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IoT-QWatch: A Novel Framework to Support the Development of Quality Aware Autonomic IoT Applications

Lookup NU author(s): Professor Raj Ranjan

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Abstract

IEEEThe unprecedented growth of Internet of Things (IoT) is leading to its increased usage in various domains, such as manufacturing, health, and smart cities. A majority of IoT applications are autonomic, i.e., they operate under minimal/no human intervention, and make decisions/actuations based on machine-to-machine communication and data analytics. A key challenge in the development of such applications is the ability to measure their quality while they are working in a diverse and heterogeneous IoT ecosystem. In this paper, we propose an agent based Internet of Things-Quality Watch (IoT-QWatch) framework that provides the ability to measure IoT quality metrics at each stage of the autonomic IoT application life cycle running in the IoT ecosystem. We envision that IoT-QWatch will enable the development of a new generation of quality-aware autonomic IoT applications that are able to be resilient to the heterogeneous and uncertain nature of IoT ecosystems. We present architectural details and implementation of IoT-QWatch, and corresponding models used to measure IoT quality metrics at different stages. We conduct extensive experiments using a real-world IoT test bed from the domain of manufacturing to validate the efficacy of IoT-QWatch. Experimental outcomes provide promising results in realising IoT-QWatch in real-world deployment, while the framework itself offers significant extensibility to include new models for measuring IoT quality metrics.


Publication metadata

Author(s): Fizza K, Jayaraman PP, Banerjee A, Auluck N, Ranjan R

Publication type: Article

Publication status: Published

Journal: IEEE Internet of Things Journal

Year: 2023

Pages: Epub ahead of print

Online publication date: 22/05/2023

Acceptance date: 02/04/2018

ISSN (electronic): 2327-4662

Publisher: Institute of Electrical and Electronics Engineers Inc.

URL: https://doi.org/10.1109/JIOT.2023.3278411

DOI: 10.1109/JIOT.2023.3278411


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