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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM46199
Volume:
9 |
4 |
Apr 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
5G networks promise super-fast internet, but efficiently sharing resources is a big challenge, especially when users directly connect with each other (Peer-to-Peer). This research explores a new way to allocate resources in 5G P2P communication. We use machine learning to predict how much data will be used and adjust resource sharing in real-time. This means that users with the most urgent needs get priority, and resources are distributed fairly. Our method significantly improved network performance. Simulations showed a 30% increase in data transfer speeds, a 25% reduction in delays, and an 18% overall efficiency boost. Compared to older methods, our approach better balances the load and minimizes data loss. Extensive testing in a 5G environment confirmed the system’s effectiveness, demonstrating its ability to handle many users and adapt to changing conditions. In conclusion, our research shows that P2P communication, combined with intelligent resource allocation, can unlock the full potential of 5G networks for data transfer.
KEYWORDS
Publication Date
4/28/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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