research-article

A Load Balancing Algorithm for 5G Vehicular Cloud Computing Systems

Authors:

Emmanouil Skondras,

Angelos Michalas,

Dimitrios D. VergadosAuthors Info & Claims

PCI '20: Proceedings of the 24th Pan-Hellenic Conference on Informatics

Pages 241 - 244

https://doi.org/10.1145/3437120.3437316

Published: 04 March 2021 Publication History

Abstract

5G Vehicular Cloud Computing (5G-VCC) infrastructures are evolving rapidly. In a 5G-VCC system, Cloud resources should be efficiently distributed to provide satisfactory Quality of Service (QoS) for modern services with increased requirements. Furthermore, the workload should be fairly distributed to the available Virtual Machines (VMs). This paper proposes an algorithm for performing load balancing in Cloud infrastructures that exist in 5G-VCC systems. The algorithm is called Modified Ant Colony Optimization (MACO), as its functionality is influenced by the natural behaviour of ants. Specifically, the MACO algorithm assigns a pheromone (weight) value to each VM. Subsequently, for each service request the VM with the highest pheromone is selected in a way similar to the one that ants apply to select optimal routes. The selection of each VM results in the decrement its pheromone value, considering the workload of the assigned service. Evaluation results show that the proposed algorithm outperforms existing load balancing algorithms in terms of the processing time required for serving the user requests.

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Digital Library

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Cited By

Infantia HAnbuananth CKalarani S(2023)An effective process of VM migration with hybrid heuristic-assisted encryption technique for secured data transmission in cloud environmentIntelligent Decision Technologies10.3233/IDT-23026417:4(983-1006)Online publication date: 20-Nov-2023
https://doi.org/10.3233/IDT-230264
Gupta ABhadauria H(2023)Workload prediction for SLA performance in cloud environment: ESANN approachIntelligent Decision Technologies10.3233/IDT-23010117:4(1085-1100)Online publication date: 20-Nov-2023
https://doi.org/10.3233/IDT-230101

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cover image ACM Other conferences

PCI '20: Proceedings of the 24th Pan-Hellenic Conference on Informatics

November 2020

433 pages

ISBN:9781450388979

DOI:10.1145/3437120

Copyright © 2020 ACM.

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: 04 March 2021

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PCI 2020

PCI 2020: 24th Pan-Hellenic Conference on Informatics

November 20 - 22, 2020

Athens, Greece

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Cited By

Infantia HAnbuananth CKalarani S(2023)An effective process of VM migration with hybrid heuristic-assisted encryption technique for secured data transmission in cloud environmentIntelligent Decision Technologies10.3233/IDT-23026417:4(983-1006)Online publication date: 20-Nov-2023
https://doi.org/10.3233/IDT-230264
Gupta ABhadauria H(2023)Workload prediction for SLA performance in cloud environment: ESANN approachIntelligent Decision Technologies10.3233/IDT-23010117:4(1085-1100)Online publication date: 20-Nov-2023
https://doi.org/10.3233/IDT-230101

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