Geo-distributed multi-cloud data centre storage tiering and selection with zero-suppressed binary decision diagrams
The exponential growth of data in recent years prompted cloud providers to introduce diverse geo-distributed storage solutions for various needs. The vast amount of storage options, however, presents organisations with a challenge in determining the ideal data placement configuration. The study introduces a novel optimisation algorithm utilising the zero-suppressed binary decision diagram to select the optimal data centre, storage tiers, and cloud provider. The algorithm takes on a holistic approach that considers cost, latency, and high availability, applicable to both geo-distributed on-premise environments and public cloud providers. Furthermore, the proposed methodology leverages the recursive structure of the zero-suppressed binary decision diagram, allowing for the enumeration and ranking of all valid configurations based on total cost. Overall, the study offers flexibility for organisations in addressing specific priorities for cloud storage solutions by providing alternative near-optimal configurations.
Authors
- Kazushi Ikeda (ORCID: https://orcid.org/0009-0000-9563-760X)
- William Emmanuel S. Yu
- Miguel de Cervantes Saavedra
- Renzo Roel P. Tan (ORCID: https://orcid.org/0000-0002-0449-8999)
- Brian Godwin Lim (ORCID: https://orcid.org/0000-0003-1168-4295)
Institutions
- Ateneo de Manila University (PH)
- Nara Institute of Science and Technology (JP)
Publication Details
- Journal
- International Journal of Cloud Computing
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1504/ijcc.2025.147441
- Primary Topic
- Cloud Computing and Resource Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00