CF4BDA: A Conceptual Framework for Big Data Analytics Applications in the Cloud
(2015) In IEEE Access 3. p.1944-1952- Abstract
- Building big data analytics applications (BDA) in the Cloud introduces inevitable challenges such as loss of control and uncertainty. To address the existing challenges, numerous efforts have been made on BDA application engineering to optimise quality of BDA applications in the Cloud, such as performance and reliability. However, there is still a lack of systematic view on engineering BDA applications in the Cloud. Therefore, in this paper, we present a conceptual framework named CF4BDA to analyse existing work on BDA applications from two perspectives: the lifecycle of BDA applications and the objects involved in the context of BDA applications in the Cloud. The framework can help researchers and practitioners identify the research... (More)
- Building big data analytics applications (BDA) in the Cloud introduces inevitable challenges such as loss of control and uncertainty. To address the existing challenges, numerous efforts have been made on BDA application engineering to optimise quality of BDA applications in the Cloud, such as performance and reliability. However, there is still a lack of systematic view on engineering BDA applications in the Cloud. Therefore, in this paper, we present a conceptual framework named CF4BDA to analyse existing work on BDA applications from two perspectives: the lifecycle of BDA applications and the objects involved in the context of BDA applications in the Cloud. The framework can help researchers and practitioners identify the research opportunities in a structured way and guide implementing BDA applications in the Cloud. We perform a preliminary evaluation of the usefulness of CF4BDA by applying it to analyse a set of representative studies. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/8171377
- author
- Lu, Qinghua ; Li, Zheng LU ; Kihl, Maria LU ; Zhu, Liming and Zhang, Weishan
- organization
- publishing date
- 2015
- type
- Contribution to journal
- publication status
- published
- subject
- in
- IEEE Access
- volume
- 3
- pages
- 1944 - 1952
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- scopus:84959855743
- wos:000371388200148
- ISSN
- 2169-3536
- DOI
- 10.1109/ACCESS.2015.2490085
- project
- LCCC
- language
- English
- LU publication?
- yes
- id
- 8a1031d6-5f92-42b6-9367-32e7f72f78c6 (old id 8171377)
- date added to LUP
- 2016-04-01 13:02:00
- date last changed
- 2022-01-27 08:57:06
@article{8a1031d6-5f92-42b6-9367-32e7f72f78c6, abstract = {{Building big data analytics applications (BDA) in the Cloud introduces inevitable challenges such as loss of control and uncertainty. To address the existing challenges, numerous efforts have been made on BDA application engineering to optimise quality of BDA applications in the Cloud, such as performance and reliability. However, there is still a lack of systematic view on engineering BDA applications in the Cloud. Therefore, in this paper, we present a conceptual framework named CF4BDA to analyse existing work on BDA applications from two perspectives: the lifecycle of BDA applications and the objects involved in the context of BDA applications in the Cloud. The framework can help researchers and practitioners identify the research opportunities in a structured way and guide implementing BDA applications in the Cloud. We perform a preliminary evaluation of the usefulness of CF4BDA by applying it to analyse a set of representative studies.}}, author = {{Lu, Qinghua and Li, Zheng and Kihl, Maria and Zhu, Liming and Zhang, Weishan}}, issn = {{2169-3536}}, language = {{eng}}, pages = {{1944--1952}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, series = {{IEEE Access}}, title = {{CF4BDA: A Conceptual Framework for Big Data Analytics Applications in the Cloud}}, url = {{http://dx.doi.org/10.1109/ACCESS.2015.2490085}}, doi = {{10.1109/ACCESS.2015.2490085}}, volume = {{3}}, year = {{2015}}, }