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Short-distance Transport of Resources02:12

Short-distance Transport of Resources

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Short-distance transport refers to transport that occurs over a distance of just 2-3 cells, crossing the plasma membrane in the process. Small uncharged molecules, such as oxygen, carbon dioxide, and water, can diffuse across the plasma membrane on their own. In contrast, ions and larger molecules require the assistance of transport proteins due to their charge or size. Transport across membranes also occurs within individual cells, playing a variety of essential roles for the plant as a whole.
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Related Experiment Video

Updated: Jan 29, 2026

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem
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Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem

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Intelligent Agent for Resource Allocation from Mobile Infrastructure to Vehicles in Dynamic Environments Scalable on

Renato Cumbal1, Berenice Arguero1, Germán V Arévalo1

  • 1Carrera de Telecomunicaciones, Universidad Politécnica Salesiana, Quito 170525, Ecuador.

Sensors (Basel, Switzerland)
|January 28, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces an intelligent framework for Vehicle-to-Infrastructure (V2I) communications, optimizing Road-Side Unit (RSU) placement and radio-resource allocation. The system achieves over 90% coverage using minimal RSUs and dynamically manages resources for efficient intelligent transportation systems.

Keywords:
AIQ-learningV2IVANETdynamic coverageresource allocationsmart generic network controller

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Area of Science:

  • Intelligent Transportation Systems
  • Wireless Communications
  • Network Optimization

Background:

  • Urban mobility faces increasing complexity, necessitating advanced communication frameworks.
  • Existing Vehicle-to-Infrastructure (V2I) systems require efficient resource allocation and infrastructure deployment strategies.

Purpose of the Study:

  • To develop an intelligent optimization and resource-allocation framework for V2I communications.
  • To enhance vehicular coverage and radio-resource efficiency in urban environments.

Main Methods:

  • Macroscopic mobility analysis integrated with Integer Linear Programming (ILP) for optimal Road-Side Unit (RSU) placement.
  • Q-learning-based Smart Generic Network Controller (SGNC) for dynamic radio-resource allocation.
  • Simulations in a realistic georeferenced urban scenario.

Main Results:

  • ILP model activated only 2.9% of RSUs, ensuring over 90% vehicular coverage.
  • SGNC demonstrated stable resource allocation, managing 10 antennas and 120 resources.
  • Dynamic reallocation mechanism maintained efficiency above 70% system capacity.

Conclusions:

  • The proposed framework offers a scalable solution for V2I deployment in intelligent transportation systems.
  • Dynamic resource allocation significantly improves efficiency and coverage consistency compared to static methods.
  • The intelligent framework effectively addresses the complexities of modern urban mobility.