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

✍ Scribed by Florin Pop, Joanna Kołodziej, Beniamino Di Martino (eds.)

• Publisher: Springer International Publishing
• Year: 2016
• Tongue: English
• Leaves: 509
• Series: Computer Communications and Networks
• Edition: 1
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages i-xiii
Front Matter....Pages 1-1
Performance Modeling of Big Data-Oriented Architectures....Pages 3-34
Workflow Scheduling Techniques for Big Data Platforms....Pages 35-53
Cloud Technologies: A New Level for Big Data Mining....Pages 55-67
Agent-Based High-Level Interaction Patterns for Modeling Individual and Collective Optimizations Problems....Pages 69-81
Maximize Profit for Big Data Processing in Distributed Datacenters....Pages 83-95
Energy and Power Efficiency in Cloud ....Pages 97-127
Context-Aware and Reinforcement Learning-Based Load Balancing System for Green Clouds....Pages 129-144
Front Matter....Pages 145-145
High-Performance Storage Support for Scientific Big Data Applications on the Cloud....Pages 147-170
Information Fusion for Improving Decision-Making in Big Data Applications....Pages 171-188
Load Balancing and Fault Tolerance Mechanisms for Scalable and Reliable Big Data Analytics....Pages 189-203
Fault Tolerance in MapReduce: A Survey....Pages 205-240
Big Data Security....Pages 241-261
Front Matter....Pages 263-263
Big Biological Data Management....Pages 265-277
Optimal Worksharing of DNA Sequence Analysis on Accelerated Platforms....Pages 279-309
Feature Dimensionality Reduction for Mammographic Report Classification....Pages 311-337
Parallel Algorithms for Multirelational Data Mining: Application to Life Science Problems....Pages 339-363
Front Matter....Pages 365-365
Parallelization of Sparse Matrix Kernels for Big Data Applications....Pages 367-382
Delivering Social Multimedia Content with Scalability....Pages 383-399
A Java-Based Distributed Approach for Generating Large-Scale Social Network Graphs....Pages 401-417
Predicting Video Virality on Twitter....Pages 419-439
Front Matter....Pages 365-365
Big Data Uses in Crowd Based Systems....Pages 441-459
Evaluation of a Web Crowd-Sensing IoT Ecosystem Providing Big Data Analysis....Pages 461-488
A Smart City Fighting Pollution, by Efficiently Managing and Processing Big Data from Sensor Networks....Pages 489-513
Back Matter....Pages 515-516

✦ Subjects

Computer Communication Networks;Simulation and Modeling;Performance and Reliability;Database Management