Microservice-Aware Deployment and Swarm Intelligence Cooperative Routing in Vehicle Edge Computing

The integration of vehicle edge computing (VEC) and microservice architectures improves real-time data processing and computational optimization in the Internet of Vehicles. Specifically, in high-traffic areas, the dynamic deployment and request routing of microservices with complex data dependencies within vehicle clusters can effectively reduce the computational load on edge devices. However, existing research has primarily focused on efficiently utilizing vehicular resources, overlooking the dynamic nature of vehicular cluster networks and the additional communication costs arising from data dependencies between microservices. Therefore, we propose a joint service deployment and request routing problem for vehicle collaboration. We first design a vehicle-road collaborative service framework assisted by temporary vehicle workers, expanding available resources and coverage by deploying microservice instances on selected temporary vehicle nodes. Second, recognizing the dependency between service deployment and request routing, we propose a dual-timescale service-deployment and request-routing policy. On a long timescale, a microservice-aware deployment method optimizes request selection and response time. On a short timescale, we propose a decentralized, swarm intelligence-based collaborative request routing method that constructs a response threshold model through agent interaction, thereby enhancing the collaborative optimization capability of the system. Finally, experimental results using real datasets show that our method outperforms other approaches in reducing request response time when communication costs are taken into account.