An enhanced binary classifier for Edge devices

Hurbungs, V.; Bassoo, Vandana; Fowdur, Tulsi Pawan

doi:10.1016/j.micpro.2022.104596

Cited by 4 publications

(1 citation statement)

References 32 publications

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“…It was found that compared to baselines during the rush hours, the proposed approach could reduce the service delay by 8%-20% and the migration cost by more than 75%. Finally in Hurbungs et al (2021), the authors performed a detailed literature review on the edge, fog and cloud computing paradigms and in Hurbungs and Bassoo (2022) an enhanced binary classifier for edge devices was proposed.…”

Section: Related Workmentioning

confidence: 99%

Performance analysis of edge, fog and cloud computing paradigms for real-time video quality assessment and phishing detection

Fowdur

Abdoolla

Doobur

2023

IJPCC

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Purpose The purpose of this paper is to perform a comparative analysis of the delay associated in running two real-time machine learning-based applications, namely, a video quality assessment (VQA) and a phishing detection application by using the edge, fog and cloud computing paradigms. Design/methodology/approach The VQA algorithm was developed using Android Studio and run on a mobile phone for the edge paradigm. For the fog paradigm, it was hosted on a Java server and for the cloud paradigm on the IBM and Firebase clouds. The phishing detection algorithm was embedded into a browser extension for the edge paradigm. For the fog paradigm, it was hosted on a Node.js server and for the cloud paradigm on Firebase. Findings For the VQA algorithm, the edge paradigm had the highest response time while the cloud paradigm had the lowest, as the algorithm was computationally intensive. For the phishing detection algorithm, the edge paradigm had the lowest response time, and the cloud paradigm had the highest, as the algorithm had a low computational complexity. Since the determining factor for the response time was the latency, the edge paradigm provided the smallest delay as all processing were local. Research limitations/implications The main limitation of this work is that the experiments were performed on a small scale due to time and budget constraints. Originality/value A detailed analysis with real applications has been provided to show how the complexity of an application can determine the best computing paradigm on which it can be deployed.

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Section: Related Workmentioning

confidence: 99%