Service Anycast Forwarding for Software Defined Computing Power Network

With the rise of the computing power network (CPN), which integrate edge computing, cloud computing, and network infrastructure, replicated computing services are increasingly distributed to meet user demands for location-independent, reliable, and low latency services. Service anycast forwarding coordinates distributed service instances by binding them to a unified identifier and dynamically routing requests to the optimal instance. However, challenges such as varying user demand distribution, network complexity, and service instance heterogeneity complicate balanced service forwarding. To address these, we propose an SDN-based service anycast forwarding mechanism for CPN (SA-CPN). In the data plane, a cyclic forwarding queue efficiently maps weighted strategies and selects instances for each service request, improving policy performance. In the control plane, an optimal transport model balances network and computation latency based on service instance capabilities. We further design an optimal transport-based service anycast forwarding algorithm (OTSAF) using Sinkhorn iterations. Our implementation of SA-CPN in a real system shows that OTSAF consistently outperforms four baseline methods across various performance metrics.