In managing network quality of service (QoS), this research uses the Fibonacci pattern to optimize delay control and bandwidth allocation. QoS is very important in contemporary network management, especially considering the increasing demand for stable and effective data services. This study prioritizes data based on traffic levels using a Fibonacci algorithm simulation. Each priority is assigned a value corresponding to the Fibonacci sequence, which allows for resource allocation that is more in line with network load.The simulation was conducted under normal and overload conditions. The research results show that conventional methods, such as round-robin and weighted fair queuing, can improve QoS efficiency with the Fibonacci pattern by up to 15%. This improvement primarily focuses on managing important data packets such as real-time communication and video streaming, and reducing latency. Additionally, this technique is better at adapting to traffic changes.The research results show that the Fibonacci pattern can be an innovative method for managing network QoS, especially for complex priority needs. By using the Fibonacci pattern as a data priority management technique, this research helps improve network quality of service (QoS). This method is capable of improving bandwidth allocation efficiency and reducing latency by up to 15% compared to conventional approaches such as Round-Robin and Weighted Fair Queuing. The main contribution of this research is to offer a new approach based on Fibonacci patterns that can be adapted to the dynamics of network traffic.
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