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Energy-Efficient Resource Allocation in Data Centers Using a Hybrid Evolutionary Algorithm

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Machine Learning for Intelligent Decision Science

Part of the book series: Algorithms for Intelligent Systems ((AIS))

Abstract

Energy efficient scheduling in a cloud data center aims at effectively utilizing available resources and improving the energy utilization. Resource scheduling is NP-hard and often requires substantial computational resources. This chapter presents an interactive PSO-GA algorithm that performs parallel processing of particle swarm optimization (PSO) and genetic algorithm (GA) using multi-threading and shared memory for information exchange to enhance convergence time and global exploration. With the proposed approach, this chapter demonstrates an efficient virtual machine placement in a data center that greatly reduces the total energy consumption up to 34% and the convergence time up to 50% compared to PSO, GA, and modified best-fit decreasing approaches. Further, this method achieves average parallel efficiency of 90% and a speed up of 1.5. This chapter also evaluates effectiveness of the proposed algorithm on benchmark optimization test problems over the state-of-the art algorithms.

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Acknowledgements

The research presented is supported by the project NextGenSmart DC (629.002.102) funded by the Netherlands Organization for Scientific Research (NWO).

Author information

Authors and Affiliations

  1. Cognizant Technology Solutions, Hyderabad, India

    V. Dinesh Reddy

  2. National Institute of Technology, Tiruchirappalli, India

    G. R. Gangadharan

  3. Cognizant Technology Solutions, Chennai, India

    G. S. V. R. K. Rao

  4. Institute of Architecture of Application Systems, University of Stuttgart, Stuttgart, Germany

    Marco Aiello

Authors
  1. V. Dinesh Reddy
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  2. G. R. Gangadharan
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  3. G. S. V. R. K. Rao
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  4. Marco Aiello
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Corresponding author

Correspondence to G. R. Gangadharan .

Editor information

Editors and Affiliations

  1. School of Computer Engineering, Kalinga Institute of Industrial Technology, Deemed to be University, Bhubaneswar, Odisha, India

    Jitendra Kumar Rout

  2. School of Computer Engineering, Kalinga Institute of Industrial Technology, Deemed to be University, Bhubaneswar, Odisha, India

    Minakhi Rout

  3. School of Computer Engineering, Kalinga Institute of Industrial Technology, Deemed to be University, Bhubaneswar, Odisha, India

    Himansu Das

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Reddy, V.D., Gangadharan, G.R., Rao, G.S.V.R.K., Aiello, M. (2020). Energy-Efficient Resource Allocation in Data Centers Using a Hybrid Evolutionary Algorithm. In: Rout, J., Rout, M., Das, H. (eds) Machine Learning for Intelligent Decision Science. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-3689-2_4

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