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Load Balancing in Cloud Through Multi Objective Optimization

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Advances in Decision Sciences, Image Processing, Security and Computer Vision (ICETE 2019)

Part of the book series: Learning and Analytics in Intelligent Systems ((LAIS,volume 3))

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Abstract

The Scheduling and Load balancing in cloud is considered as NP complete problem where the tasks are assigned to the cloud are dynamic in nature so the heuristic approach can be followed to find the solution. Load balancing directly affects the reliability, response time, through put and energy efficiency of a server. The optimized solution for load balancing should consider various objectives like minimizing energy consumption and minimum execution time so that reduced cost. Balancing the load across cloud servers is possible through virtual machine (VM) migration from overloaded servers to under loaded servers conditionally. Even migration of VMs from under loaded servers may take place in cloud to release the under loaded servers and make them free so that the energy consumption can be improved.

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Author information

Authors and Affiliations

  1. Computer Science Engineering, Osmania University, Hyderabad, India

    S. Jyothsna

  2. Department of Information Technology, CBIT, Hyderabad, India

    K. Radhika

Authors
  1. S. Jyothsna
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  2. K. Radhika
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Corresponding author

Correspondence to S. Jyothsna .

Editor information

Editors and Affiliations

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

    Suresh Chandra Satapathy

  2. Department of CSE, CMR Technical Campus, Hyderabad, Telangana, India

    K. Srujan Raju

  3. Department of CSE, University College of Engineering, Osmania University, Hyderabad, Telangana, India

    K. Shyamala

  4. Department of ECE, University College of Engineering, Osmania University, Hyderabad, Telangana, India

    D. Rama Krishna

  5. Institute of Informatics and Telecommunications, Reshetnev Siberian State University of Science and Technology, Krasnoyarsk, Russia

    Margarita N. Favorskaya

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Jyothsna, S., Radhika, K. (2020). Load Balancing in Cloud Through Multi Objective Optimization. In: Satapathy, S.C., Raju, K.S., Shyamala, K., Krishna, D.R., Favorskaya, M.N. (eds) Advances in Decision Sciences, Image Processing, Security and Computer Vision. ICETE 2019. Learning and Analytics in Intelligent Systems, vol 3. Springer, Cham. https://doi.org/10.1007/978-3-030-24322-7_38

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