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Updated: Sep 29, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Predictive Energy-Aware Routing Solution for Industrial IoT Evaluated on a WSN Hardware Platform.

Eusebiu Jecan1, Catalin Pop2, Ovidiu Ratiu2

  • 1Communications Department, Technical University of Cluj-Napoca, 28 Memorandumului Street, 400114 Cluj-Napoca, Romania.

Sensors (Basel, Switzerland)
|March 26, 2022
PubMed
Summary

Predictive energy-aware routing (PEAR) enhances industrial wireless sensor network (IWSN) lifetime predictability. This solution balances energy consumption, significantly extending sensor operational duration and ensuring system availability.

Keywords:
IIoTISA100.11aIWSNenergy awareenergy marginpredictable lifetimerouting

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Area of Science:

  • Industrial Internet of Things (IIoT)
  • Wireless Sensor Networks (WSNs)
  • Network Communication Standards

Background:

  • Sensor lifetime predictability is crucial for industrial wireless sensor networks (IWSNs) to ensure system availability, cost-efficiency, and safety.
  • Dynamic network conditions and centralized deployments in IWSNs significantly impact sensor lifespan.
  • The absence of energy-aware mechanisms compromises sensor lifetime predictability.

Purpose of the Study:

  • To define a conceptual model for enhancing energy predictability and efficiency in IWSNs.
  • To introduce the Predictive Energy-Aware Routing (PEAR) solution for assured network lifetime predictability.
  • To validate PEAR's effectiveness within the constraints of the ISA100.11a standard and VR950 IIoT Gateway.

Main Methods:

  • Development of a conceptual model for energy-aware mechanisms in IWSNs.
  • Implementation of the Predictive Energy-Aware Routing (PEAR) solution.
  • Integration of PEAR with the ISA100.11a communication standard and VR950 IIoT Gateway hardware.

Main Results:

  • PEAR ensures predictable energy consumption across single and multiple network clusters.
  • Intracluster energy balancing reduced overconsumption by 10.4 times after 210 routing changes.
  • Intercluster energy balancing increased cluster lifetime by an average of 2.3 times (up to 3.2 times) and reduced average consumption by 23.6%.

Conclusions:

  • The PEAR solution demonstrates feasibility and effectiveness in enhancing energy predictability and efficiency in IWSNs.
  • PEAR's energy-aware routing and balancing capabilities are suitable for real-world industrial applications.
  • The research validates the conceptual model's potential for improving IWSN operational longevity and reliability.