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Resource management and job scheduling of China earthquake grid experiment system: Construction of resource management and job dynamic scheduling model ProRMJS

Resource management and job scheduling of China earthquake grid experiment system: Construction of resource management and job dynamic scheduling model ProRMJS

作     者:侯建民 刘瑞丰 单保华 赵永 牛爱军 邹立晔 侯立华 韩军 

作者机构:China Earthquake Networks CenterBeijing 100036 China Institute of Computing Technology Chinese Academy of SciencesBeijing 100080 China The Second Academy of China-Aerospace Science and Industry CorporationBeijing 100854 China 

出 版 物:《Acta Seismologica Sinica(English Edition)》 (地震科学)

年 卷 期:2006年第19卷第6期

页      面:695-703页

核心收录:

学科分类:12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 081201[工学-计算机系统结构] 0812[工学-计算机科学与技术(可授工学、理学学位)] 

基  金:Project "Seismic Data Share" from Ministry of Science and Technology of China 

主  题:grid computing earthquake grid resource management job allocation 

摘      要:Grid technique is taken as the third generation internet technology and resource management is the core of it. Aiming at the problems of resource management of CEDAGrid (China Earthquake Disaster Alleviation and Simulation Grid) in its preliminary construction, this paper presents a resource management and job scheduling model: ProRMJS to solve these problems. For platform supposed agreeably each computing node can provide computation service, ProRMJS uses "computation pool" to support scheduler, and then the scheduler allocates jobs dynamically according to computing capability and status of each node to ensure the stability of the platform. At the same time, ProRMJS monitors the status of job on each node and sets a time threshold to manage the job scheduling. By estimating the computing capability of each node, ProRMJS allocates jobs on demand to solve the problem of supposing each node can finish the job acquiescently. When calculating the computing capability of each node, ProRMJS allows for the various factors that affect the computing capability and then the efficiency of the platform is improved. Finally the validity of the model is verified by an example.

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