Computer Science

Computer Science ›› 2021, Vol. 48 ›› Issue (11A): 225-231.doi: 10.11896/jsjkx.201200066

• Big Data & Data Science • Previous Articles     Next Articles

Analysis of Workload Failure in Co-located Data Centers

JIANG Cong-feng1, YIN Ji-liang1, HU Hai-zhou1, YAN Long-chuan2, ZHANG Ji-lin3, WAN Jian4, QIU Ye-liang5   

  1. 1 School of Computer Science and Technology,Hangzhou Dianzi University,Hangzhou 310018,China
    2 State Grid Electrical Information Communication Co.,Ltd.,Beijing 100053,China
    3 School of Cyberspace Security,Hangzhou Dianzi University,Hangzhou 310018,China
    4 School of Information and Electronic Engineering,Zhejiang University of Science and Technology,Hangzhou 310023,China
    5 Alibaba Cloud Computing Co.,Ltd.,Hangzhou 311121,China
  • Online:2021-11-10 Published:2021-11-12
  • About author:JIANG Cong-feng,born in 1980,Ph.D,professor,Ph.D.supervisor,is a member of China Computer Federation.His main research interests include cloud computing,system optimization and performance evaluation.
  • Supported by:
    National Key Research and DevelopmentPragram of China(2017YFB101000),National Natural Science Foundation of China(61972118) and Zhejiang Key Research and Development Program of China(2019C01059).

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Abstract: Datacenter workload co-location can greatly increase the resource utilization of cloud data centers,while it also increases the scheduling complexity and job failures.In this paper,the cluster trace dataset from Alibaba Cloud is investigated,and the characteristics of batch workload failure rates and cluster resource utilization are studied.The main contributions and findings of this paper are as follows.First,Only a small portion of specific types of jobs account for the overall cluster failure rate and resource waste due to job failures.Second,the execution time of task failover in the Fuxi distributed scheduler can be quantified as Gaussian distribution,and the task scheduling delay can be quantified as Zipf distribution.Third,Based on the failed instances distribution on cluster nodes,it's found that the job failures randomly occur in the cluster spatially,and the failed jobs are prone to fail again after their failovers.Moreover,job failures occur in the cluster temporally but not evenly distributed in the cluster.Fourth,the mean time between failures of the cluster is calculated according to instance failure data,and the results show that most of the cluster nodes have the mean time between failures values as 1000 seconds,while a few of them have the mean time between failures values as 10000 seconds.

Key words: Co-located cluster, Distributed scheduling, Failure analysis, Workload characteristics

CLC Number: 

  • TN391
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[1] TIAN Yu-li, LI Ning. System Usage Analysis and Failure Analysis for Cloud Computing [J]. Computer Science, 2020, 47(12): 50-55.
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