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An adaptive task allocation technique for green cloud computing

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Abstract

The rapid growth of todays IT demands reflects the increased use of cloud data centers. Reducing computational power consumption in cloud data center is one of the challenging research issues in the current era. Power consumption is directly proportional to a number of resources assigned to tasks. So, the power consumption can be reduced by a demotivating number of resources assigned to serve the task. In this paper, we have studied the energy consumption in cloud environment based on varieties of services and achieved the provisions to promote green cloud computing. This will help to preserve overall energy consumption of the system. Task allocation in the cloud computing environment is a well-known problem, and through this problem, we can facilitate green cloud computing. We have proposed an adaptive task allocation algorithm for the heterogeneous cloud environment. We applied the proposed technique to minimize the makespan of the cloud system and reduce the energy consumption. We have evaluated the proposed algorithm in CloudSim simulation environment, and simulation results show that our proposed algorithm is energy efficient in cloud environment compared to other existing techniques.

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Authors and Affiliations

  1. National Institute of Technology, Rourkela, India

    Sambit Kumar Mishra, Bibhudatta Sahoo & Sajay Kumar Jena

  2. University of Technology Sydney, Sydney, Australia

    Deepak Puthal

  3. Fordham University, Bronx, NY, USA

    Mohammad S. Obaidat

  4. University of Jordan, Amman, Jordan

    Mohammad S. Obaidat

Authors
  1. Sambit Kumar Mishra
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  2. Deepak Puthal
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  3. Bibhudatta Sahoo
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  4. Sajay Kumar Jena
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  5. Mohammad S. Obaidat
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Corresponding author

Correspondence to Deepak Puthal.

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Mishra, S.K., Puthal, D., Sahoo, B. et al. An adaptive task allocation technique for green cloud computing. J Supercomput 74, 370–385 (2018). https://doi.org/10.1007/s11227-017-2133-4

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  • DOI: https://doi.org/10.1007/s11227-017-2133-4

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