Resource Management for Big Data Platforms

Algorithms, Modelling, and High-Performance Computing Techniques
 Previously published in hardcover
Besorgungstitel | Lieferzeit:3-5 Tage I
ISBN-13:
9783319831558
Einband:
Previously published in hardcover
Seiten:
516
Autor:
Florin Pop
Gewicht:
1083 g
Format:
235x155x mm
Serie:
Computer Communications and Networks
Sprache:
Englisch
Beschreibung:

Performance Modeling of Big Data Oriented Architectures
Marco Gribaudo, Mauro Iacono, and Francesco Palmieri

Workflow Scheduling Techniques for Big Data Platforms
Mihaela-Catalina Nita, Mihaela Vasile, Florin Pop, and Valentin Cristea

Cloud Technologies: A New Level for Big Data Mining
Viktor Medvedev and Olga Kurasova

Agent Based High-Level Interaction Patterns for Modeling Individual and Collective Optimizations Problems
Rocco Aversa and Luca Tasquier

Maximize Profit for Big Data Processing in Distributed Datacenters
Weidong Bao, Ji Wang, and Xiaomin Zhu

Energy and Power Efficiency in the Cloud
Michal Karpowicz, Ewa Niewiadomska-Szynkiewicz, Piotr Arabas, and Andrzej Sikora

Context Aware and Reinforcement Learning Based Load Balancing System for Green Clouds
Ionut Anghel, Tudor Cioara, and Ioan Salomie

High-Performance Storage Support for Scientific Big Data Applications on the Cloud
Dongfang Zhao, Akash Mahakode, Sandip Lakshminarasaiah, and Ioan Raicu

Information Fusion for Improving Decision-Making in Big Data Applications
Nayat Sanchez-Pi, Luis Martí, José Manuel Molina, and Ana C. Bicharra Garca

Load Balancing and Fault Tolerance Mechanisms for Scalable and Reliable Big Data Analytics
Nitin Sukhija, Alessandro Morari, and Ioana Banicescu Bunjamin Memishi, Shadi Ibrahim, María S. Pérez, and Gabriel Antoniu

Big Data Security
Agnieszka Jakóbik

Big Biological Data Management
Edvard Pedersen and Lars Ailo Bongo

Optimal Worksharing of DNA Sequence Analysis on Accelerated Platforms
Suejb Memeti, Sabri Pllana, and Joanna Kolodziej

Feature Dimensionality Reduction for Mammographic Report Classification
Agnello Luca, Comelli Albert, and Vitabile Salvatore

Parallel Algorithms for Multi-Relational Data Mining: Application to Life Science Problems
Rui Camacho, Jorge G. Barbosa, Altino Sampaio, João Ladeiras, Nuno A. Fonseca and Vítor S. Costa

Parallelization of Sparse Matrix Kernels for Big Data Applications
Oguz Selvitopi, Kadir Akbudak, and Cevdet Aykanat

Delivering Social Multimedia Content with Scalability
Irene Kilanioti and George A. Papadopoulos

A Java-Based Distributed Approach for Generating Large-Scale Social Network Graphs
Vlad Serbanescu, Keyvan Azadbakht, and Frank de Boer

Predicting Video Virality on Twitter
Irene Kilanioti and George A. Papadopoulos

Big Data uses in Crowd Based Systems
Cristian Chilipirea, Andreea-Cristina Petre, and Ciprian Dobre

Evaluation of a Web Crowd-Sensing IoT Ecosystem Providing Big Data Analysis
Ioannis Vakintis, Spyros Panagiotakis, George Mastorakis, and Constandinos X. Mavromoustakis

A Smart City Fighting Pollution by Efficiently Managing and Processing Big Data from Sensor Networks
Voichita Iancu, Silvia Cristina Stegaru, and Dan Stefan Tudose
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.

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