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A Walkthrough in Live Migration Strategies for Energy-Aware Resource Management in Cloud

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Autonomic Computing in Cloud Resource Management in Industry 4.0

Part of the book series: EAI/Springer Innovations in Communication and Computing ((EAISICC))

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Abstract

The era of modern computing has fascinated the masses and has outreached to their daily grinds via provisioning day-to-day services for facilitating their work. With this extensive reachability of human populace on service-oriented paradigms, the requirement to manage the existing resources has also escalated. Cloud being the global capturer of pay-per-utility model has become the point of convergence of modern technologies in serving the clients in their day-to-day chores. The extensions of cloud computing, majorly, IoT, Fog Model, and NBIoT, have proliferated across geographical boundaries to every corner of the world. Thus, the exaggerating use of such platforms for services has created a dire need for resource management and is becoming as a major challenge to be addressed before service providers. Besides, the increasing traffic on cloud has also posed a threatening alarm before the cloud human entities and, as per the available statistics, electricity consumption will hike from 632 to 1963 Billion Kilo Watt Hours by the end of 2020 and CO2 emission would be ~1034 megatons. Although it has encapsulated the research focus, and many heuristics have been proposed in this direction, still an infallible solution strategy needs to be derived. Bin packing is an upstanding solution to the problem, and its pragmatic implementation is realized through employing live migration strategies. Consequently, this research study presents an extensive exploration in the direction of resource management and energy management in cloud along with the techniques of live migration as a mitigation.

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Authors and Affiliations

  1. Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, India

    Neha Gupta, Kamali Gupta, Meenu Khurana & Deepali Gupta

  2. Department of Virtualization, School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India

    Anurag Jain

  3. Department of Informatics, School of Computer Science, University of Petroleum and Energy Studies (UPES), Dehradun, Uttarakhand, India

    Bhupesh Kumar Dewangan

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  1. Neha Gupta
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  2. Kamali Gupta
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  3. Meenu Khurana
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  4. Deepali Gupta
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  5. Anurag Jain
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  6. Bhupesh Kumar Dewangan
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Correspondence to Kamali Gupta .

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Editors and Affiliations

  1. Department of Informatics, School of Computer Science University of Petroleum and Energy Studies (UPES), Dehradun, Uttarakhand, India

    Tanupriya Choudhury

  2. Department of Informatics, School of Computer Science University of Petroleum and Energy Studies (UPES), Dehradun, Uttarakhand, India

    Bhupesh Kumar Dewangan

  3. Department of Informatics, School of Computer Science University of Petroleum and Energy Studies (UPES), Dehradun, Uttarakhand, India

    Ravi Tomar

  4. Computing and Software Engineering, Arba Minch University, Arba Minch, Ethiopia

    Bhupesh Kumar Singh

  5. Nanyang Technological University (NTU), Singapore, Singapore

    Teoh Teik Toe

  6. Duy Tan University, Da Nang, Vietnam

    Nguyen Gia Nhu

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Gupta, N., Gupta, K., Khurana, M., Gupta, D., Jain, A., Dewangan, B.K. (2021). A Walkthrough in Live Migration Strategies for Energy-Aware Resource Management in Cloud. In: Choudhury, T., Dewangan, B.K., Tomar, R., Singh, B.K., Toe, T.T., Nhu, N.G. (eds) Autonomic Computing in Cloud Resource Management in Industry 4.0. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-71756-8_16

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