SLA-WS: SLA-based workload scheduling technique in multi-cloud platform

Nelli, Arundhati; Jogdand, Rashmi M.

doi:10.1007/s12652-021-03666-z

Cited by 6 publications

(2 citation statements)

References 38 publications

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“…In this work the performance achieved using MMWS with other workload scheduling technique namely workload-scheduling adaptive-dragonfly algorithm (WS-ADA) [15], reliability multi cloudscheduler (REL-MC) [25] and service-level agreement-based workload-scheduling (SLA-WS) [26]. The SLA-violation rate and resource utilization are metrics used for validating workload scheduling model.…”

Section: Resultsmentioning

confidence: 99%

A Min-Max Workload Scheduling Technique Using Soft-Computing Approach in Multi-Cloud Platform

2023

IJIES

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Maximizing resource utilization by minimizing service level agreement (SLA) violation is considered to be extremely difficult process for scheduling of realtime workload on multi-cloud platform. In particular the proposed work considers both energy and performance as SLA minimization constraint for scheduling of workload in multi-cloud platform. The scheduling optimization of SLA minimization is done as single objective function using dragonfly soft computing approach. Further, the scheduling optimization of min-max is done as multi-objective for maximizing resource utilization with minimal SLA violation using dragonfly soft computing approach. The results show that the min-max workload scheduling (MMWS) has improved the resource utilization by 16.02%, 7.92%, and 2.52% respectively for montage workload and 9.92%, 4.07%, and 1.11% for SIPHT workload in comparison to the existing workload-scheduling adaptive-dragonfly algorithm (WS-ADA), reliability multi cloud-scheduler (REL-MC) and service-level agreement-based workload-scheduling (SLA-WS) method respectively. The results show that the MMWS has reduced the SLA violation rate by 81.92%, 69.23%, and 30.11% respectively for montage workload and 84.57%, 61.32%, and 12.62% for SIPHT workload in comparison to the existing WS-ADA, REL-MC and SLA-WS methods respectively. Hence, from the experiment outcomes it is shown that the proposed MMWS technique reduces SLA violation with improved resource efficiency in comparison with WS-ADA, REL-MC and SLA-WS.

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Section: Resultsmentioning

confidence: 99%

A Min-Max Workload Scheduling Technique Using Soft-Computing Approach in Multi-Cloud Platform

2023

IJIES

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“…In this model, the virtual machines can migrate among the physical machine, and the required resources are shared among the virtual machines. The energy consumed by the physical machine 𝑗𝑗 𝑚𝑚 is evaluated using the given Equation ( 1) [17]…”

Section: System Model For Workload Scheduling Under Multi-cloud Platformmentioning

confidence: 99%

Dragonfly soft-computing approach for workload scheduling resource utilization maximization using multi-cloud platform

Nelli¹,

Jogdand²

2023

IJITS JOURNAL

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The execution of the real-time workload in the multi-cloud platform with the Service Level Agreement (SLA) requirements is a challenging task. Existing workload scheduling models have addressed issues related to minimizing execution time, cost, and energy with application reliability prerequisite. However, these models are not efficient in maximizing resource utilization under a multi-cloud platform. In addressing resource utilization issues, this paper presents a Workload Scheduling Resource Utilization Maximization (WS-RUM) technique for the multi-cloud platform. The WS-RUM technique leverages a multi-objective such as energy, processing efficiency, and fault-tolerant offloading mechanism employing a dragonfly soft computing algorithm. The WS-RUM improves resource utilization by minimizing both energy and processing time for real-time workload execution in comparison with existing workload execution.

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A Review on FoG Computing in 5G Wireless Technologies: Research Challenges, Issues and Solutions

Premalatha,

Prakasam

2024

Wireless Pers Commun

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SLA-WS: SLA-based workload scheduling technique in multi-cloud platform

Cited by 6 publications

References 38 publications

A Min-Max Workload Scheduling Technique Using Soft-Computing Approach in Multi-Cloud Platform

A Min-Max Workload Scheduling Technique Using Soft-Computing Approach in Multi-Cloud Platform

Dragonfly soft-computing approach for workload scheduling resource utilization maximization using multi-cloud platform

A Review on FoG Computing in 5G Wireless Technologies: Research Challenges, Issues and Solutions

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