​Energy-efficient solutions for wireless sensor networks: Dissertation

Research output: ThesisDissertationCollection of Articles

Abstract

Wireless sensors play a bigger and bigger role in our everyday life and they have become a part of our life in homes, vehicles, traffic, food production and healthcare, monitoring and controlling our activities. Low-cost and resource-efficient solutions are an essential part of this development.
The aim of the study was to develop solutions, which improve the energy efficiency of wireless sensor networks yet still fulfil the requirements of monitoring applications.
In the study, five new solutions were developed to save energy in wireless sensor networks and all the solutions were studied and verified with test bed implementations. The developed solutions are:
1. Energy-efficient medium access control (MAC), namely revive MAC (R-MAC) for duty-cycling networks with a long sampling interval (many minutes)
2. Wake-up radio solution for on-demand sampling networks, which uses the main radio as the wake-up transmitter
3. Energy-efficient internet of things (IoT) routing solution for wake-up routing with a routing protocol for low-Power and lossy networks (RPL)
4. Energy-efficient IoT compression solution: robust header compression (ROHC) compression with constrained application protocol (CoAP)
5. Data analysis solution based on an energy-efficient sensor node, where filter clogging is forecast from analysis of the vibration data at the node.
All the developed solutions were promising and can be utilized in many domain areas. The solutions can be considered as proofs of concept, which need to be developed further for use in final products.
Original languageEnglish
QualificationDoctor Degree
Awarding Institution
  • University of Oulu
Supervisors/Advisors
  • Leiviskä, Kauko, Supervisor, External person
  • Frantti, Tapio, Supervisor, External person
  • Paavola, Marko, Supervisor, External person
Award date26 Jan 2018
Publisher
Print ISBNs978-952-62-1760-4
Electronic ISBNs978-952-62-1761-1
Publication statusPublished - 2018
MoE publication typeG5 Doctoral dissertation (article)

Keywords

  • compression
  • data analysis
  • energy efficiency
  • vibration
  • wake-up radio
  • wireless measuring
  • Wireless sensor network
  • CoAP
  • IoT
  • MAC
  • ROHC
  • RPL

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