Sublinear Algorithms for Big Data Applications

• Κύριοι συγγραφείς: Wang, Dan (Συγγραφέας), Han, Zhu (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2015.
• Σειρά: SpringerBriefs in Computer Science,
• Θέματα: Computer science.; Computer communication systems.; Database management.; Electrical engineering.; Computer Science.; Database Management.; Computer Communication Networks.; Communications Engineering, Networks.
• Φυσική περιγραφή: XI, 85 p. 30 illus., 20 illus. in color. online resource.
• ISBN: 9783319204482
• ISSN: 2191-5768

The brief focuses on applying sublinear algorithms to manage critical big data challenges. The text offers an essential introduction to sublinear algorithms, explaining why they are vital to large scale data systems. It also demonstrates how to apply sublinear algorithms to three familiar big data applications: wireless sensor networks, big data processing in Map Reduce and smart grids. These applications present common experiences, bridging the theoretical advances of sublinear algorithms and the application domain. Sublinear Algorithms for Big Data Applications is suitable for researchers, engineers and graduate students in the computer science, communications and signal processing communities.