Latency Analysis of Cloud Infrastructure for Time-Critical IoT Use Cases

Kartinah, Zen and Saju, Mohanan and Seleviawati, Tarmizi and Noralifah, Annuar (2022) Latency Analysis of Cloud Infrastructure for Time-Critical IoT Use Cases. In: 2022 Applied Informatics International Conference (AiIC), 18-19 May 2022, Serdang, Malaysia.

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Official URL: https://ieeexplore.ieee.org/document/9914601

Abstract

The time-critical Internet of Things (IoT) use cases such as driverless cars and robotic surgical arms need high bandwidth and low latency for real-time intelligent data processing and trained machine learning inference. Latency in real-time processing is influenced by many factors such as artificial intelligence (AI) computing algorithm, device processing capabilities, the frameworks, and also the distance from the cloud infrastructure. However, the geographical distance between the data origin and data processing is one of the major factors contributing to the network latency for timecritical IoT use cases. In this paper, we analyzed the latency from a particular client point based on the live data generated by their cloud data centers. The experiments were done through the big three cloud vendors, which are Microsoft Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP). As a result, a time-critical IoT low latency approach is proposed in this paper.

Item Type: Proceeding (Paper)
Uncontrolled Keywords: Latency, IoT, Edge Computing, Cloud Computing, RTT.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Faculties, Institutes, Centres > Faculty of Computer Science and Information Technology
Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Depositing User: Gani
Date Deposited: 27 Dec 2022 06:34
Last Modified: 27 Dec 2022 06:34
URI: http://ir.unimas.my/id/eprint/41012

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