Introducing distributed dynamic data-intensive (D3) science: Understanding applications and infrastructure

Shantenu Jha, Daniel S. Katz, Andre Luckow, Neil Chue Hong, Omer Rana, Yogesh Simmhan

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

A common feature across many science and engineering applications is the amount and diversity of data and computation that must be integrated to yield insights. Datasets are growing larger and becoming distributed; their location, availability, and properties are often time-dependent. Collectively, these characteristics give rise to dynamic distributed data-intensive applications. While “static” data applications have received significant attention, the characteristics, requirements, and software systems for the analysis of large volumes of dynamic, distributed data, and data-intensive applications have received relatively less attention. This paper surveys several representative dynamic distributed data-intensive application scenarios, provides a common conceptual framework to understand them, and examines the infrastructure used in support of applications.

Original languageEnglish (US)
Article numbere4032
JournalConcurrency Computation
Volume29
Issue number8
DOIs
StatePublished - Apr 25 2017

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Computer Science Applications
  • Computer Networks and Communications
  • Computational Theory and Mathematics

Keywords

  • data intensive
  • distributed
  • dynamic
  • scientific applications

Fingerprint Dive into the research topics of 'Introducing distributed dynamic data-intensive (D3) science: Understanding applications and infrastructure'. Together they form a unique fingerprint.

  • Cite this