Distributed Processing Allocation of Machine Learning in Wireless Sensor Networks

Jun Motoyama, Rina Ooka, Takumi Miyoshi, Taku Yamazaki, Takuya Asaka

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

Abstract

Distributed processing technology in wireless sensor network (WSN) has attracted attention because of the performance improvement of sensor nodes. Although the conventional methods divide and allocate computational processing of machine learning to sensor nodes, appropriate allocation has not been realized from the viewpoint of the whole network. In this paper, assuming that multiple machine learning processes occur simultaneously, we propose a processing division and allocation method to equalize processing load on sensor nodes. The evaluation results show that the method can almost fairly distribute the load to sensor nodes.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728173993
DOIs
Publication statusPublished - 2020 Sep 28
Event7th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020 - Taoyuan, Taiwan, Province of China
Duration: 2020 Sep 282020 Sep 30

Publication series

Name2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020

Conference

Conference7th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020
Country/TerritoryTaiwan, Province of China
CityTaoyuan
Period20/9/2820/9/30

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Artificial Intelligence
  • Computer Science Applications
  • Signal Processing
  • Electrical and Electronic Engineering
  • Instrumentation

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