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Dynamic Bandwidth Slicing for Time-Critical IoT Data Streams in the Edge-Cloud Continuum

Habeeb, Fawzy and Alwasel, Khaled and Noor, Ayman and Jha, Devki Nandan and Alqattan, Duaa and Li, Yinhao and Aujla, Gagangeet Singh and Szydlo, Tomasz and Ranjan, Rajiv (2022) 'Dynamic Bandwidth Slicing for Time-Critical IoT Data Streams in the Edge-Cloud Continuum.', IEEE Transactions on Industrial Informatics .

Abstract

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 (IoT) 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 analytics 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 QoS-based multi-level queue traffic scheduling system that can undertake semi-automatic 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.

Item Type:Article
Full text:(AM) Accepted Manuscript
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Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1109/TII.2022.3169971
Publisher statement:© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Date accepted:No date available
Date deposited:06 May 2022
Date of first online publication:25 April 2022
Date first made open access:06 May 2022

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