Cloud Host Selection using Iterative Particle-Swarm Optimization for Dynamic Container Consolidation

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G Ravikumar
Zunaira Begum
A. Shiva Kumar
V. Kiranmai
M. Bhavsingh
O. Kiran Kumar

Abstract

A significant portion of the energy consumption in cloud data centres can be attributed to the inefficient utilization of available resources due to the lack of dynamic resource allocation techniques such as virtual machine migration and workload consolidation strategies to better optimize the utilization of resources. We present a new method for optimizing cloud data centre management by combining virtual machine migration with workload consolidation. Our proposed Energy Efficient Particle Swarm Optimization (EE-PSO) algorithm to improve resource utilization and reduce energy consumption. We carried out experimental evaluations with the Container CloudSim toolkit to demonstrate the effectiveness of the proposed EE-PSO algorithm in terms of energy consumption, quality of service guarantees, the number of newly created VMs, and container migrations.

Article Details

How to Cite
Ravikumar, G. ., Begum, Z. ., Kumar, A. S. ., Kiranmai, V., Bhavsingh, M., & Kumar, O. K. . (2022). Cloud Host Selection using Iterative Particle-Swarm Optimization for Dynamic Container Consolidation. International Journal on Recent and Innovation Trends in Computing and Communication, 10(1s), 247–253. https://doi.org/10.17762/ijritcc.v10i1s.5846
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