Cost modelling and optimisation for cloud: a graph-based approach

Abstract Cloud computing has become popular among individuals and enterprises due to its convenience, scalability, and flexibility. However, a major concern for many cloud service users is the rising cost of cloud resources. Since cloud computing uses a pay-per-use model, costs can add up quickly, and unexpected expenses can arise from a lack of visibility and control. The cost structure gets even more complicated when working with multi-cloud or hybrid environments. Businesses may spend much of their IT budget on cloud computing, and any savings can improve their competitiveness and financial stability. Hence, an efficient cloud cost management is crucial. To overcome this difficulty, new approaches and tools are being developed to provide greater oversight and command over cloud a graph-based approach for modelling cost elements and cloud resources and a potential way to solve the resulting constraint problem of cost optimisation. In this context, we primarily consider utilisation, cost, performance, and availability. The proposed approach is evaluated on three different user scenarios, and results indicate that it could be effective in cost modelling, cost optimisation, and scalability. This approach will eventually help organisations make informed decisions about cloud resource placement and manage the costs of software applications and data workflows deployed in single, hybrid, or multi-cloud environments.

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Publication Details

Journal
Journal of Cloud Computing Advances Systems and Applications
Published
2024-09-30
DOI
https://doi.org/10.1186/s13677-024-00709-6
Citations
11
Primary Topic
Cloud Computing and Resource Management
Type
article
Field-Weighted Citation Impact
8.57

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article

Cost modelling and optimisation for cloud: a graph-based approach

Akif Quddus Khan, Ahmet Soylu, Dumitru Roman, Radu Prodan et al.
11 citations
Journal of Cloud Computing Advances Systems and Applications
Cloud Computing and Resource Management
8.57
article

Cost modelling and optimisation for cloud: a graph-based approach

Akif Quddus Khan, Ahmet Soylu, Dumitru Roman, Radu Prodan, Mihhail Matskin, Christoph Bußler
article en
11 citations

Abstract

Abstract Cloud computing has become popular among individuals and enterprises due to its convenience, scalability, and flexibility. However, a major concern for many cloud service users is the rising cost of cloud resources. Since cloud computing uses a pay-per-use model, costs can add up quickly, and unexpected expenses can arise from a lack of visibility and control. The cost structure gets even more complicated when working with multi-cloud or hybrid environments. Businesses may spend much of their IT budget on cloud computing, and any savings can improve their competitiveness and financial stability. Hence, an efficient cloud cost management is crucial. To overcome this difficulty, new approaches and tools are being developed to provide greater oversight and command over cloud a graph-based approach for modelling cost elements and cloud resources and a potential way to solve the resulting constraint problem of cost optimisation. In this context, we primarily consider utilisation, cost, performance, and availability. The proposed approach is evaluated on three different user scenarios, and results indicate that it could be effective in cost modelling, cost optimisation, and scalability. This approach will eventually help organisations make informed decisions about cloud resource placement and manage the costs of software applications and data workflows deployed in single, hybrid, or multi-cloud environments.

Journal of Cloud Computing Advances Systems and ApplicationsVol. 13(1)
SINTEF (NO), OsloMet – Oslo Metropolitan University (NO), Norwegian University of Science and Technology (NO), Robert Bosch (United States) (US), University of Klagenfurt (AT), KTH Royal Institute of Technology (SE)
Norges Teknisk-Naturvitenskapelige Universitet, St. Olavs Hospital Universitetssykehuset i Trondheim, Horizon 2020 Framework Programme
Decent work and economic growth
Openalex Percentile: Top 2%
Cloud Computing and Resource Management
8.57
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