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PT-GA-IRIAL: Enhanced Energy Efficient Approach to Select Migration VMs for Load Balancing in Cloud Computing Environment

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Second International Conference on Computer Networks and Communication Technologies (ICCNCT 2019)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 44))

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Abstract

Cloud computing is a very well known technology for all business people, software developers, end-users, and so on. Significant researches are going on to balance the cloud load. The migration of heavily loaded Virtual Machines (VMs) into lightly loaded Physical Machines (PMs) balances the Cloud load. In Resource Intensity Aware Load Balancing (RIAL) method, based on the weight of resources under utilization, it selected the VMs from heavily loaded PMs for migration and chosen the lightly loaded PMs as destination. An Improved RIAL was proposed to consider both lightly and heavily loaded PMs as destination. Later it was enhanced in the proposed Power Consumption Aware- Traffic Aware- IRIAL (PT-IRIAL) method with the consideration of power consumption, temperature and traffic measures to select the VMs for migration and select PMs for destination. From all these, in this current paper, the crossover and mutation process of GA is utilized to optimally select the migration VMs and choose the destination PMs. Thus this GA based load optimization algorithm optimally maps the migration VMs with the destination PMs efficiently.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Coimbatore Institute of Technology, Coimbatore, Hindusthan College of Arts and Science, Coimbatore, Tamilnadu, India

    V. Radhamani

  2. Department of Computer Science, Hindusthan College of Arts and Science, Coimbatore, Tamilnadu, India

    G. Dalin

Authors
  1. V. Radhamani
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  2. G. Dalin
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Corresponding author

Correspondence to V. Radhamani .

Editor information

Editors and Affiliations

  1. Department of Computer Science Engineering, RVS Technical Campus, Coimbatore, Tamil Nadu, India

    S. Smys

  2. University of the Ryukyus, Okinawa, Japan

    Tomonobu Senjyu

  3. Department of Telecommunication Engineering, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic

    Pavel Lafata

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Radhamani, V., Dalin, G. (2020). PT-GA-IRIAL: Enhanced Energy Efficient Approach to Select Migration VMs for Load Balancing in Cloud Computing Environment. In: Smys, S., Senjyu, T., Lafata, P. (eds) Second International Conference on Computer Networks and Communication Technologies. ICCNCT 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 44. Springer, Cham. https://doi.org/10.1007/978-3-030-37051-0_66

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  • DOI: https://doi.org/10.1007/978-3-030-37051-0_66

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-37050-3

  • Online ISBN: 978-3-030-37051-0

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