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A Cloud Resource Allocation Strategy Based on Fitness Based Live Migration and Clustering

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Abstract

With the advent of cloud computing and its boom in recent years, resource management tends to gain interest. Cloud offers different types of services necessary to mankind, the advancement being the virtual machines as resources in Infrastructure as a service. Our proposed fitness function detects the Hotspot and Coldspot to manage the resources dynamically by performing load balancing and server consolidation which is achieved through migration. The resource usage is maximized through utilization of the resources in their idle periods by forming clusters. The proposed system is implemented with open-source cloud framework OpenNebula. The experimental results prove that proposed system maximizes the resource utilization even in their idle periods.

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Acknowledgements

This work is financially supported by (Ref. No. 42-137 SR) University Grants Commission, New Delhi under Major Research Project.

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Authors and Affiliations

  1. Department of Computer Technology, Anna University, MIT, Chromepet, Chennai, India

    Valliyammai Chinnaiah, Sindhu Gudi Pudi, Thamarai Selvi Somasundaram & S. Sameer Basha

Authors
  1. Valliyammai Chinnaiah
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  2. Sindhu Gudi Pudi
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  3. Thamarai Selvi Somasundaram
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  4. S. Sameer Basha
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Correspondence to Valliyammai Chinnaiah.

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Chinnaiah, V., Gudi Pudi, S., Somasundaram, T. et al. A Cloud Resource Allocation Strategy Based on Fitness Based Live Migration and Clustering. Wireless Pers Commun 98, 2943–2958 (2018). https://doi.org/10.1007/s11277-017-5009-2

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  • DOI: https://doi.org/10.1007/s11277-017-5009-2

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