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Feature Driven Survey of Big Data Systems

Topics: Big Data fundamentals – Services Computing, Techniques, Recommendations and Frameworks; Modeling, Experiments, Sharing Technologies & Platforms; Modern Architecture; Software Engineering Approaches, including Formal Methods, Agile Methods and Theoretical Algorithms for IoT and Big Data; System Design and Architecture

Authors: Cigdem Avci Salma 1 ; Bedir Tekinerdogan 2 and Ioannis N. Athanasiadis 2

Affiliations: 1 Wageningen University and European Space Agency, Netherlands ; 2 Wageningen University, Netherlands

ISBN: 978-989-758-183-0

Keyword(s): Feature Driven Design, Feature Modeling, Big Data.

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.

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Paper citation in several formats:
Salma C., Tekinerdogan B. and Athanasiadis I. (2016). Feature Driven Survey of Big Data Systems.In Proceedings of the International Conference on Internet of Things and Big DataISBN 978-989-758-183-0, pages 348-355. DOI: 10.5220/0005877503480355

@conference{iotbd16,
author={Cigdem Avci Salma and Bedir Tekinerdogan and Ioannis N. Athanasiadis},
title={Feature Driven Survey of Big Data Systems},
booktitle={Proceedings of the International Conference on Internet of Things and Big Data},
year={2016},
pages={348-355},
doi={10.5220/0005877503480355},
isbn={978-989-758-183-0},
}

TY - CONF

JO - Proceedings of the International Conference on Internet of Things and Big Data
TI - Feature Driven Survey of Big Data Systems
SN - 978-989-758-183-0
AU - Salma C.
AU - Tekinerdogan B.
AU - Athanasiadis I.
PY - 2016
SP - 348
EP - 355
DO - 10.5220/0005877503480355

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