绿色云环境下基于动态匹配机制的资源调度策略  

RESOURCE SCHEDULING ALGORITHM BASED ON DYNAMIC MATCHING MECHANISM IN GREEN CLOUD ENVIRONMENT

作　　者：李维勇[1] 王颖 张伟[2] Li Weiyong;Wang Ying;Zhang Wei(School of Network and Communication,Nanjing Vocational College of Information Technology,Nanjing 210023,Jiangsu,China;School of Computer Science,Nanjing University of Posts and Telecommunications,Nanjing 210023,Jiangsu,China)

机构地区：[1]南京信息职业技术学院网络与通信学院,江苏南京210023 [2]南京邮电大学计算机学院,江苏南京210023

出　　处：《计算机应用与软件》2025年第2期299-307,386,共10页Computer Applications and Software

基　　金：国家自然科学基金项目(61672297);2019年中国特色高水平高职学校和专业建设计划项目(教职成函〔2019〕14号)。

摘　　要：针对云计算系统低性能高能耗的问题,提出一种基于动态匹配机制的资源调度算法。根据价值度和紧急度进行任务分类,采用四象限法则将全局云任务队列拆成四个分队列;利用具有记忆标识的颜色Petri网建立资源节点可用度评估模型,根据节点可用度所处区间动态划分四级资源池;将四个分队列中的任务匹配调度到四级资源池中,同时,资源池采用不同的电源管理技术进行管理。仿真结果表明,相对传统的资源调度策略,该策略能够有效保证用户服务性能,并显著降低系统总能耗开销。Aiming at the problem of low performance and high energy consumption in the cloud computing system,this paper proposes a resource scheduling algorithm based on dynamic matching mechanism.Tasks were classified according to the value and emergency,and the global cloud task queue was divided into four sub queues by four quadrant laws.The availability evaluation model was established by using colored Petri Net with memory identifier,and the nodes were dynamically divided into four-level resource pools according to the different availability zone.The tasks in sub-queues were matched and scheduled to four-level resource pools,at the same time,the resource pool was managed by different power management technologies.The simulation results show that compared with the traditional resource scheduling strategy,the proposed strategy can effectively guarantee the user service performance and significantly reduce the total energy consumption of the system.

关 键 词：云计算 资源调度 任务分类 颜色PETRI网 电源管理 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]