[1]梁中军,孙志于,韩同欣,等.面向多等级应用的气象云资源调度方法研究[J].计算机技术与发展,2022,32(08):203-209.[doi:10. 3969 / j. issn. 1673-629X. 2022. 08. 033]
　LIANG Zhong-jun,SUN Zhi-yu,HAN Tong-xin,et al.Research on Resource Scheduling in Meteorological Cloud Environment for Multi-class Application[J].,2022,32(08):203-209.[doi:10. 3969 / j. issn. 1673-629X. 2022. 08. 033]
点击复制

面向多等级应用的气象云资源调度方法研究()
分享到：

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
32
期数:
2022年08期
页码:
203-209
栏目:
应用前沿与综合
出版日期:
2022-08-10

文章信息/Info

Title:
Research on Resource Scheduling in Meteorological Cloud Environment for Multi-class Application
文章编号:
1673-629X(2022)08-0203-06
作者:
梁中军1; 2; 孙志于1; 韩同欣2; 宋雅婷1; 张正阳1
1. 新疆气象信息中心,新疆 乌鲁木齐 830002;
2. 国家气象信息中心,北京 100081
Author(s):
LIANG Zhong-jun1; 2; SUN Zhi-yu1; HAN Tong-xin2; SONG Ya-ting1; ZHANG Zheng-yang1
1. Xinjiang Meteorological Information Center,Urumqi 830002,China;
2. National Meteorological Information Center,Beijing 100081,China
关键词:
气象云; 资源调度; 多等级应用; 蛙跳算法; 多目标优化
Keywords:
meteorological cloud; resource scheduling; multi-class application; leaping frog algorithm; multi objective optimization
分类号:
TP393
DOI:
10. 3969 / j. issn. 1673-629X. 2022. 08. 033
摘要:
气象云平台是集约支撑气象业务发展基础资源平台,如何合理调度气象云平台的基础资源已成为气象业务稳定运行的关键。 由于不同等级气象应用在汛期和日常具有特殊支撑需求,以及部分功能组件对气象云平台的物理服务器有约束要求,现有调度算法难以被直接应用。 为此,该文对问题建模,设计目标函数分别评价气象云平台的资源利用水平和对重要核心业务的支撑情况,基于物理服务器与功能组件之间的约束关系,将问题建模成一个多约束多目标优化问题。然后,设计一种改进蛙跳算法的气象云资源调度方法求解模型,该方法利用适应度函数来综合评价模型目标,并重新定义蛙跳算子,利用局部最优交叉操作和最优青蛙变异策略来迭代搜索最优资源调度方案。 最后,通过实验验证了该方法的效果。
Abstract:
Meteorological cloud platform is a basic resource platform that supports the development of meteorological services intensively.How to reasonably schedule the basic resources of meteorological cloud platform has become the key to the stable operation of meteorological services. Because different levels of meteorological applications have special support requirements in flood season and daily life,and some functional components have constraints on physical servers of meteorological cloud platform,existing scheduling algorithms aredifficult? to be directly applied. Therefore,we model the problem and design objective functions to evaluate respectively the resource utilization level of meteorological cloud platform and its support? for important core business. Based on the constraint relationship betweenphysical server and functional components,the problem is modeled as a multi-constraint multi-objective optimization problem. Then,aweather cloud resource scheduling model with improved leaping frog algorithm is designed. The fitness function is used to comprehensively evaluate the model objective, and the leaping frog operator is redefined,and the local optimal crossover operation and the optimalfrog mutation strategy are used to iteratively search for the optimal resource scheduling scheme. Finally,the effectiveness of the proposedmethod is verified by experiments.

相似文献/References:

[1]廖宁 刘建勋 王俊年.DPSO算法在服务网格资源调度中的应用[J].计算机技术与发展,2009,(08):104.
　LIAO Ning,LIU Jian-xun,WANG Jun-nian.Application of Discrete Particle Swarm Optimization Algorithm to Service Grid Resource Optimization Scheduling[J].,2009,(08):104.
[2]徐慧慧 石磊 陈信.网格资源调度算法研究[J].计算机技术与发展,2009,(09):76.
　XU Hui-hui,SHI Lei,CHEN Xin.Research on Grid Resource Scheduling Algorithm[J].,2009,(08):76.
[3]陈小飞 徐宏炳.基于网格的并行FFT计算研究[J].计算机技术与发展,2008,(03):67.
　CHEN Xiao-fei,XU Hong-bing.Research of Parallel FFT Computing Based on Grid[J].,2008,(08):67.
[4]储凡静 刘方爱.一种基于XML的个性化的资源需求描述机制[J].计算机技术与发展,2008,(06):67.
　CHU Fan-jing,LIU Fang-ai.Personal Resource Requirement Description Mechanism Based on XML[J].,2008,(08):67.
[5]姜姗 刘方爱.基于多任务拍卖的资源调度算法[J].计算机技术与发展,2006,(12):86.
　JIANG Shan,LIU Fang-ai.Resource Scheduling Algorithm Based on Multi- Job Auction[J].,2006,(08):86.
[6]舒文迪 解福.基于信誉度效益最优的网格调度算法研究[J].计算机技术与发展,2011,(01):133.
　SHU Wen-di,XIE Fu.Research of Grid Dispatch Algorithm Based on Optimal Credit Benefit[J].,2011,(08):133.
[7]吕克 徐夫田 舒文迪.基于信誉度的网格资源质量优化[J].计算机技术与发展,2011,(06):104.
　L Ke,XU Fu-tian,SHU Wen-di.Quality Optimization of Grid Resources Based on Credit[J].,2011,(08):104.
[8]刘永 王新华 邢长明[] 王硕.云计算环境下基于蚁群优化算法的资源调度策略[J].计算机技术与发展,2011,(09):19.
　LIU Yong,WANG Xin-hua,XING Chang-ming,et al.Resources Scheduling Strategy Based on Ant Colony Optimization Algorithms in Cloud Computing[J].,2011,(08):19.
[9]邢静宇[],张立臣[]. 基于能量控制与资源调度的信息物理系统建模[J].计算机技术与发展,2014,24(07):120.
　XING Jing-yu[],ZHANG Li-chen[]. Cyber Physical System Modeling Based on Energy Control and Resource Scheduling[J].,2014,24(08):120.
[10]朱新峰,吴名位,王国海.基于多目标优先级粒子群算法的资源调度策略[J].计算机技术与发展,2022,32(01):19.[doi:10. 3969 / j. issn. 1673-629X. 2022. 01. 004]
　ZHU Xin-feng,WU Ming-wei,WANG Guo-hai.Resource Scheduling Strategy Based on Multi-objective PriorityParticle Swarm Optimization[J].,2022,32(08):19.[doi:10. 3969 / j. issn. 1673-629X. 2022. 01. 004]

更新日期/Last Update: 2022-08-10