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FSF: Applying Machine Learning Techniques to Data Forwarding in Socially Selfish Opportunistic Networks.

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Summary

This study introduces the FriendShip and Acquaintanceship Forwarding (FSF) protocol for opportunistic networks. FSF improves data delivery by considering node social ties and selfishness, boosting delivery ratios up to 20%.

Keywords:
friendshipmachine learningopportunistic networksroutingselfishness

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Area of Science:

  • Computer Science
  • Networking
  • Distributed Systems

Background:

  • Opportunistic networks offer communication solutions where traditional infrastructure is unavailable or overloaded.
  • Efficient data delivery in these networks remains a challenge, balancing delivery efficiency, delay, and cost.
  • Existing routing protocols often rely on network state or node mobility, with social behavior emerging as a promising alternative.

Purpose of the Study:

  • To propose a novel routing protocol, FriendShip and Acquaintanceship Forwarding (FSF), for opportunistic networks.
  • To enhance data delivery efficiency by incorporating social ties, node selfishness, and device resource levels into routing decisions.

Main Methods:

  • Developed the FriendShip and Acquaintanceship Forwarding (FSF) protocol, which classifies social ties and assesses node selfishness and resource levels.
  • Utilized logistic functions to model node selfishness and evaluated resource constraints of potential relay nodes.
  • Conducted trace-driven simulation experiments using the ONE simulator.

Main Results:

  • The FSF algorithm significantly outperforms existing schemes by increasing the delivery ratio by up to 20%.
  • FSF introduces a lower number of forwarding events compared to previous methods.
  • Buffer management algorithms are critical for network performance, especially in scenarios involving selfish nodes.

Conclusions:

  • Accounting for node selfishness and social relationships in routing decisions is crucial for improving opportunistic network performance.
  • The FSF protocol offers a more efficient and effective approach to data delivery in challenging network environments.
  • Further research into buffer management strategies can further optimize opportunistic network performance.