Computation-Driven Multipath Transmission: A Delay Minimization Approach Integrating Computing Capability and Bandwidth

Multipath cooperation technology alleviates transmission pressure by leveraging path diversity. However, in next-generation service-oriented environments with computation-intensive services, the limited computing capability of transmission paths can degrade end-to-end service quality, even when bandwidth is sufficient. This issue becomes more pronounced in dynamic mobile scenarios, where fluctuating link status and computational resources introduce new challenges in path selection. To address these challenges, we propose a novel path selection approach that jointly considers both network and computation constraints for computation-intensive services. First, we construct a computation-integrated multipath transmission framework to support real-time monitoring of both link-level computing capabilities and network conditions. Second, we introduce a packet structure embedding device identifiers and computing capability, enabling adaptive scheduling. Finally, we develop a computing capability-constrained delay-minimizing packet scheduler (C²-DMPS) to balance bandwidth and computational load, ensuring low-latency transmission for emerging service demands. The results demonstrate the critical role of computational capacity in maintaining service performance, especially under volatile network conditions, highlighting potential risks to service continuity in next-generation environments.