Main Reference PaperNovel Scheduling Algorithms for Efficient Deployment of MapReduce Applications in Heterogeneous Computing Environments, IEEE Transactions on Cloud Computing, 2016 [Java/Hadoop].
  • This paper proposes, technique to efficiently utilize the task resources in MapReduce Framework. To achieve the resource utilization, this work propose a job scheduling algorithms called DJASL algorithm. According to the DJASL algorithm, the JobTracker first computes the capability of each TaskTracker and then sets the numbers of CPU and I/O slots accordingly.

+ Description
  • This paper proposes, technique to efficiently utilize the task resources in MapReduce Framework. To achieve the resource utilization, this work propose a job scheduling algorithms called DJASL algorithm. According to the DJASL algorithm, the JobTracker first computes the capability of each TaskTracker and then sets the numbers of CPU and I/O slots accordingly.

  • To improve the job running time and resource utilization.

  • To Improve the data locality.

+ Aim & Objectives
  • To improve the job running time and resource utilization.

  • To Improve the data locality.

  • The better scheduler scheme is contributed, the resource utilization can be predicted by looking at the current resource usage of the task. Such a scheduler would be a learning scheduler.

+ Contribution
  • The better scheduler scheme is contributed, the resource utilization can be predicted by looking at the current resource usage of the task. Such a scheduler would be a learning scheduler.

  • Java JDK 1.8, Hadoop 1.2.1

  • Netbeans 8.0.1, J2SE, Hadoop

+ Software Tools & Technologies
  • Java JDK 1.8, Hadoop 1.2.1

  • Netbeans 8.0.1, J2SE, Hadoop

  • B.E / B.Tech / M.E / M.Tech

+ Project Recommended For
  • B.E / B.Tech / M.E / M.Tech

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