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Dynamic bandwidth slicing for time-critical IoT data streams in the edge-cloud continuum

Lookup NU author(s): Dr Fawzy Mohammad H Habeeb, Dr Dev JhaORCiD, Duaa Alqattan, Yinhao Li, Tomasz Szydlo, Professor Raj Ranjan

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Abstract

© 2005-2012 IEEE.Edge computing has gained momentum in recent years, as complementary to cloud computing, for supporting applications (e.g., industrial control systems) that require time-critical communication guarantees. While edge computing can provide immediate analysis of streaming data from Internet of Things devices, those devices lack computing capabilities to guarantee reasonable performance for time-critical applications. To alleviate this critical problem, the prevalent trend is to offload these data analytic tasks from the edge devices to the cloud. However, existing offloading approaches are static in nature as they are unable to adapt varying workload and network conditions. To handle these issues, we present a novel distributed and quality of services based multilevel queue traffic scheduling system that can undertake semiautomatic bandwidth slicing to process time-critical incoming traffic in the edge-cloud environments. Our developed system shows a great enhancement in latency and throughput as well as reduction in energy consumption for edge-cloud environments.

Publication metadata

Author(s): Habeeb F, Alwasel K, Noor A, Jha DN, AlQattan D, Li Y, Aujla GS, Szydlo T, Ranjan R

Publication type: Article

Publication status: Published

Journal: IEEE Transactions on Industrial Informatics

Year: 2024

Volume: 18

Issue: 11

Pages: 8017-8026

Print publication date: 01/11/2022

Online publication date: 25/04/2022

Acceptance date: 12/04/2022

ISSN (print): 1551-3203

ISSN (electronic): 1941-0050

Publisher: IEEE

URL: https://doi.org/10.1109/TII.2022.3169971

DOI: 10.1109/TII.2022.3169971

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