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A load balancing strategy based on data correlation in cloud computing

Published: 06 December 2016 Publication History

Abstract

According to the problems of the correlation of the data disposed by virtual machines and the reduce of resource utilization caused by migration of a single virtual machine in cloud computing, this paper proposes a load balancing strategy based on data correlation in cloud computing. This strategy finds out the migration unit based on the correlation between the data and the virtual machines used to deal with the same data, and construct the load-intensive data set to carry on the overall migration. The experimental results show that the load balancing strategy can reduce the communication overhead and improve the utilization of resources in a certain extent.

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  • (2024)Agnostic Energy Consumption Models for Heterogeneous GPUs in Cloud ComputingApplied Sciences10.3390/app1406238514:6(2385)Online publication date: 12-Mar-2024
  • (2023)Enhancing Load Balancing in Cloud Computing Through Deadlock PredictionIndustrial Networks and Intelligent Systems10.1007/978-3-031-47359-3_19(257-274)Online publication date: 31-Oct-2023
  • (2022)Performance analysis and system optimization of an energy-saving mechanism in cloud computing with correlated trafficJournal of Industrial and Management Optimization10.3934/jimo.202110618:5(3133)Online publication date: 2022
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cover image ACM Other conferences
UCC '16: Proceedings of the 9th International Conference on Utility and Cloud Computing
December 2016
549 pages
ISBN:9781450346160
DOI:10.1145/2996890
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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 December 2016

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Author Tags

  1. cloud computing
  2. data correlation
  3. load balancing
  4. virtual machine migration

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UCC '16

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Overall Acceptance Rate 38 of 125 submissions, 30%

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Cited By

View all
  • (2024)Agnostic Energy Consumption Models for Heterogeneous GPUs in Cloud ComputingApplied Sciences10.3390/app1406238514:6(2385)Online publication date: 12-Mar-2024
  • (2023)Enhancing Load Balancing in Cloud Computing Through Deadlock PredictionIndustrial Networks and Intelligent Systems10.1007/978-3-031-47359-3_19(257-274)Online publication date: 31-Oct-2023
  • (2022)Performance analysis and system optimization of an energy-saving mechanism in cloud computing with correlated trafficJournal of Industrial and Management Optimization10.3934/jimo.202110618:5(3133)Online publication date: 2022
  • (2022)Genetic Approach based Optimized Load Balancing in Cloud Computing: A Performance Perspective2022 9th International Conference on Computing for Sustainable Global Development (INDIACom)10.23919/INDIACom54597.2022.9763200(814-819)Online publication date: 23-Mar-2022
  • (2022)A Proposed Load Balancer Using Naïve Bayes to Enhance Response Time on Cloud Computing2022 24th International Conference on Advanced Communication Technology (ICACT)10.23919/ICACT53585.2022.9728946(82-90)Online publication date: 13-Feb-2022
  • (2022)A Performed Optimized Load Balancing Genetic Approach Technique in Cloud EnvironmentRecent Trends in Communication and Intelligent Systems10.1007/978-981-19-1324-2_29(269-279)Online publication date: 25-May-2022
  • (2022)Adaptive Bat Optimization Algorithm for Efficient Load Balancing in Cloud Computing EnvironmentAdvances in Computational Intelligence and Communication Technology10.1007/978-981-16-9756-2_35(357-369)Online publication date: 6-Apr-2022
  • (2021)An Improved Q-Learning-Based Scheduling Strategy with Load Balancing for Infrastructure-Based Cloud ServicesArabian Journal for Science and Engineering10.1007/s13369-021-06279-y47:8(9547-9555)Online publication date: 9-Nov-2021
  • (2020)Cloud Load Balancing Using Optimization TechniquesMobile Radio Communications and 5G Networks10.1007/978-981-15-7130-5_60(735-744)Online publication date: 29-Sep-2020
  • (2019)Load balancing in cloud computing using water flow-like algorithmProceedings of the Second International Conference on Data Science, E-Learning and Information Systems10.1145/3368691.3368720(1-6)Online publication date: 2-Dec-2019
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