Main Reference PaperComparative Analysis of Energy-Efficient Scheduling Algorithms for Big Data Applications, IEEE Transactions on Big Data, 2018[Python/Apache Spark]
  • This work is proposed an energy efficient tasks scheduling algorithm to minimize the energy consumption for big data application in Spark. The proposed optimal scheduling algorithm maintains the strategy table records the energy consumption and execution time of tasks. This table is updated at the end of Spark application running. When a new node is added to the cluster or the energy efficiency changes, the energy efficiency strategy table will be updated and schedules the tasks in spark cluster.

Description
  • This work is proposed an energy efficient tasks scheduling algorithm to minimize the energy consumption for big data application in Spark. The proposed optimal scheduling algorithm maintains the strategy table records the energy consumption and execution time of tasks. This table is updated at the end of Spark application running. When a new node is added to the cluster or the energy efficiency changes, the energy efficiency strategy table will be updated and schedules the tasks in spark cluster.

  • To reduce the energy consumption in Spark cluster.

  • To reduce the execution time of workloads.

Aim & Objectives
  • To reduce the energy consumption in Spark cluster.

  • To reduce the execution time of workloads.

  • Effective missing data prediction mechanism is contributed.

Contribution
  • Effective missing data prediction mechanism is contributed.

  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

Project Recommended For
  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

Order To Delivery
  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

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