Description: Optimized Cloud Based Scheduling, Hardcover by Tan, Rong Kun Jason; Leong, John A.; Sidhu, Amandeep S., ISBN 3319732129, ISBN-13 9783319732121, Like New Used, Free shipping in the US
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.
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Book Title: Optimized Cloud Based Scheduling
Number of Pages: Xiii, 99 Pages
Publication Name: Optimized Cloud Based Scheduling
Language: English
Publisher: Springer International Publishing A&G
Subject: Systems Architecture / Distributed Systems & Computing, Engineering (General), Intelligence (Ai) & Semantics, Enterprise Applications / General
Publication Year: 2018
Item Weight: 106.6 Oz
Type: Textbook
Subject Area: Computers, Technology & Engineering
Item Length: 9.3 in
Author: John A. Leong, Rong Kun Jason Tan, Amandeep S. Sidhu
Item Width: 6.1 in
Series: Studies in Computational Intelligence Ser.
Format: Hardcover
