
Intelligent Distributed Computing XII
Springer (Publisher)
Published on 26. January 2019
Book
Paperback/Softback
XV, 448 pages
978-3-030-07616-0 (ISBN)
Description
This book gathers a wealth of research contributions on recent advances in intelligent and distributed computing, and which present both architectural and algorithmic findings in these fields. A major focus is placed on new techniques and applications for evolutionary computation, swarm intelligence, multi-agent systems, multi-criteria optimization and Deep/Shallow machine learning models, all of which are approached as technological drivers to enable autonomous reasoning and decision-making in complex distributed environments. Part of the book is also devoted to new scheduling and resource allocation methods for distributed computing systems. The book represents the peer-reviewed proceedings of the 12th International Symposium on Intelligent Distributed Computing (IDC 2018), which was held in Bilbao, Spain, from October 15 to 17, 2018.
More details
Series
Edition
Softcover Reprint of the Original 1st 2018 ed.
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
108 s/w Abbildungen
XV, 448 p. 108 illus.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 25 mm
Weight
698 gr
ISBN-13
978-3-030-07616-0 (9783030076160)
DOI
10.1007/978-3-319-99626-4
Schweitzer Classification
Other editions
Additional editions

Javier Del Ser | Eneko Osaba | Miren Nekane Bilbao
Intelligent Distributed Computing XII
Book
09/2018
Springer
€213.99
Shipment within 10-15 days
Content
Part I: Main Track.- Long distance in-links for ranking enhancement.- Concept Tracking and Adaptation for Drifting Data Streams under Extreme Verification Latency.- Adversarial Sample Crafting for Time Series Classification with Elastic Similarity Measures.- Slot Co-allocation Optimization in Distributed Computing with Heterogeneous Resources.- About Designing an Observer Pattern-Based Architecture for a Multi-Objective Metaheuristic Optimization Framework.- Scalable Inference of Gene Regulatory Networks with the Spark Distributed Computing Platform.- Finding Best Compiler Options for Critical Software Using Parallel Algorithms.- Drift Detection over Non-stationary Data Streams using Evolving Spiking Neural Networks.- Part II: Energy.- A Hybrid Ensemble of Heterogeneous Regressors for Wind Speed Estimation in Wind Farms.- Bio-inspired approximation to MPPT under real irradiation conditions.- Part III: Industry.- Decision Making in Industry 4.0 Scenarios supported by Imbalanced Data Classification.