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中文摘要：
云计算集群环境下多资源分配的公平性是考量资源调度子系统最重要的指标之一,DRF作为通用的多资源公平分配算法,在异构异质的集群环境下可能有失公平性。在研究Mesos框架中DRF多资源公平分配算法的基础上,设计并实现了增加机器性能评估影响因子的meDRF分配算法。将计算节点的机器性能得分,作为DRF主导份额计算的因子,使得计算任务有均等的机会获得优质计算资源和劣质计算资源。通过选取K-means、Bayes及PageRank等多种作业进行实验,实验结果表明：meDRF较DRF分配算法更能体现多资源分配的公平性,且资源分配具有更好的稳定性,能有效提高系统资源的利用率。
英文摘要：
The fairness of multi-resource allocation is one of the most important indicators in the resource scheduling subsystem,Dominant Resource Fairness（ DRF）,as a general resource allocation algorithm for multi-resources scenarios,it may be unfair in heterogeneous cluster environment. On the basis of the research on the DRF multi-resource fair allocation algorithm under Mesos framework environment,me DRF allocation algorithm was designed and implemented to evaluate the influence factors of the performance of the server. The machine performance scores of computing nodes,as the dominant factor of DRF share calculation,made computing tasks have equal chance to obtain high quality computing resources and poor computing resources.Experiments were conducted by using K-means,Bayes and PageRank jobs under Hadoop. The experimental results show that,compared with DRF allocation algorithm,the me DRF algorithm can reflect more fairness of the allocation of resources,and the allocation of resources has better stability,which effectively improves the utilization of system resources.
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