摘要
在云存储系统的体系架构中,当前对数据服务器守护进程的I/O请求调度采用先来先服务(first in first out)策略,这种调度策略没有考虑不同类型I/O请求的时效性要求,容易造成时效性要求高的I/O请求因被阻塞而无法得到及时处理,从而降低整个系统的服务质量.为解决该问题,本文提出一种用于云存储数据服务器的I/O请求调度算法.该算法首先对来自客户端的I/O请求进行分类,并赋予不同的优先级;然后以合适的时长作为周期、以分时间片的方式对不同优先级的I/O请求进行周期性的调度.分布式文件系统仿真实验结果表明,该算法在重负载情况下对实时请求的响应速度提高了20%,同时也兼顾了低优先级请求的响应性能.
Distributed file systems(DFSs)are generally employed for storing user data while designing a cloud storage system.The primary aspects of DFSs include efficient storage and management of metadata,data distribution strategies,and reliability of user data.In the case of data servers of a DFS,the FIFO(first in first out)strategy is adopted for scheduling I/O requests which are received by a data server daemon.The FIFO algorithm prioritises all such requests equally;requests that require better quality of services may therefore be blocked for long durations.To address this issue,a new priority based periodic scheduling algorithm(PPSA)has been proposed.Initially,PPSA classifies requests into different priority queues.Then,it periodically schedules requests according to their respective priorities and dedicated time slices.The obtained DFS simulation results show that PPSA can increase the response performance of heavy-load real-time requests by 20%,and can also ascertain the lowest response time performance for other requests.
作者
李宇
LI Yu(School of Software Engineening,Beijing Jiaotong University,Beijing 100044,China)
出处
《西南交通大学学报》
EI
CSCD
北大核心
2018年第4期857-864,共8页
Journal of Southwest Jiaotong University
关键词
大数据
云计算
分布式文件系统
周期性
优先级
调度算法
big data
cloud computing
distributed file system
periodic
priority
scheduling algorithms