Home > Research > Publications & Outputs > Cost-aware orchestration of applications over h...


Text available via DOI:

View graph of relations

Cost-aware orchestration of applications over heterogeneous clouds

Research output: Contribution to journalJournal article

  • K. Alexander
  • M. Hanif
  • C. Lee
  • E. Kim
  • S. Helal
Article numbere0228086
<mark>Journal publication date</mark>18/02/2020
<mark>Journal</mark>PLoS ONE
Issue number2
Number of pages21
Publication StatusPublished
<mark>Original language</mark>English


The orchestration of applications and their components over heterogeneous clouds is recognized as being critical in solving the problem of vendor lock-in with regards to distributed and cloud computing. There have been recent strides made in the area of cloud application orchestration with emergence of the TOSCA standard being a definitive one. Although orchestration by itself provides a considerable amount of benefit to consumers of cloud computing services, it remains impractical without a compelling reason to ensure its utilization by cloud computing consumers. If there is no measurable benefit in using orchestration, then it is likely that clients may opt out of using it altogether. In this paper, we present an approach to cloud orchestration that aims to combine an orchestration model with a cost and policy model in order to allow for cost-aware application orchestration across heterogeneous clouds. Our approach takes into consideration the operating cost of the application on each provider, while performing a forward projection of the operating cost over a period of time to ensure that cost constraints remain unviolated. This allows us to leverage the existing state of the art with regards to orchestration and model-driven approaches as well as tie it to the operations of cloud clients in order to improve utility. Through this study, we were able to show that our approach was capable of providing not only scaling features but also orchestration features of application components distributed across heterogeneous cloud platforms.