Joint Service Placement and Container Retention for Serverless-Based Vehicular Edge Computing

Lightweight containers in serverless-based vehicular edge computing (SVEC) offer flexible service provisioning for edge service providers (ESPs), enabling quick response to various service requests from mobile vehicles and improving the quality of service delivery. However, the unpredictability of vehicle mobility and the variability of service requests pose significant challenges to service placement for ESPs. Moreover, the cold-start latency experienced by service containers in SVEC can greatly hinder the responsiveness of vehicle services. To mitigate this impact and enhance the overall system performance, container retention is introduced as a solution. In this paper, we study the joint service placement and container retention problem in the dynamic SVEC system. First, we model the joint decision problem with specific constraints and aim to maximize the profit of each edge considering vehicle mobility. Second, an online co-decision scheme called CMU-O is proposed to solve the problem, which adopts an improved upper confidence bound method based on dynamic osmotic pressure (UCB-OP). Finally, the experimental results demonstrate that the service request success rate of the CMU-O is on average 7% higher than the baselines. Furthermore, the profits obtained under the CMU-O are also on average 23% higher than the baselines.