Memory Management Productivity in Big data Multimedia using Fireworks Algorithm

dc.creatorN. Hasoon, Jamal
dc.creatorHassan, Rehab
dc.date2019-08-03
dc.date.accessioned2022-11-05T02:30:40Z
dc.date.available2022-11-05T02:30:40Z
dc.identifierhttps://produccioncientificaluz.org/index.php/opcion/article/view/31281
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5141541
dc.descriptionThe using of Big Data applications increased exponentially in the last few years. There are some knowledge extracted from huge volumes of data has been concerned by several enterprise. The working in Big Data faced chal- lenges and should do hard. As a result, various types of distributions and tech- nologies have been developed. This paper present a method for memory map- ping of image depend on some aggregation function and optimization these function using Fireworks algorithm to reduce the size of memory required in searching process. Image features extraction used in aggregation function and used later for optimization. Three types of feature extraction used image descriptors techniques. The proposed method provides abstract domain that replaced total data domain and the performance increase the system through- put and reduce cost.es-ES
dc.formatapplication/pdf
dc.languagespa
dc.publisherUniversidad del Zuliaes-ES
dc.relationhttps://produccioncientificaluz.org/index.php/opcion/article/view/31281/32332
dc.rightsDerechos de autor 2020 Opciónes-ES
dc.sourceOpción; Vol. 35 (2019): Edición Especial Nro. 20; 841-858es-ES
dc.source2477-9385
dc.source1012-1587
dc.subjectBig dataes-ES
dc.subjectCloud Computinges-ES
dc.subjectFirework algorithmes-ES
dc.subjectfeature extractiones-ES
dc.titleMemory Management Productivity in Big data Multimedia using Fireworks Algorithmes-ES
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typeArtículo revisado por pareses-ES


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