OPTIMIZING UNIVERSITY DATABASE MANAGEMENT THROUGH DYNAMIC FRAGMENTATION AND REALLOCATION: A CASE STUDY
Dynamic allocation and reallocation of data fragments in distributed databases, particularly in the context of NoSQL databases, are essential for optimizing performance and resource utilization. This paper explores the application of dynamic fragment allocation and reallocation algorithms in a di...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Academica Brancusi
2024-05-01
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| Series: | Fiabilitate şi Durabilitate |
| Subjects: | |
| Online Access: | https://www.utgjiu.ro/rev_mec/mecanica/pdf/2024-01/41_Adrian%20RUNCEANU,%20Mihaela-Ana%20RUNCEANU%20%20-%20OPTIMIZING%20UNIVERSITY%20DATABASE%20MANAGEMENT%20THROUGH%20DYNAMIC%20FRAGMENTATION%20AND%20REALLOCATION%20A%20CASE%20STUDY.pdf |
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| Summary: | Dynamic allocation and reallocation of data fragments in distributed databases,
particularly in the context of NoSQL databases, are essential for optimizing performance and
resource utilization. This paper explores the application of dynamic fragment allocation and
reallocation algorithms in a distributed database environment through a case study focused on
university data management. By leveraging a well-defined database schema custom-made for
university information management, the study highlights the integration of dynamic allocation
strategies to efficiently manage faculties, departments, students, teachers, courses, and timetables.
Through this case study, the paper demonstrates the significance of dynamic allocation and
reallocation algorithms in enhancing data processing efficiency and optimizing resource
utilization within distributed database systems.
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| ISSN: | 1844-640X 2344-3669 |