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Game Theory-Based Efficient Message Forwarding Scheme for Opportunistic Networks

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Advanced Information Networking and Applications (AINA 2024)

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Abstract

In order to efficiently transmit data packets, this paper proposes a method known as GT-EMFT for game-theoretic efficient message forwarding in opportunistic networks. In this protocol, the optimal approach for choosing the next hop depends on a cooperative game between two players which frame the game by taking into account the context information, channel interference, meeting likelihood, and successful delivery of the related node from the destination. Using the Opportunistic Network Environment Simulator, simulation results demonstrate that the proposed protocol GT-EMFT outperforms the benchmark protocols Epidemic and GTEER in terms of average latency, delivery ratio, and average residual energy.

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Authors and Affiliations

  1. Department of Computer Science, Bharati College, University of Delhi, New Delhi, India

    Vinesh Kumar

  2. Department of Computer Science and Engineering, Sant Longowal Institute of Engineering and Technology, Longowal, India

    Jagdeep Singh

  3. Department of Information Technology, Netaji Subhas University of Technology, New Delhi, India

    Sanjay Kumar Dhurandher

  4. National Institute of Electronics and Information Technology, New Delhi, India

    Sanjay Kumar Dhurandher

  5. Department of Computer Science, Toronto Metropollitan University, Toronto, ON, M5B2K3, Canada

    Isaac Woungang

Authors
  1. Vinesh Kumar
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  2. Jagdeep Singh
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  3. Sanjay Kumar Dhurandher
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  4. Isaac Woungang
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Corresponding author

Correspondence to Jagdeep Singh .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

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© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Kumar, V., Singh, J., Dhurandher, S.K., Woungang, I. (2024). Game Theory-Based Efficient Message Forwarding Scheme for Opportunistic Networks. In: Barolli, L. (eds) Advanced Information Networking and Applications. AINA 2024. Lecture Notes on Data Engineering and Communications Technologies, vol 199. Springer, Cham. https://doi.org/10.1007/978-3-031-57840-3_1

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