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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Configuring a context-aware middleware for Wireless Sensor Networks.

Nadia Gámez1, Javier Cubo, Lidia Fuentes

  • 1Department of Computer Science, University of Málaga, Campus de Teatinos, 29071, Málaga, Spain. nadia@lcc.uma.es

Sensors (Basel, Switzerland)
|September 27, 2012
PubMed
Summary
This summary is machine-generated.

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This study introduces a method to automatically adapt FamiWare middleware for Ambient Intelligence systems. The approach enables efficient management of complex contexts from diverse devices, enhancing application adaptability in the Future Internet.

Area of Science:

  • Computer Science
  • Ubiquitous Computing
  • Middleware Engineering

Background:

  • Future Internet applications require dynamic reconfiguration with minimal human intervention due to changing environments.
  • Context-aware applications need robust context acquisition and adaptation decision-making techniques.
  • Managing complex, heterogeneous context data from various devices and users is challenging.

Purpose of the Study:

  • To address the limitation in FamiWare middleware regarding automatic incorporation of new context management.
  • To propose a metamodel-based approach for defining and configuring context-aware FamiWare variants.
  • To enable automatic generation of context-aware middleware for heterogeneous devices.

Main Methods:

  • Context modeling using a metamodel to define system-specific contexts.
Keywords:
AALAmIWSNconfigurationcontext-awaremiddlewaremodel-driven

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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Published on: September 8, 2023

  • Defining a mapping to transform metamodel elements into FamiWare family elements.
  • Utilizing the FamiWare configuration process to customize new context-aware variants.
  • Automatic code generation for deployment on heterogeneous devices.

    • Main Results:

    • A novel process for extending FamiWare with new context management capabilities.
    • Successful automatic transformation of context models into configurable middleware.
    • Generated FamiWare variants efficiently manage contexts on heterogeneous devices.
    • Demonstrated adaptability of Ambient Intelligence systems through automated middleware reconfiguration.

    Conclusions:

    • The proposed metamodel-driven approach effectively enables automatic context management in FamiWare.
    • This method enhances the adaptability and efficiency of Ambient Intelligence systems.
    • The process facilitates the creation of customized, context-aware middleware for diverse applications.