A Review of Data Placement and Replication Strategies Based on Machine Learning

The global increase in data volumes has brought forth the need for scalable distributed systems that can provide satisfactory quality of service. Data placement and replication are well known techniques that provide increased performance, improved fault tolerance and higher availability. These techn...

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Veröffentlicht in:	Proceedings - International Conference on Parallel and Distributed Systems S. 278 - 285
Hauptverfasser:	Najjar, Amir, Mokadem, Riad, Pierson, Jean-Marc
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 10.10.2024
Schlagworte:	Costs Data Placement Data Replication Distributed databases Distributed Systems Fault tolerance Fault tolerant systems Machine Learning Quality of service Reinforcement learning Taxonomy Time factors Tuning Unsupervised learning
ISSN:	2690-5965
Online-Zugang:	Volltext
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