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

Yuvaraj, N. and Raja, R. and Ganesan, V. and Dhas, Suresh Gnana (2018) Analysis on Improving the Response Time with PIDSARSA-RAL in ClowdFlows Mining Platform. EAI Endorsed Transactions on Energy Web, 5 (20): e2. ISSN 2032-944X

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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.

Item Type: Article
Uncontrolled Keywords: SARSA Active Learning, Big Data Mining, PID Controller, Reinforcement Learning
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor II.
Date Deposited: 21 Sep 2020 13:36
Last Modified: 21 Sep 2020 13:36
URI: https://eprints.eudl.eu/id/eprint/515

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