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Gathering Big Data in Wireless Sensor Networks by Drone.

Josiane da Costa Vieira Rezende1, Rone Ilídio da Silva2, Marcone Jamilson Freitas Souza1

  • 1Departamento de Computação, Universidade Federal de Ouro Preto, Rua Diogo de Vasconcelos, 122, Bairro Pilar, Ouro Preto 35400-000, Brazil.

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This study optimizes drone tours for Wireless Sensor Networks (WSN) with large data volumes. An algorithm minimizes drone flight time by intelligently selecting data collection points, improving efficiency by up to 30%.

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Area of Science:

  • Computer Science
  • Wireless Sensor Networks
  • Robotics

Background:

  • Existing research on mobile data collection in Wireless Sensor Networks (WSN) often assumes limited data per sensor node.
  • Drones as mobile sinks face energy constraints, limiting their operational time and data collection capacity.
  • Efficient tour planning for drones is crucial for maximizing data retrieval from WSNs with substantial data volumes.

Purpose of the Study:

  • To investigate optimal drone tour strategies for big data gathering in WSNs.
  • To minimize the overall drone flight time required for complete data collection.
  • To address the challenge of limited drone power supply in WSN data collection.

Main Methods:

  • Consideration of sensor nodes with a large volume of data packets.
  • Utilizing a quad-copter drone as a mobile sink with hovering capabilities.
  • Development of a novel algorithm to select sensor nodes for data transmission during drone movement, reducing hover time.

Main Results:

  • The proposed algorithm effectively reduces drone hovering time by strategically managing data collection.
  • Experimental results demonstrate a significant improvement in drone tour efficiency.
  • The algorithm surpasses state-of-the-art heuristics by up to 30% in performance for drone tour optimization.

Conclusions:

  • The developed algorithm provides an efficient solution for big data gathering in WSNs using drones.
  • Minimizing drone flight time and energy consumption is achievable through intelligent tour planning.
  • This approach enhances the practicality and effectiveness of drones in WSN data collection scenarios.