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Advances in Distributed Computing and Machine Learning pp 3–14Cite as

Unconstrained Power Management Algorithm for Green Cloud Computing

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Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 302))

Abstract

Green cloud computing (GCC) is an emerging trend to reduce the environmental impact of information and communications technology (ICT) devices. Here, power management plays a vital role in providing potential solutions. It helps to ensure efficient, safe and reliable electric distribution to the devices connected to it. In general, the power supply of datacenters is connected to the grid, which is operated using non-renewable or brown energy (NRE) sources (like fossil fuels). These sources will not be replenished and run out over time. Moreover, they are harmful to the environment by releasing carbon dioxide, heat and other gasses. Subsequently, the power supply of datacenters is connected to renewable or green energy (RE) sources (like solar) in order to reduce the environmental impact. However, these sources are less reliable and seasonal. Therefore, nowadays, datacenters use both NRE and RE sources to make a trade-off. In this paper, we propose unconstrained power management (UPM) algorithm for GCC. We consider three power supplies, namely grid, PV and battery, to handle the load power demand of the user requests (URs) submitted to the datacenters. The proposed algorithm tries to fulfill such demand using RE sources. In case of scarcity in RE sources, it manages the load power using NRE sources. We simulate the proposed algorithm by considering three scenarios, namely NRE sources, RE sources and both, using five different instances. The simulation results are compared and analyzed in terms of three performance metrics, namely overall cost (OC), UR assigned to NRE (UNRE) and UR assigned to RE (URE), to show the applicability of the proposed algorithm under three different scenarios.

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Author information

Authors and Affiliations

  1. Veer Surendra Sai University of Technology, Burla, 768018, Odisha, India

    Sanjib Kumar Nayak & Satyabrata Das

  2. National Institute of Technology, Warangal, 506004, Telangana, India

    Sanjaya Kumar Panda

Authors
  1. Sanjib Kumar Nayak
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  2. Sanjaya Kumar Panda
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  3. Satyabrata Das
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Information Technology, Institute of Technical Education and Research(ITER), Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, Odisha, India

    Jyoti Prakash Sahoo

  2. School of Information Technology and Engineering (SITE), Vellore Institute of Technology, Vellore, India

    Asis Kumar Tripathy

  3. Center for Forensic Science, School of Mathematical and Physical Science, University of Technology Sydney, Broadway, NSW, Australia

    Manoranjan Mohanty

  4. Department of Computer Science and Information Engineering (CSIE), Providence University, Taichung, Taiwan

    Kuan-Ching Li

  5. Department. of Computer Science and Information Technology, Institute of Technical Education and Research(ITER), Siksha ‘O’ Anusandhan Deemed to be University, Bhubaneswar, India

    Ajit Kumar Nayak

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Nayak, S.K., Panda, S.K., Das, S. (2022). Unconstrained Power Management Algorithm for Green Cloud Computing. In: Sahoo, J.P., Tripathy, A.K., Mohanty, M., Li, KC., Nayak, A.K. (eds) Advances in Distributed Computing and Machine Learning. Lecture Notes in Networks and Systems, vol 302. Springer, Singapore. https://doi.org/10.1007/978-981-16-4807-6_1

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