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A Virtual Machine Placement Policy via Biogeography-based Optimization in the Cloud

Published: 05 January 2018 Publication History

Abstract

With the rapid development and popularization of cloud computing, cloud datacenters urgently need some highly efficient policies to improve their resource utilizations (e.g., power and physical machine resources). Although there are numerous virtual machine placement (VMP) policies which are designed to identify some most suitable physical machines for virtual machine requests, they are still not enough to improve their resource utilizations. Therefore, in this paper, we first exploit original biogeography-based optimization (BBO) algorithm to solve the VMP problem. In our BBO-based VMP policy, we first map the VMP problem to an ecosystem model, and then we redefine operators of the original BBO algorithm according to the ecosystem model. Finally, we perform a thorough performance evaluation of our BBO-based VMP policy in terms of the robustness, performance, and scalability. Experimental results show that our proposed policy outperforms other related policies.

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  • (2018)Friendly Online Technology Development Cloud Service for Bahraini Students based on E-Advisor2018 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)10.1109/3ICT.2018.8855783(1-7)Online publication date: Nov-2018
  • (2018)How to Improve the Resource Utilization in Cloud Data Center?2018 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)10.1109/3ICT.2018.8855740(1-6)Online publication date: Nov-2018

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cover image ACM Other conferences
IMCOM '18: Proceedings of the 12th International Conference on Ubiquitous Information Management and Communication
January 2018
628 pages
ISBN:9781450363853
DOI:10.1145/3164541
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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  • SKKU: SUNGKYUNKWAN UNIVERSITY

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 January 2018

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Author Tags

  1. Cloud datacenter
  2. biogeography-based optimization
  3. ecosystem model
  4. power consumption
  5. resource wastage
  6. virtual machine placement

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  • Refereed limited

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IMCOM '18

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IMCOM '18 Paper Acceptance Rate 100 of 255 submissions, 39%;
Overall Acceptance Rate 213 of 621 submissions, 34%

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View all
  • (2018)Friendly Online Technology Development Cloud Service for Bahraini Students based on E-Advisor2018 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)10.1109/3ICT.2018.8855783(1-7)Online publication date: Nov-2018
  • (2018)How to Improve the Resource Utilization in Cloud Data Center?2018 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)10.1109/3ICT.2018.8855740(1-6)Online publication date: Nov-2018

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