Abstract
This paper introduces the Distributed Utility Function Algorithm (D-AFU) as a notable progression in managing and optimizing network traffic within distributed settings. Based on the utility function principle, D-AFU dynamically adjusts data rate in response to ever-changing network demands, with optimal performance and a higher user experience. Contrary to the centralized model, D-AFU employs a distributed, scalable, and resilient against failures and system overloads mechanism. Its efficiency is validated using the NS-3 simulator. Three main metrics were used: the data rate allocation, utility per session, and fairness (quantified by the Gini coefficient). D-AFU displays exceptional performance and low latency, particularly vital for real-time applications with high Quality of Service (QoS) requirements.
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