基于推测的无响应任务自适应容错调度算法

Adaptive Fault-tolerant Scheduling Algorithm for Unresponsive Task Based on Speculation

已有的基于静态的执行失败判定时间阈值的无响应任务容错调度算法,不能适应大数据处理中心动态的集群负载。针对该问题,提出判定无响应任务执行失败时间阈值自适应调整方法。基于该模型,设计了自适应的无响应任务容错调度算法(AFTS)。AFTS算法通过分析作业规模、单个任务大小和剩余作业推测执行时间等参数,自适应地调整无响应任务判定执行失败的时间阈值,以减少无响应任务对整体作业执行效率的影响,降低作业响应时间。基于开发的原型系统,验证了自适应判定方法,测试了算法的性能。实验结果表明,AFTS算法在作业响应时间等方面优于已有的无响应任务容错调度算法。

Current fault-tolerant scheduling algorithm for unresponsive task,based on static execution failed time threshold,can not adapt to dynamic cluster load of large data processing center.To address this issue,an adaptive execution failed time threshold method was proposed.Based on this method,an adaptive fault-tolerant scheduling algorithm(AFTS)for unresponsive task was designed.AFTS adjusts unresponsive task's time threshold to be determined failure dynamically and to reduce the job response time,according to the information of job size,the size of individual tasks and the remaining operating time.A prototype system using AFTS is developed,on which the validation of the adaptive execution failed time threshold method and the evaluation of AFTS's performance are carried out.It is shown that AFTS outperforms current fault-tolerant scheduling algorithm in term of the job response time.