cloud computing theory practice (74 Ergebnisse)

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Zustand: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.

paperback. Zustand: New. 3rd Edition. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

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Hardcover. Zustand: New. Language:Chinese.HardCover.Pub Date:2024-03 Pages:294 Publisher:Science Press:This book focuses on the technological frontier of ecological big data platform based on remote sensing cloud computing. and systematically expounds on it from three aspects: theory. method. and practice. First. it introduces the background. basic concepts. and principles of ecological big data platform based on remote sensing cloud computing; secondly. it introduces the data. methods. and key technologies of ecolog.

paperback. Zustand: New. Paperback. Pub Date: 2016-12-01 Pages: 284 Language: Chinese Publisher: electronic industry press This book introduces the basic theory of cloud computing and related practice. emphasize the equal emphasis on theory and practice.Main content includes: the basic theory of cloud computing technology. and other computing the difference between generic and contact. as well as the representative of the cloud computing platform system;Virtualization technology.

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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Maintaining accuracy in load balancing using metaheuristics poses challenges despite recent hybrid approaches. Optimized metaheuristic methods are employed to balance loads in the cloud efficiently. Multi-objective Quality of Service (QoS) metrics like reduced SLA violations, makespan, high throughput, and low energy consumption are crucial. Cloud applications, being computation-intensive, demand effective load balancing to prevent poor solutions due to exponential memory growth.To enhance load balancing in cloud computing, a new hybrid model is proposed, performing file classification using Filetype formatting. Three algorithms-Ant Colony Optimization using Filetype Formatting (ACOFTF), Data Format Classification using Support Vector Machine (DFC-SVM), and Datatype Formatting DFTF/DTF-are developed.Overall, the proposed hybrid metaheuristic approaches offer promising solutions for enhancing load balancing in cloud computing environments.