Distributing On-Demand Analytics Processing on Heterogeneous Industrial Internet of Things Edge Hardware

Phil Lane, Richard Hill, Stuart Berry

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The ever increasing competitiveness of the business landscape is leading to a growing interest in data analytics, machine learning, forecasting, model generation, training workloads, visualisation, etc. The Industrial Internet of Things (IIoT) is a key element of the realisation of these and deployment of IIoT introduces heterogeneous hardware into organisations. The computing capability of this hardware is often relatively under utilised. In this contribution, we investigate what performance can be extracted from a heterogeneous system of edge compute nodes combined with some centralised compute capability.
Original languageEnglish
Title of host publicationThe 9th IEEE International Conference on Smart City and Informatization (iSCI2021)
PublisherIEEE Computer Society
Number of pages8
Publication statusAccepted/In press - 20 Oct 2021
Event9th IEEE International Conference on Smart City and Informatizion - Hybrid mode due to COVID-19 (online and Shenyang China, Hybrid (Online and Shenyang, China)
Duration: 20 Oct 202122 Oct 2021
Conference number: 9
https://isci2021.sau.edu.cn/index.jsp?urltype=tree.TreeTempUrl&wbtreeid=1001

Conference

Conference9th IEEE International Conference on Smart City and Informatizion
Abbreviated titleiSCI 2021
CityHybrid (Online and Shenyang, China)
Period20/10/2122/10/21
Internet address

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