing servers cooperate.Experimental results show that this method can greatly reduce the calculation time of monitoring tasks and improve the timeliness of monitoring and early warning.

关 键 词：淤地坝监测 边缘计算 任务调度 任务完成时间模型 

分 类 号：TV698.1[水利工程—水利水电工程] TP18[自动化与计算机技术—控制理论与控制工程]