Resource Management for Big Data Platforms: Algorithms, Modelling, and High-Performance Computing Techniques

Editors: Pop, Florin, Kołodziej, Joanna, Di Martino, Beniamino (Eds.)
Provides a comprehensive overview of the development of RMS for big data platforms and applications, covering theory, methodologies, experimentation, and real-world applications
Presents state-of-the-art solutions for issues of big data processing, resource and data management, fault tolerance, monitoring and controlling, and security
Discusses the development of related programming models and technologies in information and communication, and how these help in formulating practical solutions for the topics covered

Serving as a flagship driver towards advance research in the area of Big Data platforms and applications, this book provides a platform for the dissemination of advanced topics of theory, research efforts and analysis, and implementation oriented on methods, techniques and performance evaluation. In 23 chapters, several important formulations of the architecture design, optimization techniques, advanced analytics methods, biological, medical and social media applications are presented. These chapters discuss the research of members from the ICT COST Action IC1406 High-Performance Modelling and Simulation for Big Data Applications (cHiPSet). This volume is ideal as a reference for students, researchers and industry practitioners working in or interested in joining interdisciplinary works in the areas of intelligent decision systems using emergent distributed computing paradigms. It will also allow newcomers to grasp the key concerns and their potential solutions.


Number of Pages
XIII, 516
Number of Illustrations and Tables
81 b/w illustrations, 57 illustrations in colour
Topics
Computer Communication Networks
Simulation and Modeling
Performance and Reliability
Database Management



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