Optimal Admission Control Mechanism Design for Time-Sensitive Services in Edge Computing

Edge computing is a promising solution for reducing service latency by provisioning time-sensitive services directly from the network edge. However, upon workload peaks at the resource-limited edge, an edge service has to queue service requests, incurring high waiting time. Such quality of service (QoS) degradation ruins the reputation and reduces the long-term revenue of the service provider. To address this issue, we propose an admission control mechanism for time-sensitive edge services. Specifically, we allow the service provider to offer admission advice to arriving requests regarding whether to join for service or balk to seek alternatives. Our goal is twofold: maximizing revenue of the service provider and ensuring QoS if the provided admission advice is followed. To this end, we propose a threshold structure that estimates the highest length of the request queue. Leveraging such a threshold structure, we propose O2A, a mechanism to balance the trade-off between increasing revenue from accepting more requests and guaranteeing QoS by advising requests to balk. Rigorous analysis shows that O2A achieves the goal and that the provided admission advice is optimal for end-users to follow. We further validate O2A through trace-driven simulations with both synthetic and real-world service request traces.