2024-03-29T06:56:39Zhttps://gredos.usal.es/oai/requestoai:gredos.usal.es:10366/1392292022-02-07T16:12:25Zcom_10366_138329com_10366_122682com_10366_4666com_10366_3823col_10366_139093
Evolutionary Algorithms for Query Op-timization in Distributed Database Sys-tems: A review
Ali, Zulfiqar
Kiran, Hafiza Maria
Shahzad, Waseem
Computación
Informótica
Computing
Information Technology
Evolutionary Algorithms are bio-inspired optimization problem-solving approaches that exploit principles of biological evolution. , such as natural selection and genetic inheritance. This review paper provides the application of evolutionary and swarms intelligence based query optimization strategies in Distributed Database Systems. The query optimization in a distributed environment is challenging task and hard problem. However, Evolutionary approaches are promising for the optimization problems. The problem of query optimization in a distributed database environment is one of the complex problems. There are several techniques which exist and are being used for query optimization in a distributed database. The intention of this research is to focus on how bio-inspired computational algorithms are used in a distributed database environment for query optimization. This paper provides working of bio-inspired computational algorithms in distributed database query optimization which includes genetic algorithms, ant colony algorithm, particle swarm optimization and Memetic Algorithms.
2019-02-05T12:03:34Z
2019-02-05T12:03:34Z
2018-09-21
info:eu-repo/semantics/article
ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 7 (2018)
2255-2863
http://hdl.handle.net/10366/139229
eng
Attribution-NonCommercial-NoDerivs 3.0 Unported
https://creativecommons.org/licenses/by-nc-nd/3.0/
info:eu-repo/semantics/openAccess
application/pdf
Ediciones Universidad de Salamanca (España)