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<p>The growing demand for energy, coupled with the increasing need for environmental protection and energy efficiency, is more pressing than ever. In this context, energy harvesting in networks offers a promising solution to reduce energy waste by utilizing ambient energy to charge devices. With the advent of 6G, new architectures have emerged, including data and energy integrated networks, which use radio frequency energy signals for energy harvesting. While the theoretical foundation of data and energy integrated networks (DEINs) has been established, their evaluation and verification is still difficult to ensure, and the analysis of their effectiveness and performance remains lacking. In this paper, we present a model-based approach utilizing UPPAAL to model, analyze, and evaluate the performance of DEIN networks. We explore various model configurations and conduct stochastic model checking to assess system behavior. Furthermore, we calibrate the model using real-world measurements to validate its effectiveness and demonstrate its capability to investigate diverse energy-related aspects.</p>

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A model-checking based approach to verify data and energy integrated networks (DEINs): toward the formal verification of 6G networks

  • 期刊论文

  • 发表日期：

    2025年11月22日

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  • Ilyes Rezgui,
  • Afef Gafsi,
  • Imen Ben Hafaiedh,
  • Yassine Gana

摘要

The growing demand for energy, coupled with the increasing need for environmental protection and energy efficiency, is more pressing than ever. In this context, energy harvesting in networks offers a promising solution to reduce energy waste by utilizing ambient energy to charge devices. With the advent of 6G, new architectures have emerged, including data and energy integrated networks, which use radio frequency energy signals for energy harvesting. While the theoretical foundation of data and energy integrated networks (DEINs) has been established, their evaluation and verification is still difficult to ensure, and the analysis of their effectiveness and performance remains lacking. In this paper, we present a model-based approach utilizing UPPAAL to model, analyze, and evaluate the performance of DEIN networks. We explore various model configurations and conduct stochastic model checking to assess system behavior. Furthermore, we calibrate the model using real-world measurements to validate its effectiveness and demonstrate its capability to investigate diverse energy-related aspects.