College of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China;Suzhou Institute for Advanced Study, University of Scienceand Technology of China, Suzhou 215123, China 在期刊界中查找 在百度中查找 在本站中查找
College of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China;Suzhou Institute for Advanced Study, University of Scienceand Technology of China, Suzhou 215123, China 在期刊界中查找 在百度中查找 在本站中查找
MapReduce is a popular batch data processing framework in cloud computing field. Sharing MapReduce cluster and meeting the deadlines of jobs is a key problem to be solved. This paper proposes a two phase real-time scheduling algorithm which separate scheduling into job scheduling and task scheduling.It uses sampling method to estimate the task excuting time so that the scheduler can make a decision on how many slots should be assigned to the job and how to calculate the job's priority. Using delay-scheduling scheme in task scheduling, the"computing locality"problem can be solved well. Experiments result shows that the scheduling algorithm implemented in this paper satisfies the job's real-time requirement as well as throughput of the cluster.