Time slotted channel hopping scheduling based on the energy consumption of wireless sensor networks

Tadanori Matsui, Hiroaki Nishi

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

5 Citations (Scopus)

Abstract

Wireless Sensor Nnetworks (WSNs) are becoming increasingly widespread owing to the introduction of the Internet of Things (IoT) and the networks' comparatively low cost and usability. WSNs are usually battery-powered, owing to their low power consumption, which however limits their computational performance. The lifetime of a WSN strongly depends on its communication-related power consumption. Time Slotted Channel Hopping (TSCH) solves the problem of power consumption by featuring both time-division and frequency- division multiplexing in the system's Media Access Control (MAC) layer. In this paper, Pruning-based Coloring Scheduling (PRCOS) is proposed, which is an algorithm for TSCH scheduling that accounts for the power consumption to extend the system's lifetime. Using mathematical analysis, we show that the proposed algorithm decreases the transfer time and energy consumption by factors of 0.43 and 0.57, respectively, compared with existing algorithms.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE 15th International Workshop on Advanced Motion Control, AMC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages605-610
Number of pages6
ISBN (Electronic)9781538619469
DOIs
Publication statusPublished - 2018 Jun 1
Event15th IEEE International Workshop on Advanced Motion Control, AMC 2018 - Tokyo, Japan
Duration: 2018 Mar 92018 Mar 11

Publication series

NameProceedings - 2018 IEEE 15th International Workshop on Advanced Motion Control, AMC 2018

Other

Other15th IEEE International Workshop on Advanced Motion Control, AMC 2018
Country/TerritoryJapan
CityTokyo
Period18/3/918/3/11

Keywords

  • Centralized Scheduling
  • Energy Consumption
  • TSCH
  • Wireless Sensor Network

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Mechanical Engineering
  • Control and Optimization

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