Human-centric storage resource mechanism for big data on cloud service architecture

Hyun Woo Kim, Jong Hyuk Park, Young Sik Jeong

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

With the rapid advancement of information technology in recent years, significant research addressing the efficient storage of big data has been conducted. Traditionally, big data with media-driven service have simply implied extensive amounts of data. However, this definition has evolved to include the extraction of values, analysis, and the prediction of results from a vast volume of unstructured and varied datasets. Because of the explosive growth of computer processing technologies, the creation of big data has originated from unstructured data, text data, image data, and location data created by a variety of digital devices. Classically, the storage of big data has been administered by companies that provide storage services or by specialized storage companies. Significant cost is incurred to store big data efficiently and maintain sufficient storage requirements, which increase continuously. In this paper, a human-centric Resource-Integrated System for Big Data (RISBD) is proposed that utilizes the resources of legacy desktop computers for big data storage to future communication. This is advantageous in terms of the cost of implementing a new storage system. Furthermore, it provides high storage scalability because it is an XML-based standard storage integration system developed using software.

Original languageEnglish
Pages (from-to)2437-2452
Number of pages16
JournalJournal of Supercomputing
Volume72
Issue number7
DOIs
StatePublished - 1 Jul 2016

Keywords

  • Big data storage
  • Distributed file system
  • Fault tolerance
  • Human-centric resource management
  • Legacy desktop computer
  • Media-driven service
  • Resource-integrated mechanism

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