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Big Data: Exascale computation and beyond

Editorial Board
Lead Guest Editors:
  • Thoudam Doren Singh ()
  • Dr. Ripon Patgiri (National Institute of Technology Silchar)
Aims & Scope
Big data is the one of the most emerging technology, which includes science, engineering, business and the arts. Data is growing at an exponential pace. Its growth is many fold, and hence, it is defined by many V’s and a C. The Big Data poses many challenges, which includes data capture, curation, storage, search, sharing, transfer, analysis, and visualization. Moreover, there is a rapid growth of modern technology in the IT industry, which keeps the data growth rate of Big Data at an exponential pace. For instance, 5G, IoT, Fog Computing, Wearable technology, etc. demands rising of Big Data 2.0.
  • Big Data vs Big Computing
  • Big Data Storage Systems
  • Big Data Processing Systems
  • Big Data Analytics
  • Big Data Visualization
  • Big Data Privacy and Security
  • Big Data Tools
  • Big Data Streaming
  • Big Data Ecosystem
  • HDFS and Metadata Server
  • Job and Task scheduling
  • Load Balancing
  • Replication, Duplication, and Deduplication
  • Issues and Challenges of Datacenters
  • Modern Storage devices
  • Big Graph
  • Exascale Computing: Data-intensive approach
  • Energy aware computing in Big Data
  • Role of GPU in Big Data
  • Applications of Big Data
  • Interdisciplinary Study- Bioinformatics, High Energy Physics etc.
  • Big Data vs Big Data 2.0: Technology Transfer
  • Big Data 2.0: Architecture
  • Big Data 2.0: Future trends
  • Big Data 2.0: Issues and challenges
Manuscript submission deadline:
Notification of acceptance:
Submission of final revised paper:
Publication of special issue (tentative):

Scalable Information Systems
Submission Closed