Dynamic Resource Allocation Using Improved Firefly Optimization Algorithm in Cloud Environment

Abedi, Simin; Ghobaei‐Arani, Mostafa; Khorami, Ehsan; Mojarad, Musa

doi:10.1080/08839514.2022.2055394

Cited by 17 publications

(4 citation statements)

References 40 publications

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“…The third stage involves updating the population using relevant strategies by adopting recombination and mutation, contributing to the evolution of potential solutions. Finally, optimal or highly probable solutions are selectively retained at each iteration, refining the population of solutions until the termination condition is met [202]- [204]. This iterative process helps in determining the most effective mapping between requested VMs and available servers.…”

Section: Optimization Algorithm-based Managementmentioning

confidence: 99%

A Comprehensive Survey on Sustainable Resource Management in Cloud Computing Environments

Saxena,

Singh

2024

Preprint

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Section: Optimization Algorithm-based Managementmentioning

confidence: 99%

A Comprehensive Survey on Sustainable Resource Management in Cloud Computing Environments

Saxena,

Singh

2024

Preprint

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“…16. The drawback of the study was that some objectives still need to achieve using better optimization [38]. Khan et al (2022) presented a hybrid cuckoo search and particle swarm optimization (CU-PSO) approach for effective VM migration.…”

Section: Literature Surveymentioning

confidence: 99%

Algorithmic Approach to Virtual Machine Migration in Cloud Computing with Updated SESA Algorithm

Kaur

Kumar

Gupta

et al. 2023

Sensors

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Cloud computing plays an important role in every IT sector. Many tech giants such as Google, Microsoft, and Facebook as deploying their data centres around the world to provide computation and storage services. The customers either submit their job directly or they take the help of the brokers for the submission of the jobs to the cloud centres. The preliminary aim is to reduce the overall power consumption which was ignored in the early days of cloud development. This was due to the performance expectations from cloud servers as they were supposed to provide all the services through their services layers IaaS, PaaS, and SaaS. As time passed and researchers came up with new terminologies and algorithmic architecture for the reduction of power consumption and sustainability, other algorithmic anarchies were also introduced, such as statistical oriented learning and bioinspired algorithms. In this paper, an indepth focus has been done on multiple approaches for migration among virtual machines and find out various issues among existing approaches. The proposed work utilizes elastic scheduling inspired by the smart elastic scheduling algorithm (SESA) to develop a more energy-efficient VM allocation and migration algorithm. The proposed work uses cosine similarity and bandwidth utilization as additional utilities to improve the current performance in terms of QoS. The proposed work is evaluated for overall power consumption and service level agreement violation (SLA-V) and is compared with related state of art techniques. A proposed algorithm is also presented in order to solve problems found during the survey.

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“…The experimental analysis observed that the task migration from the containers disrupted the communication flow between the containers of similar hosts, which was a limitation of this work. Abedi et al [37] developed an improved firefly algorithm (IFA) based on LB optimization to solve DRA problem, hence this development was called IFA-DRA. Adil et al [38] proposed a novel hybrid approach called content-aware machine learning based LB schedular (CA-MLBS).…”

Section: Sanaj and Prathapmentioning

confidence: 99%

An efficient load balancing in cloud computing using hybrid Harris hawks optimization and cuckoo search algorithm

2023

IJATEE

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One of the most common services used by people worldwide is cloud computing. Users get immediate access to a variety of computer components or services, including servers, apps, storage, and network. Task planning is crucial in the cloud environment. Applications for users, or tasks at a particular time, are premeditated for specific properties.The concentration is mostly on minimizing the spectrum of construction and resource utilization.

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Dynamic Resource Allocation Using Improved Firefly Optimization Algorithm in Cloud Environment

Cited by 17 publications

References 40 publications

A Comprehensive Survey on Sustainable Resource Management in Cloud Computing Environments

A Comprehensive Survey on Sustainable Resource Management in Cloud Computing Environments

Algorithmic Approach to Virtual Machine Migration in Cloud Computing with Updated SESA Algorithm

An efficient load balancing in cloud computing using hybrid Harris hawks optimization and cuckoo search algorithm

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