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An Energy-Aware Dynamic Resource Management Technique Using Deep Q-Learning Algorithm and Joint VM and Container Consolidation Approach for Green Computing in Cloud Data Centers

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Distributed Computing and Artificial Intelligence, Special Sessions, 17th International Conference (DCAI 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1242))

Abstract

These days by a high increase in the amount of computation and big data gathering and analysis, everybody needs more resources. Buying more computational and storage resources are so expensive. However, cloud computing solved this problem by providing a “pay as you go” plans therefor, users will only pay for resources that they used. However, using this technology has its challenges. One of them is resource management, which is focusing on the methodologies of dedicating resources to the users with the minimum of waste. In this paper, we propose a novel energy-aware resource management technique, using the concepts of both joint VM and container consolidation approach and deep Q-Learning algorithm for green computing in cloud data centers in order to minimize the waste of resources, migration rate, and energy.

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Author information

Authors and Affiliations

  1. Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

    Niloofar Gholipour

  2. BISITE Research Group, University of Salamanca, Salamanca, Spain

    Niloufar Shoeibi

  3. ICT Research Institute, Tehran, Iran

    Ehsan Arianyan

Authors
  1. Niloofar Gholipour
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  2. Niloufar Shoeibi
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  3. Ehsan Arianyan
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Corresponding authors

Correspondence to Niloofar Gholipour or Niloufar Shoeibi .

Editor information

Editors and Affiliations

  1. IoT European Digital Innovation Hub, Bioinformatics Intelligent Systems and Educational Technology Research Group, Department of Computer Science, Faculty of Science, University of Salamanca, Salamanca, Spain

    Sara Rodríguez González

  2. GRASIA Research Group, Facultad de Informática, Universidad Complutense de Madrid, Madrid, Spain

    Alfonso González-Briones

  3. Faculty of Mechanical Engineering, Department of Production Computerisation and Robotisation, Lublin University of Technology, Lublin, Poland

    Arkadiusz Gola

  4. Cerca Trova Ltd, Sofia, Bulgaria

    George Katranas

  5. Department of Biology, Ecology and Earth Science, University of Calabria, Arcavacata di Rende, Cosenza, Italy

    Michela Ricca

  6. Bulgarian Academy of Sciences, Institute of Mathematics and Informatics, Sofia, Bulgaria

    Roussanka Loukanova

  7. Bulgarian Academy of Sciences, Institute of Mathematics and Informatics, Salamanca, Spain

    Javier Prieto

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Gholipour, N., Shoeibi, N., Arianyan, E. (2021). An Energy-Aware Dynamic Resource Management Technique Using Deep Q-Learning Algorithm and Joint VM and Container Consolidation Approach for Green Computing in Cloud Data Centers. In: Rodríguez González, S., et al. Distributed Computing and Artificial Intelligence, Special Sessions, 17th International Conference. DCAI 2020. Advances in Intelligent Systems and Computing, vol 1242. Springer, Cham. https://doi.org/10.1007/978-3-030-53829-3_26

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