Resource Management for Big Data Platforms

Algorithms, Modelling, and High-Performance Computing Techniques

  • Florin Pop
  • Joanna Kołodziej
  • Beniamino Di Martino

Part of the Computer Communications and Networks book series (CCN)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Architecture of Big Data Platforms and Applications

    1. Front Matter
      Pages 1-1
    2. Marco Gribaudo, Mauro Iacono, Francesco Palmieri
      Pages 3-34
    3. Mihaela-Catalina Nita, Mihaela Vasile, Florin Pop, Valentin Cristea
      Pages 35-53
    4. Viktor Medvedev, Olga Kurasova
      Pages 55-67
    5. Weidong Bao, Ji Wang, Xiaomin Zhu
      Pages 83-95
    6. Michał Karpowicz, Ewa Niewiadomska-Szynkiewicz, Piotr Arabas, Andrzej Sikora
      Pages 97-127
    7. Ionut Anghel, Tudor Cioara, Ioan Salomie
      Pages 129-144
  3. Big Data Analysis

    1. Front Matter
      Pages 145-145
    2. Dongfang Zhao, Akash Mahakode, Sandip Lakshminarasaiah, Ioan Raicu
      Pages 147-170
    3. Nayat Sanchez-Pi, Luis Martí, José Manuel Molina, Ana C. Bicharra García
      Pages 171-188
    4. Nitin Sukhija, Alessandro Morari, Ioana Banicescu
      Pages 189-203
    5. Bunjamin Memishi, Shadi Ibrahim, María S. Pérez, Gabriel Antoniu
      Pages 205-240
    6. Agnieszka Jakóbik
      Pages 241-261
  4. Biological and Medical Big Data Applications

    1. Front Matter
      Pages 263-263
    2. Edvard Pedersen, Lars Ailo Bongo
      Pages 265-277
    3. Suejb Memeti, Sabri Pllana, Joanna Kołodziej
      Pages 279-309
    4. Luca Agnello, Albert Comelli, Salvatore Vitabile
      Pages 311-337
    5. Rui Camacho, Jorge G. Barbosa, Altino Sampaio, João Ladeiras, Nuno A. Fonseca, Vítor S. Costa
      Pages 339-363

About this book

Introduction

This book constitutes a flagship driver towards presenting and supporting advance research in the area of Big Data platforms and applications. Extracting valuable information from raw data is especially difficult considering the velocity of growing data from year to year and the fact that 80% of data is unstructured. In addition, data sources are heterogeneous (various sensors, users with different profiles, etc.) and are located in different situations or contexts. Successful contributions may range from advanced technologies, applications and innovative solutions to global optimization problems in scalable large-scale computing systems to development of methods, conceptual and theoretical models related to Big Data applications and massive data storage and processing. The book provides, in this sense, a platform for the dissemination of advanced topics of theory, research efforts and analysis and implementation for Big Data platforms and applications being oriented on methods, techniques and performance evaluation.

This book presents new ideas, analysis, implementations and evaluation of next-generation Big Data platforms and applications. In 23 chapters, several important formulations of the architecture design, optimization techniques, advanced analytics methods, biological, medical and social media applications are presented. These subjects represent the main objectives of ICT COST Action IC1406 High-Performance Modelling and Simulation for Big Data Applications (cHiPSet) and the research presented in these chapters was performed by joint collaboration of members from this action. This volume will serve 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 potential solutions for the selected topics.

Keywords

Big-Data platforms High-performance computing Modelling and simulation Massive data processing Performance analysis

Editors and affiliations

  • Florin Pop
    • 1
  • Joanna Kołodziej
    • 2
  • Beniamino Di Martino
    • 3
  1. 1.University Politehnica of BucharestBucharestRomania
  2. 2.Cracow University of TechnologyCracowPoland
  3. 3.Second University of NaplesNaplesItaly

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-44881-7
  • Copyright Information Springer International Publishing AG 2016
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-44880-0
  • Online ISBN 978-3-319-44881-7
  • Series Print ISSN 1617-7975
  • Series Online ISSN 2197-8433
  • About this book