Implementing an optimal rate allocation tuned to the user quality of experience

Optimal resource allocation elegantly kaizens bandwidth utilization in present-day communications systems carrying distinctive traffic types with specific quality of service (QoS) requirements, whose fulfillment may elevate users´ quality of Experience (QoE). This paper investigates the QoE of users running real-life real-time and delay-tolerant applications by implementing an Internet-connected real-world mobile network which hosts a node with a centralized convex resource allocation optimization algorithm to calculate and enforce an optimal bandwidth distribution. The experiments show that leveraging the rate assignment approach escalates the real-life network traffic QoE through a fine-grained temporal resource allocation pattern which plummets the total bandwidth consumption and the cost of employing the services.