An Investigative Study of Competition-Aware Incentive Mechanisms in Mobile Ad Hoc Networks

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This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2026 | Volume : 13 | 01 | Page :
    By

    Manas Kumar Yogi,

  • Nadiminti Sai Priya Satwika,

  1. Assistant Professor, Department of Computer Science and Engineering, Pragati Engineering College (A), Surampalem, Andhra Pradesh, India
  2. Undergraduate Student, Department of Computer Science and Engineering, Pragati Engineering College (A), Surampalem, Andhra Pradesh, India

Abstract

Mobile Ad Hoc Networks (MANETs) present a unique communication paradigm characterized by their decentralized and dynamic nature, where nodes rely on each other for packet forwarding and network maintenance. However, the inherent selfishness of individual nodes and resource constraints often lead to non-cooperative behaviors, significantly degrading network performance. This investigative study delves into the critical role of competition-aware incentive mechanisms in fostering sustainable cooperation within MANETs. Competition, a portmanteau of competition and cooperation, acknowledges that nodes can simultaneously compete for resources while collaborating for collective network benefits. We explore the theoretical underpinnings of competition in MANETs, primarily through the lens of game theory, examining models such as Stackelberg and bargaining games that capture the intricate interplay between competitive and cooperative strategies. The article reviews the evolution from traditional incentive mechanisms, which often focus solely on cooperation, to more sophisticated competition-aware designs that account for both aspects. Furthermore, we investigate the integration of emerging technologies, including blockchain and artificial intelligence, in developing robust and fair incentive structures. The study also analyzes the performance implications of these mechanisms on key network metrics such as throughput, latency, and energy efficiency. Finally, we discuss the prevailing challenges, such as privacy concerns and scalability issues, and outline promising research directions in this evolving field. This comprehensive analysis aims to provide a foundational understanding of competition-aware incentive mechanisms, highlighting their potential to enhance the resilience and efficiency of MANETs.

Keywords: Competition, cooperation, MANET, mobile, resource, self-organizing

How to cite this article:
Manas Kumar Yogi, Nadiminti Sai Priya Satwika. An Investigative Study of Competition-Aware Incentive Mechanisms in Mobile Ad Hoc Networks. Journal of Mobile Computing, Communications & Mobile Networks. 2026; 13(01):-.
How to cite this URL:
Manas Kumar Yogi, Nadiminti Sai Priya Satwika. An Investigative Study of Competition-Aware Incentive Mechanisms in Mobile Ad Hoc Networks. Journal of Mobile Computing, Communications & Mobile Networks. 2026; 13(01):-. Available from: https://journals.stmjournals.com/jomccmn/article=2026/view=237833


References

  1. Aloui A, Hachicha H, Zagrouba E. Multi-Agent-Based Approaches. In: IEEE, editor. IEEE Transactions on Intelligent Transportation Systems. 1st edition. New York, USA: IEEE; 2025. pp. 1–20.
  2. Arshadi H, Kim HM. When Incentives Feel Different. In: MDPI, editor. Electronics. 14th edition. Basel, Switzerland: MDPI; 2025. pp. 4916–4930.
  3. Bianca Ogbo N, Song Z, Han TA. Evolution of Coordination. In: DAI, editor. Distributed Artificial Intelligence. 7th edition. London, UK: Springer; 2025. pp. 38–47. International proceedings data.
  4. Chu W, Shi Y, Jiang X, Ciano T, Zhao B. Game theory approach for secured supply chain. In: Springer, editor. Annals of Operations Research. 1st edition. Berlin, Germany: Springer; 2026. pp. 301–319.
  5. Esmaeilyfard R, Moghisi M. An incentive mechanism design for multitask. In: Springer, editor. The Journal of Supercomputing. 1st edition. Boston, USA: Springer; 2023. pp. 5248–5275.
  6. Garai M, Sliti M, Mrabet M, Ammar LB. AI-Enabled Vehicular Data Offloading. In: IEEE, editor. IEEE Access. 1st edition. New York, USA: IEEE; 2025. pp. 1468–1492.
  7. Gelhaar J, Gürpinar T, Henke M, Otto B. Taxonomy of Incentive Mechanisms. In: PACIS, editor. Pacific Asia Conference on Information Systems. 25th edition. Singapore, Singapore: PACIS; 2021. pp. 1–15.
  8. Huang C, Dachille J, Liu X. Technical report: Coopetition in federated learning. In: arXiv, editor. arXiv Preprints. 1st edition. Ithaca, USA: Cornell University; 2024. pp. 1–10.
  9. Kadoch M. Recent advances in mobile ad hoc networks. In: MDPI, editor. Electronics. 10th edition. Basel, Switzerland: MDPI; 2021. pp. 1446–1460.
  10. Ji K, Bae S, Li N, Han K. Competition-Aware Decision-Making Approach. In: IEEE, editor. IEEE Intelligent Vehicles Symposium. 1st edition. New York, USA: IEEE; 2024. pp. 878–884.
  11. Li Y, Li F, Zhu L, Sharif K, Chen H. Two-tiered incentive mechanism design. In: CCF, editor. CCF Transactions on Pervasive Computing. 1st edition. Beijing, China: Springer; 2022. pp. 339–356.
  12. Machado C, Westphall CM. Blockchain incentivized data forwarding. In: Elsevier, editor. Ad Hoc Networks. 1st edition. Amsterdam, Netherlands: Elsevier; 2021. pp. 102321.
  13. Mandlikova M, Majlingova A. Economic Logistics Optimization. In: MDPI, editor. Logistics. 9th edition. Basel, Switzerland: MDPI; 2025. pp. 74–90. Research logistics case study.
  14. Mianji EM, Muntean GM, Tal I. Enhancing vehicular network security. In: IEEE, editor. IEEE Transactions on Intelligent Transportation Systems. 1st edition. New York, USA: IEEE; 2025. pp. 1–15.
  15. Nan Y, Liu MJ, Luo J, Ye D. Conceptualization of dynamic digital coopetition. In: Elsevier, editor. International Journal of Hospitality Management. 1st edition. Amsterdam, Netherlands: Elsevier; 2025. pp. 104036.
  16. Ryu J, Kim S. Reputation-based opportunistic routing protocol. In: IEEE, editor. IEEE Access. 1st edition. New York, USA: IEEE; 2023. pp. 47701–47711.
  17. Sandhya E, Sk KS, Mantena SV, Desanamukula VS. Enhancing security and efficiency. In: Nature, editor. Scientific Reports. 1st edition. London, UK: Nature Publishing Group; 2025. pp. 818.
  18. Xu Q, Zhang L, Liu Y, Li Z. Enhancing Trust Management System. In: IEEE, editor. IEEE Transactions on Intelligent Transportation Systems. 1st edition. New York, USA: IEEE; 2026. pp. 1–12.
  19. Xu Z, Sun H, Sun P, Kong Q. Requester mobility for crowdsensing. In: Elsevier, editor. Ad Hoc Networks. 1st edition. Amsterdam, Netherlands: Elsevier; 2025. pp. 103680.

Ahead of Print Subscription Review Article
Volume 13
01
Received 13/02/2026
Accepted 19/02/2026
Published 05/03/2026
Publication Time 20 Days


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