A GREY WOLF ALGORITHM FOR INDEX OPTIMIZATION IN RELATIONAL DATABASES

Fernando Verástegui, Rony Cueva, Manuel Tupia

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

Optimizing indexes in relational databases is crucial for enhancing information system performance, productivity, and decision-making. Indexes are structures that expedite data retrieval, offering swift access to records. Optimization yields faster data access, reducing query delays and enhancing application responsiveness, crucial in competitive enterprise settings. It also eases server load and resource use, resulting in long-term cost savings. Proper index management preserves database integrity, ensuring accurate, consistent data retrieval. Poor design can lead to locking and performance issues, affecting system reliability. The Grey Wolf Optimization (GWO) algorithm, introduced by Seyedali Mirjalili in 2014, is a metaheuristic inspired by grey wolf social behavior. It aids in solving optimization problems, including data management. This algorithm models the social hierarchy and hunting dynamics of grey wolf packs, including four wolf types: alpha, beta, delta, and omega, representing the pack's dominant individuals. This paper presents a GWO algorithm to solve the optimization problem in the indexing of large relational databases.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 17th IADIS International Conference Information Systems 2024, IS 2024
EditoresMiguel Baptista Nunes, Pedro Isaias, Philip Powell, Luis Rodrigues
EditorialIADIS
Páginas61-68
Número de páginas8
ISBN (versión digital)9789898704566
EstadoPublicada - 2024
Evento17th IADIS International Conference Information Systems 2024, IS 2024 - Porto, Portugal
Duración: 9 mar. 202411 mar. 2024

Serie de la publicación

NombreProceedings of the 17th IADIS International Conference Information Systems 2024, IS 2024

Conferencia

Conferencia17th IADIS International Conference Information Systems 2024, IS 2024
País/TerritorioPortugal
CiudadPorto
Período9/03/2411/03/24

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