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Enabling Efficient Communications with Resource Constrained Information Endpoints in Smart Homes.

Diego Sánchez-de-Rivera1, Borja Bordel2, Ramón Alcarria

  • 1Universidad Politécnica de Madrid, UPM Campus Sur, Km 7.5 de la Autovía de Valencia, Madrid 28031, Spain. diegosanchez@dit.upm.es.

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Summary

This study introduces an efficient, automatic configuration algorithm for smart home information endpoints. It ensures devices work together and optimizes resource usage by dynamically adjusting settings like lifecycle and data compression.

Keywords:
Smart Homesdynamic configurationefficiencyinformation endpointsmathematical modelsresource consumption

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Area of Science:

  • Computer Science
  • Engineering

Background:

  • Smart Homes leverage the Internet of Things (IoT) and Cyber-Physical Systems (CPS) for enhanced living environments.
  • These systems involve sensors capturing data, servers processing it, and endpoints consuming the information.
  • Resource-constrained components and massive machine-type communications characterize these dense architectures.

Purpose of the Study:

  • To propose an automatic and dynamic configuration algorithm for information endpoints in Smart Homes.
  • To address the manual configuration limitations of endpoints, unlike existing sensor-server communication solutions.
  • To ensure interoperability and adequate resource usage through efficient endpoint configuration.

Main Methods:

  • Identification and mathematical modeling of costs associated with endpoint-server communications in Smart Homes.
  • Development of a dynamic configuration algorithm based on the principle of "efficiency."
  • Experimental validation using both real-world implementation and simulation scenarios.

Main Results:

  • The proposed algorithm dynamically selects the most efficient configuration for each endpoint at any given moment.
  • Demonstrated ability to guarantee device interoperability within Smart Home environments.
  • Ensured adequate resource usage by adapting endpoint lifecycle and information compression mechanisms.

Conclusions:

  • The developed algorithm effectively automates and optimizes information endpoint configuration in Smart Homes.
  • This approach enhances resource management and ensures seamless device interaction.
  • The solution is validated through practical implementation and simulation, confirming its efficacy.