Managing and Processing Big Data in Cloud Computing

Managing and Processing Big Data in Cloud Computing

Rajkumar Kannan (King Faisal University, Saudi Arabia), Raihan Ur Rasool (King Faisal University, Saudi Arabia), Hai Jin (Huazhong University of Science and Technology, China) and S.R. Balasundaram (National Institute of Technology, Tiruchirappalli, India)
Release Date: January, 2016|Copyright: © 2016 |Pages: 307
ISBN13: 9781466697676|ISBN10: 1466697679|EISBN13: 9781466697683|DOI: 10.4018/978-1-4666-9767-6

Description

Big data has presented a number of opportunities across industries. With these opportunities come a number of challenges associated with handling, analyzing, and storing large data sets. One solution to this challenge is cloud computing, which supports a massive storage and computation facility in order to accommodate big data processing.

Managing and Processing Big Data in Cloud Computing explores the challenges of supporting big data processing and cloud-based platforms as a proposed solution. Emphasizing a number of crucial topics such as data analytics, wireless networks, mobile clouds, and machine learning, this publication meets the research needs of data analysts, IT professionals, researchers, graduate students, and educators in the areas of data science, computer programming, and IT development.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • Big Data Virtualization
  • Data Clusters
  • Mobile Cloud Computing
  • Resource Scheduling
  • Sustainability Issues
  • Unstructured Data

Reviews and Testimonials

This volume contains 15 chapters on managing and processing big data in cloud computing. Computer scientists from Europe, Pakistan, India, and Ethiopia address text classification, social networks, Map Reduce, Hadoop, virtual packet streaming, wireless multi-hop networks, mobile cloud computing, big data virtualization, machine learning algorithms for big data computation, resource scheduling, techniques for big data analysis, green and energy-efficiency issues, and the heterogeneity paradigm in big data architectures.

– ProtoView Reviews

This is a very research-heavy volume, dense with original research, analyses, and a lot of additional reading references. Although the topics are sometimes fairly narrow, some chapters contain pages and pages of references for additional reading and research that can be incredibly valuable. For researchers or those trying to better utilize big data and cloud computing, this volume should prove to be a very valuable resource.

– Tyler Manolovitz, Digital Resources Coordinator, Sam Houston State University, USA, American Reference Books Annual

Table of Contents and List of Contributors

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Author(s)/Editor(s) Biography

Rajkumar Kannan received the B.Sc and M.Sc degrees in Computer Science from Bharathidasan University – Tiruchirappalli, India in 1991 and 1993 respectively and the PhD degree in Computer Applications from National Institute of Technology – Tiruchirappalli, India in 2007. Rajkumar works for King Faisal University, Saudi Arabia in the College of Computer Science and Information Technology. His research activities primarily lie at the confluence of multimedia, information retrieval, semantic web, social informatics and collective intelligence. Rajkumar is a member of ACM and life member of CSI-India and ISTE-India.
Raihan ur Rasool is currently serving at King Faisal University (KFU) as Assistant Professor –where he is leading the effort of building CCSIT Innovation and Research Showcase (CIRS). Prior to joining CCSIT-KFU he was Fulbright post-doctorate fellow at the University of Chicago. He has over 8 years of post-PhD research, teaching and administration experience. After earning a PhD from Wuhan University of Technology, China in 2007 he joined National University of Sciences and Technology (NUST) Pakistan; where he fulfilled duties at different levels. He worked as a knowledge group head, head of department and Associate Dean. Under his leadership, NUST Pakistan won the ACM global award of ‘Best School Services’ consecutively for 3 years. His research interests include computer architecture, virtualization technology, cluster and cloud computing, peer-to-peer computing and big data analysis with pattern matching. His research work, comprising over 35 articles is published in various international conferences and journals. He has published in leading avenues of research like ISCA, HiPEC, CCGrid, ACM SIGARCH, IEEE Transactions in Cloud Computing & FGFS.
Hai Jin is a Professor of Computer Science and Engineering at the Huazhong University of Science and Technology (HUST) in China. He is now the Dean of School of Computer Science and Technology at HUST. He received his Ph.D. in computer engineering from HUST in 1994. In 1996, he was awarded German Academic Exchange Service (DAAD) fellowship for visiting the Technical University of Chemnitz in Germany. He worked for the University of Hong Kong between 1998 and 2000 and participated in the HKU Cluster project. He worked as a visiting scholar at the University of Southern California between 1999 and 2000. He is the chief scientist of the largest grid computing project, ChinaGrid, in China. Dr. Jin is a senior member of IEEE and member of ACM. He is the member of Grid Forum Steering Group (GFSG). His research interests include computer architecture, cluster computing and grid computing, virtualization technology, peer-to-peer computing, network storage, network security.
S. R. Balasundaram has been working since 1987 at the National Institute of Technology (formerly known as Regional Engineering College) Tiruchirappalli. After completing M.C.A. from PSG College of Technology, Coimbatore, he joined REC Trichy during 1987 as a Computer Programmer. He completed M.E. in Computer Science & Engineering during 1992. Currently, he is working as an Associate Professor in the Department of Computer Applications, earned his doctorate in “E-Learning and Assessment” from NIT, Trichy, and has more than 40 papers in reputed Journals and Proceedings of International Conferences. His areas of interest are: Web & Mobile Technologies, Cognitive Sciences and e-Learning Technologies.