Dynamic Distribution of Edge Intelligence at the Node Level for Internet of Things

Hawzhin Mohammed, Tolulope A. Odetola, Nan Guo, Syed Rafay Hasan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, dynamic deployment of Convolutional Neural Network (CNN) architecture is proposed utilizing only IoT-level devices. By partitioning and pipelining the CNN, it horizontally distributes the computation load among resource-constrained devices (called as horizontal collaboration), which in turn increases the throughput. Through partitioning, we can decrease the computation and energy consumption on individual IoT devices and increase the throughput without sacrificing accuracy. Also, by processing the data at the generation point, data privacy can be achieved. The results show that throughput can be increased by 1.55x to 1.75x for sharing the CNN into two and three resource-constrained devices, respectively.

Original languageEnglish (US)
Title of host publication2021 IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2021 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages330-333
Number of pages4
ISBN (Electronic)9781665424615
DOIs
StatePublished - Aug 9 2021
Event2021 IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2021 - Virtual, East Lansing, United States
Duration: Aug 9 2021Aug 11 2021

Publication series

NameMidwest Symposium on Circuits and Systems
Volume2021-August
ISSN (Print)1548-3746

Conference

Conference2021 IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2021
Country/TerritoryUnited States
CityVirtual, East Lansing
Period8/9/218/11/21

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

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