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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Vydané v:	Proceedings - International Conference on Parallel and Distributed Systems s. 278 - 285
Hlavní autori:	Najjar, Amir, Mokadem, Riad, Pierson, Jean-Marc
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 10.10.2024
Predmet:	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
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