Stammdaten

Titel: Towards Graph-based Cloud Cost Modelling and Optimisation
Untertitel:
Kurzfassung:

Cloud computing has become an increasingly popular choice for businesses and individuals due to its flexibility, scalability, and convenience; however, the rising cost of cloud resources has become a significant concern for many. The pay-per-use model used in cloud computing means that costs can accumulate quickly, and the lack of visibility and control can result in unexpected expenses. The cost structure becomes even more complicated when dealing with hybrid or multi-cloud environments. For businesses, the cost of cloud computing can be a significant portion of their IT budget, and any savings can lead to better financial stability and competitiveness. In this respect, it is essential to manage cloud costs effectively. This requires a deep understanding of current resource utilization, forecasting future needs, and optimising resource utilization to control costs. To address this challenge, new tools and techniques are being developed to provide more visibility and control over cloud computing costs. In this respect, this paper explores a graph-based solution for modelling cost elements and cloud resources and potential ways to solve the resulting constraint problem of cost optimisation. We primarily consider utilization, cost, performance, and availability in this context. Such an approach will eventually help organizations 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.

Schlagworte: cloud, cost, optimisation, graph
Publikationstyp: Beitrag in Proceedings (Autorenschaft)
Erscheinungsdatum: 06.2023 (Print)
Erschienen in: COMPSAC '23 Proceedings of the IEEE 47th Annual Computers, Software, and Applications Conference
COMPSAC '23 Proceedings of the IEEE 47th Annual Computers, Software, and Applications Conference
zur Publikation
 ( IEEE Xplore Digital Library; )
Titel der Serie: -
Bandnummer: -
Erstveröffentlichung: Ja
Version: -
Seite: S. 1337 - 1342

Versionen

Keine Version vorhanden
Erscheinungsdatum: 06.2023
ISBN:
  • 979-8-3503-2697-0
ISSN: -
Homepage: https://ieeexplore.ieee.org/document/10197049
Erscheinungsdatum: 02.08.2023
ISBN (e-book): -
eISSN: 0730-3157
DOI: http://dx.doi.org/10.1109/compsac57700.2023.00203
Homepage: https://ieeexplore.ieee.org/document/10197049
Open Access
  • Online verfügbar (nicht Open Access)

Zuordnung

Organisation Adresse
Fakultät für Technische Wissenschaften
 
Institut für Informationstechnologie
Universitaetsstr. 65-67
9020 Klagenfurt am Wörthersee
Österreich
   martina.steinbacher@aau.at
http://itec.aau.at/
zur Organisation
Universitaetsstr. 65-67
AT - 9020  Klagenfurt am Wörthersee

Kategorisierung

Sachgebiete
  • 1020 - Informatik
Forschungscluster Kein Forschungscluster ausgewählt
Peer Reviewed
  • Ja
Publikationsfokus
  • Science to Science (Qualitätsindikator: II)
Klassifikationsraster der zugeordneten Organisationseinheiten:
Arbeitsgruppen
  • Verteilte Systeme

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Beiträge der Publikation

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