Overview
- A comprehensive survey of the agent-based models, technologies, architectures and solutions for data intensive computing and massive data processing systems
- Discusses the autonomous, adaptive and self-organizing agent-based solution for massive storage, management and analytics in intelligent distributed systems
- Presents the implementation and simulation of the efficient agent-inspired techniques for data, resource, security and system reliability management
- Presents a valuable analysis of the limits of different practical approaches and addresses the most important directions in the research and future engineering trends and their consequences
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Big Data (SBD, volume 14)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (9 chapters)
Keywords
About this book
This book presents new approaches that advance research in all aspects of agent-based models, technologies, simulations and implementations for data intensive applications. The nine chapters contain a review of recent cross-disciplinary approaches in cloud environments and multi-agent systems, and important formulations of data intensive problems in distributed computational environments together with the presentation of new agent-based tools to handle those problems and Big Data in general.
This volume can serve as a reference for students, researchers and industry practitioners working in or interested in joining interdisciplinary work in the areas of data intensive computing and Big Data systems using emergent large-scale distributed computing paradigms. It will also allow newcomers to grasp key concepts and potential solutions on advanced topics of theory, models, technologies, system architectures and implementation of applications in Multi-Agent systems and data intensive computing.
Editors and Affiliations
Bibliographic Information
Book Title: Intelligent Agents in Data-intensive Computing
Editors: Joanna Kołodziej, Luís Correia, José Manuel Molina
Series Title: Studies in Big Data
DOI: https://doi.org/10.1007/978-3-319-23742-8
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing Switzerland 2016
Hardcover ISBN: 978-3-319-23741-1Published: 30 September 2015
Softcover ISBN: 978-3-319-36520-6Published: 23 August 2016
eBook ISBN: 978-3-319-23742-8Published: 21 September 2015
Series ISSN: 2197-6503
Series E-ISSN: 2197-6511
Edition Number: 1
Number of Pages: XVIII, 216
Topics: Computational Intelligence, Data Mining and Knowledge Discovery, Artificial Intelligence