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A Proposed Framework for Autonomic Resource Management in Cloud Computing Environment

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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))

Abstract

The technological revolution during the past decades has resulted in the explosion of data leading to an emergence of cloud computing that subsequently led to fog computing. These technologies are continuously striving for increased computational capability so as to inculcate it in our daily lives and obtain ever larger infrastructures. However, inclusion of heterogeneous infrastructures in such systems poses different challenges like complexity, security, and manageability. For the same, it necessitates an autonomic, self-managing system to address the growing complexities in its realization in terms of cost and complexity. These challenges have opened avenues for Autonomic computing, an approach that aims to provide significant benefits in terms of speed and automation by managing complex and heterogeneous infrastructure. Additionally, autonomic computing overcomes the limitations of manual control by providing an economical and robust solution in minimum time. As a result, autonomic computing has observed its widespread application since its inception. The proposed chapter focuses on the various aspects of autonomic computing like self-healing, self-optimization, self-protection, and so on, and presents a simplistic architecture. The proposed architecture implements autonomic computing infrastructure to dynamically control and manage services to develop and deploy an intelligent application. Hence, the proposed framework achieves the autonomic services to maintain the autonomic requirements of a wide range of network applications and services.

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Author information

Authors and Affiliations

  1. CSED, Lokmanya Tilak College of Engineering, Navi Mumbai, India

    Monika Mangla, Sanjivani Deokar & Rakhi Akhare

  2. Islamic Azad University, Tehran, Iran

    Mehdi Gheisari

Authors
  1. Monika Mangla
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  2. Sanjivani Deokar
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  3. Rakhi Akhare
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  4. Mehdi Gheisari
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Corresponding author

Correspondence to Monika Mangla .

Editor information

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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Mangla, M., Deokar, S., Akhare, R., Gheisari, M. (2021). A Proposed Framework for Autonomic Resource Management in Cloud Computing Environment. 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_10

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  • DOI: https://doi.org/10.1007/978-3-030-71756-8_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-71755-1

  • Online ISBN: 978-3-030-71756-8

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