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A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
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Data Freshness and End-to-End Delay in Cross-Layer Two-Tier Linear IoT Networks.

Imane Cheikh1, Essaid Sabir1,2, Rachid Aouami3

  • 1NEST Research Group, LRI Lab, ENSEM, Hassan II University of Casablanca, Casablanca 20000, Morocco.

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Summary

This study explores using multiple radio access technologies (multi-RAT) to reduce IoT device transmission delays and maintain data freshness using the age of information (AoI) metric. Simulations demonstrate the framework

Keywords:
IoTad hoc networkage of informationcellular networkdelaymulti-RATs integrationqueuing theory

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Telecommunications

Background:

  • Radio access networks face evolving demands, shifting focus from capacity to data freshness.
  • Exponential traffic growth necessitates advanced solutions like multiple radio access technology (multi-RAT).
  • Internet of Things (IoT) networks require efficient energy use and timely data delivery.

Purpose of the Study:

  • Investigate multi-RAT for reducing user transmission delay.
  • Preserve Quality of Service (QoS) while maintaining information freshness using the Age of Information (AoI) metric.
  • Develop a framework for forecasting network performance in multi-hop and cellular coordinated systems.

Main Methods:

  • Modeled a queuing system encompassing network and MAC layers.
  • Investigated coordination between multi-hop and cellular networks.
  • Developed a framework with models and tools for performance forecasting (end-to-end delay and AoI).

Main Results:

  • Comprehensive simulations were conducted to validate the proposed framework.
  • The framework effectively forecasts network performance metrics.
  • Numerical results highlight the benefits of the multi-RAT approach for delay and freshness.

Conclusions:

  • Leveraging multi-RAT can significantly reduce transmission delays in IoT networks.
  • The proposed framework provides valuable insights into network performance tuning and optimization.
  • The study demonstrates a viable approach to balancing QoS, delay, and data freshness in modern networks.