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Cluster-Based Control Plane Messages Management in Software-Defined Flying Ad-Hoc Network.

Pedro Cumino1, Kaled Maciel1, Thaís Tavares1

  • 1Computer Science Faculty, Federal University of Pará (UFPA), Belém 66075-110, Brazil.

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Summary
This summary is machine-generated.

This study introduces CAPONE, a novel cluster-based approach for managing control plane messages in Software-Defined Flying Ad-hoc Networks (SDN-FANETs). CAPONE enhances network performance by predicting UAV information and reducing overhead, improving packet delivery and energy efficiency.

Keywords:
SDN-FANETUAV contextual informationclusteringcontrol plane management

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Area of Science:

  • Computer Science
  • Networking
  • Artificial Intelligence

Background:

  • Flying Ad-hoc Networks (FANETs) are increasingly vital for autonomous and deployable systems, requiring efficient network management.
  • Software-Defined Networking in FANETs (SDN-FANETs) offers programmability but faces challenges in control message dissemination due to high mobility and communication constraints.
  • Existing SDN-FANET architectures struggle with low overhead and high performance in control message delivery.

Purpose of the Study:

  • To propose a Cluster-based control Plane messages management in Software-defined flying ad-hoc Network (CAPONE) for efficient SDN-FANET control.
  • To reduce bandwidth consumption and signaling overhead in FANETs through intelligent message management.
  • To enhance control message delivery performance in dynamic FANET environments.

Main Methods:

  • CAPONE utilizes UAV contextual information to predict necessary data, eliminating the need for direct control message transmission.
  • The system employs the Gap statistics method to determine the optimal number of clusters within the FANET.
  • A Fuzzy C-means algorithm is then used to assign UAVs to clusters and designate group leaders.

Main Results:

  • CAPONE significantly reduces bandwidth consumption and signaling overhead compared to existing SDN-FANET architectures.
  • Simulations demonstrate improved Packet Delivery Ratio (PDR) in FANET scenarios using the CAPONE approach.
  • The proposed method shows considerable gains in energy efficiency for UAVs within the network.

Conclusions:

  • CAPONE effectively addresses the challenges of control message dissemination in SDN-FANETs by employing a hierarchical, cluster-based strategy.
  • The predictive capabilities and clustering approach of CAPONE lead to substantial improvements in network performance metrics.
  • This research offers a promising solution for more efficient and robust management of future autonomous aerial systems.