基于时间感知主导资源公平的边缘函数计算负载调度算法  

A time-aware dominant resource fair scheduling algorithm for edge function computing

作　　者：李宝[1] 朱姝 王晓川[1] 任怡[1] 谭郁松[1] LI Bao;ZHU Shu;WANG Xiao-chuan;REN Yi;TAN Yu-song(College of Computer Science and Technology,National University of Defense Technology,Changsha 410073,China)

机构地区：[1]国防科技大学计算机学院,湖南长沙410073

出　　处：《计算机工程与科学》2024年第10期1711-1719,共9页Computer Engineering & Science

基　　金：国家自然科学基金(U19A2060)。

摘　　要：针对边缘函数计算服务FaaS中不同负载之间资源抢占导致的资源分配不公平、利用率不高的问题,提出一种时间感知的主导资源公平调度算法。首先,分析了现有主导资源公平调度算法在应用到边缘函数计算服务时的不足;其次,提出加入函数实例运行时间权重,并通过时间感知队列和主导资源公平队列协同实现对函数运行所需要的资源进行公平分配和集群资源充分利用;最后,基于主流开源函数计算服务平台的调度器对算法进行了实现。采用公开负载运行数据集的测试结果表明,该算法最多提升了18.1%的CPU利用率和21.8%的内存利用率,并且执行时间最多降低了26.1%,能够有效提升边缘函数计算服务的资源分配公平性,且提高了资源利用率。To address the issues of unfair resource allocation and low utilization caused by resource preemption among different workloads in Function-as-a-Service(FaaS)edge computing,a time-aware dominant resource fair scheduling algorithm is proposed.Firstly,the limitations of existing dominant resource fair scheduling algorithms when applied to edge function computing services are analyzed.Then,the algorithm incorporates the runtime weight of function instances and utilizes a time-aware queue in conjunction with a dominant resource fair queue to achieve fair allocation of resources required for function execution and maximize cluster resource utilization.Finally,the algorithm is implemented based on the scheduler of a mainstream open-source function computing service platform.Test results using public workload datasets show that the proposed algorithm improves CPU utilization by up to 18.1%and memory utilization by up to 21.8%,while reducing execution time by up to 26.1%.This effectively enhances the fairness of resource allocation and improves resource utilization in edge function computing services.

关 键 词：边缘计算 函数计算服务 时间感知 主导资源公平调度 

分 类 号：TP302.7[自动化与计算机技术—计算机系统结构]