An ICN-Based Delay-Sensitive Service Scheduling Architecture with Stateful Programmable Data Plane for Computing Network

The Computing Network is an emerging paradigm that integrates network and computing resources. One of its goals is to satisfy the requirements of delay-sensitive services through network scheduling capabilities. However, traditional TCP/IP networks are deficient in accurately being aware of requirements and performing flexible routing based on service levels. Information-Centric Networking (ICN) addresses these issues through its flexible protocol design and content-based routing mechanism. Additionally, the integration of Software-Defined Networking (SDN) technology further enhances its routing flexibility. Therefore, this paper proposes an ICN-based delay-sensitive service scheduling architecture with an SDN stateful programmable data plane. The network nodes are first layered based on the type of computing clusters they are linked with, and then within each layer, they are divided into several domains according to delay constraints. Then, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) algorithm, combined with the Best-Worst Method (BWM) weighting method, is adopted to evaluate the candidate clusters, and the corresponding scheduling strategy is executed in the stateful programmable data plane. The simulation results show that compared with other scheduling architectures and traditional TOPSIS with the Entropy Weight Method (EWM), the proposed architecture and algorithm show significant advantages in reducing the overall delay of service requests and improving the scheduling success ratio, as well as the load balance of the computing clusters.