Prioritized job scheduling algorithm using parallelization technique in cloud computing

Mhatre, Mallika; Shree, Pragya; Sharma, Sanjay Kumar

doi:10.1109/i2ct.2017.8226195

Cited by 3 publications

(3 citation statements)

References 5 publications

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“…There are several works in the literature about scalability [ 5 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 ]. However, they tend to focus on mechanisms that contribute to infrastructure robustness [ 14 ] since carrying out economic management of resources directly impacts the service’s quality.…”

Section: Related Workmentioning

confidence: 99%

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MoHRiPA—An Architecture for Hybrid Resources Management of Private Cloud Environments

Andreazi

Estrella

Bruschi

et al. 2021

Sensors

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The high demand for data processing in web applications has grown in recent years due to the increased computing infrastructure supply as a service in a cloud computing ecosystem. This ecosystem offers benefits such as broad network access, elasticity, and resource sharing, among others. However, properly exploiting these benefits requires optimized provisioning of computational resources in the target infrastructure. Several studies in the literature improve the quality of this management, which involves enhancing the scalability of the infrastructure, either through cost management policies or strategies aimed at resource scaling. However, few studies adequately explore performance evaluation mechanisms. In this context, we present the MoHRiPA—Management of Hybrid Resources in Private cloud Architecture. MoHRiPA has a modular design encompassing scheduling algorithms, virtualization tools, and monitoring tools. The proposed architecture solution allows assessing the overall system’s performance by using complete factorial planning to identify the general behavior of architecture under high demand of requests. It also evaluates workload behavior, the number of virtualized resources, and provides an elastic resource manager. A composite metric is also proposed and adopted as a criterion for resource scaling. This work presents a performance evaluation by using formal techniques, which analyses the scheduling algorithms of architecture and the experiment bottlenecks analysis, average response time, and latency. In summary, the proposed MoHRiPA mapping resources algorithm (HashRefresh) showed significant improvement results than the analyzed competitor, decreasing about 7% percent in the uniform average compared to ListSheduling (LS).

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Section: Related Workmentioning

confidence: 99%

“…The authors of [ 15 ] propose a method of scheduling by prioritizing tasks in parallel. This approach uses the concept of master/slave as a technique.…”

Section: Related Workmentioning

confidence: 99%

MoHRiPA—An Architecture for Hybrid Resources Management of Private Cloud Environments

Andreazi

Estrella

Bruschi

et al. 2021

Sensors

View full text Add to dashboard Cite

show abstract

“…Os autores (Mhatre;Shree;Sharma, 2017) propõem um método de escalonamento por priorização de tarefas de forma paralela, utilizando o conceito de mestre/escravo. O algoritmo proposto melhora o desempenho e utilização de recursos, além de reduzir o tempo de execução durante o balanceamento de carga.…”

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Modelagem e desenvolvimento de uma arquitetura distribuída para o gerenciamento de recursos híbridos em nuvem privada

Andreazi¹

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A novel multiclass priority algorithm for task scheduling in cloud computing

2021

View full text Add to dashboard Cite

Prioritized job scheduling algorithm using parallelization technique in cloud computing

Cited by 3 publications

References 5 publications

MoHRiPA—An Architecture for Hybrid Resources Management of Private Cloud Environments

MoHRiPA—An Architecture for Hybrid Resources Management of Private Cloud Environments

Modelagem e desenvolvimento de uma arquitetura distribuída para o gerenciamento de recursos híbridos em nuvem privada

A novel multiclass priority algorithm for task scheduling in cloud computing

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