Service-driven dynamic QoS on-demand routing algorithm

With the proliferation of Internet of Things (IoT) devices, the scale of networks is growing exponentially. However, dynamically meeting the diverse quality of service (QoS) routing requirements for users and services in large-scale networks remains a critical challenge. To address this issue, this paper proposes a Service-Driven Dynamic QoS On-Demand model and establishes a corresponding QoS optimization objective function. The SHA-256 hash algorithm is utilized to simplify the large-scale network model, effectively reducing the number of Segment Routing (SR) nodes. The proposed Service-Driven Dynamic QoS On-Demand Routing Algorithm (SDDRL) identifies the optimal path, which is then uniformly disseminated by the SDN controller, thereby addressing existing challenges in SDN-IoT networks. Compared to OSPF-based and DDQN-based algorithms, the SDDRL algorithm reduces the average delay by 53.85% and 31.63%, respectively. The proposed algorithm reduces the packet loss rate, improves the average network congestion degree and route calculation time compared to other existing algorithms, and it demonstrates superior performance in handling complex tasks.