Context-Aware Data Analytics Variability in IoT Neural Network-Based Systems

Nathalia Nascimento, Paulo Alencar, Donald Cowan

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    2 Scopus citations

    Abstract

    Emergent software applications are increasingly becoming (self-)adaptive and autonomous. Further, Internet of Things (IoT) applications increasingly involve data analytics. The introduction of neural networks in IoT systems has enabled a new generation of applications capable of performing complex sensing and actuation analysis tasks that were not previously possible with other approaches. A key component in the development of these systems is the ability to represent data analytics variability, which captures the ways in which the system can adapt in terms of the data analysis at design and run times. Although variability has been explored in the domain of software product lines (SPLs), data analytics variability in IoT neural network-based systems still seems to be poorly understood and needs to be investigated appropriately. In this paper, we introduce an approach to capture data analytics variability in IoT neural network-based systems (IoTNNSs). The approach represents several types of variability inherent in the development of these analytics systems, including those related to the application context, behavior, quality attributes, IoT devices, and neural networks.

    Original languageEnglish (US)
    Title of host publicationProceedings - 2021 IEEE International Conference on Big Data, Big Data 2021
    EditorsYixin Chen, Heiko Ludwig, Yicheng Tu, Usama Fayyad, Xingquan Zhu, Xiaohua Tony Hu, Suren Byna, Xiong Liu, Jianping Zhang, Shirui Pan, Vagelis Papalexakis, Jianwu Wang, Alfredo Cuzzocrea, Carlos Ordonez
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages3595-3600
    Number of pages6
    ISBN (Electronic)9781665439022
    DOIs
    StatePublished - 2021
    Event2021 IEEE International Conference on Big Data, Big Data 2021 - Virtual, Online, United States
    Duration: Dec 15 2021Dec 18 2021

    Publication series

    NameProceedings - 2021 IEEE International Conference on Big Data, Big Data 2021

    Conference

    Conference2021 IEEE International Conference on Big Data, Big Data 2021
    Country/TerritoryUnited States
    CityVirtual, Online
    Period12/15/2112/18/21

    All Science Journal Classification (ASJC) codes

    • Information Systems and Management
    • Artificial Intelligence
    • Computer Vision and Pattern Recognition
    • Information Systems

    Fingerprint

    Dive into the research topics of 'Context-Aware Data Analytics Variability in IoT Neural Network-Based Systems'. Together they form a unique fingerprint.

    Cite this