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ew 18(20): e2

Research Article

Analysis on Improving the Response Time with PIDSARSA-RAL in ClowdFlows Mining Platform

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  • @ARTICLE{10.4108/eai.12-9-2018.155557,
        author={N. Yuvaraj and R. Arshath Raja and Dr. V. Ganesan and  Dr. C. Suresh Gnana Dhas},
        title={Analysis on Improving the Response Time with PIDSARSA-RAL in ClowdFlows Mining Platform},
        journal={EAI Endorsed Transactions on Energy Web and Information Technologies},
        volume={5},
        number={20},
        publisher={EAI},
        journal_a={EW},
        year={2018},
        month={9},
        keywords={SARSA Active Learning, Big Data Mining, PID Controller, Reinforcement Learning},
        doi={10.4108/eai.12-9-2018.155557}
    }
    
  • N. Yuvaraj
    R. Arshath Raja
    Dr. V. Ganesan
    Dr. C. Suresh Gnana Dhas
    Year: 2018
    Analysis on Improving the Response Time with PIDSARSA-RAL in ClowdFlows Mining Platform
    EW
    EAI
    DOI: 10.4108/eai.12-9-2018.155557
N. Yuvaraj1,*, R. Arshath Raja2, Dr. V. Ganesan3, Dr. C. Suresh Gnana Dhas4
  • 1: Research Scholar, Department of Computer Science and Engineering, St. Peter's Institute of Higher Education and Research, St. Peter's University, Chennai, Tamilnadu, India - 600054
  • 2: Research Scholar, Department of Electronics and Communication Engineering, BS Abdur Rahman Crescent University, Chennai, Tamilnadu, India - 600048.
  • 3: Director, R&D, Innovative Science and Technology Publications, Chennai, Tamilnadu, India-600088.
  • 4: Professor & Head, Department of CSE, Vivekanandha College of Engineering for Women, Elayampalayam, Namakkal, Tamilnadu, India – 637205.
*Contact email: yraj1989@gmail.com

Abstract

This paper provides an improved parallel data processing in Big Data mining using ClowdFlows platform. The big data processing involves an improvement in Proportional Integral Derivative (PID) controller using Reinforcement Adaptive Learning (RAL). The Reinforcement Adaptive Learning involves the use of Actor-critic State–action–reward–state–action (SARSA) learning that suits well the stream mining module of ClowdFlows platform. The study concentrates on batch mode processing in Big Data mining model with the use of proposed PID-SARSA-RAL. The experimental evaluation with the conventional ClowdFlows platform proved the effectiveness of the proposed method over continuous parallel workflow execution.

Keywords
SARSA Active Learning, Big Data Mining, PID Controller, Reinforcement Learning
Received
2018-05-05
Accepted
2018-07-11
Published
2018-09-12
Publisher
EAI
http://dx.doi.org/10.4108/eai.12-9-2018.155557

Copyright © 2018 N. Yuvaraj et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.

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