Cantitate/Preț
Produs

Intelligent Agents in Data-intensive Computing: Studies in Big Data, cartea 14

Editat de Joanna Kołodziej, Luís Correia, José Manuel Molina
en Limba Engleză Hardback – 30 sep 2015
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.
 
 
Citește tot Restrânge

Toate formatele și edițiile

Toate formatele și edițiile Preț Express
Paperback (1) 61822 lei  6-8 săpt.
  Springer International Publishing – 23 aug 2016 61822 lei  6-8 săpt.
Hardback (1) 62423 lei  6-8 săpt.
  Springer International Publishing – 30 sep 2015 62423 lei  6-8 săpt.

Din seria Studies in Big Data

Preț: 62423 lei

Preț vechi: 78028 lei
-20% Nou

Puncte Express: 936

Preț estimativ în valută:
11947 12603$ 9956£

Carte tipărită la comandă

Livrare economică 02-16 ianuarie 25

Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9783319237411
ISBN-10: 3319237411
Pagini: 216
Ilustrații: XVIII, 216 p.
Dimensiuni: 155 x 235 x 20 mm
Greutate: 0.51 kg
Ediția:1st ed. 2016
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Big Data

Locul publicării:Cham, Switzerland

Public țintă

Research

Cuprins

Bio-Inspired ICT for Big Data Management in Healthcare.- Control AspectsiIn Multiagent Systems.- A Different Perspective of Agent-Based Techniques: Markovian Agents.- Autonomous, Adaptive, And Self-Organized Multiagent Systems for the Optimization of Decentralized Industrial Processes.-  Formal Specification Language and Agent Applications.- Large-Scale Simulations with FLAME.- Cloud Computing and Multiagent Systems, A Promising Relationship.- Privacy Risks in Cloud Computing.- Adaptive Resource Allocation in Cloud Computing Based on Agreement Protocols.

Textul de pe ultima copertă

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.
 
 

Caracteristici

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