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Wireless Networks: Applications, Challenges, and Security Issues Read chapter Read first chapter

2021 | OriginalPaper | Chapter

Fuzzy Q-Learning Based Controller for Cost and Energy Efficient Load Balancing in Cloud Data Center

Authors : Subhra Priyadarshini Biswal, Satya Prakash Sahoo, Manas Ranjan Kabat

Published in: Architectural Wireless Networks Solutions and Security Issues

Publisher: Springer Singapore

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Abstract

The goal of cloud controller is to focus on continuous delivery of services to user on demand basis followed by “pay-per-use” model. Due to the increasing demand of cloud services, energy consumption on data center is increasing rapidly which lead to high operational cost. The harmful emission from this energy intensive data center affects our environment badly and cause climate change significantly. So as an alternative we have focused on onsite green power generation to reduce the harmful effects of greenhouse gases. In this paper, we proposed a fuzzy Q-learning based self-learning controller to optimize the load for specific data center. The proposed method also helps to reduce uncertainty and solve the congestion issue efficiently through fuzzy linguistic behavior and membership function. In this proposal, fuzzy output parameter considered as reward value which is used to learn and update the state for each data centre.

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previous chapter Distributed Traversal Based Fault Diagnosis for Wireless Sensor Network
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Metadata
Title
Fuzzy Q-Learning Based Controller for Cost and Energy Efficient Load Balancing in Cloud Data Center
Authors
Subhra Priyadarshini Biswal
Satya Prakash Sahoo
Manas Ranjan Kabat
Copyright Year
2021
Publisher
Springer Singapore
Book
Architectural Wireless Networks Solutions and Security Issues

Print ISBN: 978-981-16-0385-3

Electronic ISBN: 978-981-16-0386-0

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-16-0386-0_9