Design and Development of Traffic Management Algorithm to enhance QoS in 6G Network
- DOI
- 10.2991/978-94-6463-831-8_12How to use a DOI?
- Keywords
- AWGN; BER; DBCA; FDR; SNR; QoS
- Abstract
Many experts and researchers are currently engrossed in improving wireless networks and systems by introducing effective protocols, architectures, services, or applications. Thus, the requirements of the various stakeholders in network design, operation, and deployment can be fulfilled. The main objective of this work is to improve the quality of service of wireless networks by estimating channel quality at the link and physical layers using a federated learning approach. It is proposed that different types of traffic can be allocated based on priority levels for rate adoption utilizing a combination of traffic shaping and traffic policing techniques. Here, the design and development of the Demand Based Channel Allocation (DBCA) algorithm is suggested for managing network traffic by controlling the flow rate of that traffic. The suggested system substantially boosts throughput in response to changes in nodes, simulation time, and packet size. In contrast, a BER is also significantly attained as compared with a constant rate algorithm.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Hemlata M. Jadhav AU - Makrand M. Jadhav AU - Neeta Thune AU - Archana Kanwade PY - 2025 DA - 2025/08/31 TI - Design and Development of Traffic Management Algorithm to enhance QoS in 6G Network BT - Proceeding of the 1st International Conference on Lifespan Innovation (ICLI 2025) PB - Atlantis Press SP - 93 EP - 100 SN - 2468-5739 UR - https://doi.org/10.2991/978-94-6463-831-8_12 DO - 10.2991/978-94-6463-831-8_12 ID - Jadhav2025 ER -