Feature driven survey of big data systems

Research output: Chapter in Book/Report/Conference proceedingConference paperAcademicpeer-review

2 Citations (Scopus)

Abstract

Big Data has become a very important driver for innovation and growth for various industries such as health, administration, agriculture, defence, and education. Storing and analysing large amounts of data are becoming increasingly common in many of these application areas. In general, different application domains might require different type of big data systems. Although, lot has been written on big data it is not easy to identify the required features for developing big data systems that meets the application requirements and the stakeholder concerns. In this paper we provide a survey of big data systems based on feature modelling which is a technique that is utilized for defining the common and variable features of a domain. The feature model has been derived following an extensive literature study on big data systems. We present the feature model and discuss the features to support the understanding of big data systems.

Original languageEnglish
Title of host publicationIoTBD 2016 - Proceedings of the International Conference on Internet of Things and Big Data
EditorsV. Chang, M. Ramachandran, V.M. Munoz, G. Wills, R. Walters
PublisherSciTePress
Pages348-355
ISBN (Print)9789897581830
DOIs
Publication statusPublished - 2016
EventInternational Conference on Internet of Things and Big Data, IoTBD 2016 - Rome, Italy
Duration: 23 Apr 201625 Apr 2016

Conference

ConferenceInternational Conference on Internet of Things and Big Data, IoTBD 2016
Country/TerritoryItaly
CityRome
Period23/04/1625/04/16

Keywords

  • Big data
  • Feature driven design
  • Feature modeling

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