Keywords
Distributed Storage System, Performance Metric Optimization, Cloud Computing, Data Center Digital Twin, Erasure Coding
Disciplines
Computational Engineering | Electrical and Computer Engineering | Physical Sciences and Mathematics
Abstract
With the exponential data growth, there is a crucial need for highly available, scalable, reliable, and cost-effective Distributed Storage Systems (DSSs). To ensure such efficient and fault tolerant systems, replication and erasure coding techniques are typically used in traditional DSSs. However, these systems are prone to failure and require different failure prevention and recovery algorithms. Failure recovery of DSS and data reconstruction techniques take into consideration different performance metrics optimization in the recovery process. In this paper, DSS performance metrics are introduced. Several recent papers related to adopting erasure coding in DSSs are surveyed together with highlighting related performance metrics introduced in the context of these papers. Next, we present recent literature where Digital Twins (DTs) are involved in monitoring DSSs and assisting the data center managers in intelligent decision-making. Finally, important open issues are identified to inspire future studies for fully efficient DSSs.
Author ORCID Identifier
May Itani https://orcid.org/0000-0002-0738-0822
Layal Abu Daher https://orcid.org/0000-0002-4041-3243
Ahmad Hammoud https://orcid.org/0009-0003-5049-044X
Recommended Citation
Itani, May; Abu Daher, Layal; and Hammoud, Ahmad
(2023)
"TOWARDS DIGITAL TWINS FOR OPTIMIZING METRICS IN DISTRIBUTED STORAGE SYSTEMS - A REVIEW,"
BAU Journal - Science and Technology: Vol. 5:
Iss.
1, Article 9.
DOI: https://doi.org/10.54729/2959-331X.1118
ISSN
2959-331X
Included in
Computational Engineering Commons, Electrical and Computer Engineering Commons, Physical Sciences and Mathematics Commons