Cloud Computing for Optimization: Foundations, Applications, and Challenges

Softcover Nachdruck of the original 1. Auflage 2018
ISBN: 978-3-030-08832-3
Verlag: Springer International Publishing

Buch, Englisch, Band 39, 463 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 721 g

Reihe: Studies in Big Data

This book discusses harnessing the real power of cloud computing in optimization problems, presenting state-of-the-art computing paradigms, advances in applications, and challenges concerning both the theories and applications of cloud computing in optimization with a focus on diverse fields like the Internet of Things, fog-assisted cloud computing, and big data. In real life, many problems – ranging from social science to engineering sciences – can be identified as complex optimization problems. Very often these are intractable, and as a result researchers from industry as well as the academic community are concentrating their efforts on developing methods of addressing them. Further, the cloud computing paradigm plays a vital role in many areas of interest, like resource allocation, scheduling, energy management, virtualization, and security, and these areas are intertwined with many optimization problems. Using illustrations and figures, this book offers students and researchers a clear overview of the concepts and practices of cloud computing and its use in numerous complex optimization problems.

Zielgruppe

Research

Autoren/Hrsg.

Mishra, Bhabani Shankar Prasad

Jagadev, Alok Kumar

Das, Himansu

Dehuri, Satchidananda

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Cloud-Computing, Grid-Computing
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Optimierung
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Big Data

Inhaltsverzeichnis

Nature Inspired Optimizations in Cloud Computing: Applications and Challenges.- Resource Allocation in Cloud Computing Using OptimizationTechniques.- Energy Aware Resource Allocation Model for IaaS Optimization.- A Game Theoretic Model for Cloud Federation.- Resource Provisioning Strategy for Scienti?c Work?ows in Cloud Computing Environment.- Consolidation in Cloud Environment Using OptimizationTechniques.