Distributed Storage System, Performance Metric Optimization, Cloud Computing, Data Center Digital Twin, Erasure Coding


Computational Engineering | Electrical and Computer Engineering | Physical Sciences and Mathematics


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.





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