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Priority-Based Data Collection for UAV-Aided Mobile Sensor Network.

Xiaoyan Ma1, Tianyi Liu2, Song Liu1

  • 1College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China.

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|May 31, 2020
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Summary
This summary is machine-generated.

This study introduces new algorithms for efficient data collection in dynamic mobile wireless sensor networks (WSNs) using multiple unmanned aerial vehicles (UAVs). The proposed methods enhance network fairness and communication opportunities for all nodes.

Keywords:
collision-freedata collectionmobile nodesmultiple unmanned aerial vehicleswireless sensor networks

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • Mobile wireless sensor networks (WSNs) face challenges in data collection due to dynamic network topologies.
  • The mobility of unmanned aerial vehicles (UAVs) and sensor nodes complicates efficient data routing and scheduling.

Purpose of the Study:

  • To design efficient data collection protocols for highly dynamic multi-UAV-aided mobile WSNs.
  • To develop mechanisms that ensure collision-free scheduling and balanced node distribution among multiple UAVs.
  • To improve network fairness and communication opportunities in WSNs with mobile elements.

Main Methods:

  • Proposed prioritized-based contact-duration frame selection mechanism (PCdFS) and prioritized-based multiple contact-duration frame selection mechanisms (PMCdFS).
  • Developed a Balance algorithm integrating PCdFS and PMCdFS for collision-free communication.
  • Key algorithm design principles include prioritizing nodes with shorter contact durations and not requiring higher transmission rates for lower-priority nodes.

Main Results:

  • Extensive simulations and real-world experiments demonstrated the effectiveness of the proposed algorithms.
  • Experiments with 15 mobile nodes showed significant enhancement in network fairness.
  • Validated algorithm applicability in a realistic scenario on a campus path.

Conclusions:

  • The proposed PCdFS, PMCdFS, and Balance algorithm effectively address data collection challenges in dynamic multi-UAV-aided mobile WSNs.
  • The algorithms enhance network fairness by improving communication opportunities for nodes with shorter contact durations.
  • The study confirms the practical applicability and performance of the developed methods in real-world network environments.