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Description du livre Soft Cover. Etat : new. This item is printed on demand. N° de réf. du vendeur 9783030103330
Description du livre Etat : New. N° de réf. du vendeur ABLIING23Mar3113020006496
Description du livre Etat : New. PRINT ON DEMAND Book; New; Fast Shipping from the UK. No. book. N° de réf. du vendeur ria9783030103330_lsuk
Description du livre Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents an improved design for service provisioning and allocation models that are validated through running genome sequence assembly tasks in a hybrid cloud environment. It proposes approaches for addressing scheduling and performance issues in big data analytics and showcases new algorithms for hybrid cloud scheduling. Scientific sectors such as bioinformatics, astronomy, high-energy physics, and Earth science are generating a tremendous flow of data, commonly known as big data. In the context of growing demand for big data analytics, cloud computing offers an ideal platform for processing big data tasks due to its flexible scalability and adaptability. However, there are numerous problems associated with the current service provisioning and allocation models, such as inefficient scheduling algorithms, overloaded memory overheads, excessive node delays and improper error handling of tasks, all of which need to be addressed to enhance the performance of big data analytics. 116 pp. Englisch. N° de réf. du vendeur 9783030103330
Description du livre Paperback. Etat : Brand New. reprint edition. 116 pages. 9.25x6.10x0.43 inches. In Stock. N° de réf. du vendeur x-3030103331
Description du livre Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents an improved design for service provisioning and allocation models that are validated through running genome sequence assembly tasks in a hybrid cloud environment. It proposes approaches for addressing scheduling and performance issues in big data analytics and showcases new algorithms for hybrid cloud scheduling. Scientific sectors such as bioinformatics, astronomy, high-energy physics, and Earth science are generating a tremendous flow of data, commonly known as big data. In the context of growing demand for big data analytics, cloud computing offers an ideal platform for processing big data tasks due to its flexible scalability and adaptability. However, there are numerous problems associated with the current service provisioning and allocation models, such as inefficient scheduling algorithms, overloaded memory overheads, excessive node delays and improper error handling of tasks, all of which need to be addressed to enhance the performance of big data analytics. N° de réf. du vendeur 9783030103330
Description du livre Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents an improved design for service provisioning and allocation models in a hybrid cloud environmentProposes approaches for addressing scheduling and performance issues in big data analytics Showcases new algorithms for hybrid cl. N° de réf. du vendeur 273276641
Description du livre N° de réf. du vendeur STOCK12030294
Description du livre PF. Etat : New. N° de réf. du vendeur 6666-IUK-9783030103330
Description du livre Paperback. Etat : New. New. book. N° de réf. du vendeur D8F0-0-M-3030103331-6