Uploaded June 2026 | Updated September 2026, 3 weeks ago
NSDI '26 - Enabling SLO-Aware 5G Multi-Access Edge Computing with SMEC
Xiao Zhang and Daehyeok Kim, University of Texas at Austin
5G Multi-access edge computing (MEC) promises to enable latency-critical applications by bringing computational power closer to mobile devices, but our measurements on commercial MEC deployments reveal frequent SLO violations due to high tail latencies. We identify resource contention at the RAN and the edge server as the root cause, compounded by SLO-unaware schedulers. Existing SLO-aware MEC schedulers require RAN-edge coordination, making them impractical for deployment and prone to poor performance due to coordination delays, limited heterogeneous application support, and ignoring edge resource contention. This paper introduces MEC, a practical, SLO-aware resource management framework that facilitates deadline-aware scheduling through fully decoupled operations at the RAN and edge servers. Our key insight is that standard 5G protocols and application behaviors naturally provide information exploitable for SLO-aware management without extensive infrastructure or application changes. Evaluation on our 5G testbed shows that MEC achieves 90–96% SLO satisfaction versus under 6% for existing approaches, while reducing tail latency by up to 122×.
View the full NSDI '26 program at usenix.org/conference/nsdi26/technical-sessions
NSDI '26 - Enabling SLO-Aware 5G Multi-Access Edge Computing with SMEC
Xiao Zhang and Daehyeok Kim, University of Texas at Austin
5G Multi-access edge computing (MEC) promises to enable latency-critical applications by bringing computational power closer to mobile devices, but our measurements on commercial MEC deployments reveal frequent SLO violations due to high tail latencies. We identify resource contention at the RAN and the edge server as the root cause, compounded by SLO-unaware schedulers. Existing SLO-aware MEC schedulers require RAN-edge coordination, making them impractical for deployment and prone to poor performance due to coordination delays, limited heterogeneous application support, and ignoring edge resource contention. This paper introduces MEC, a practical, SLO-aware resource management framework that facilitates deadline-aware scheduling through fully decoupled operations at the RAN and edge servers. Our key insight is that standard 5G protocols and application behaviors naturally provide information exploitable for SLO-aware management without extensive infrastructure or application changes. Evaluation on our 5G testbed shows that MEC achieves 90–96% SLO satisfaction versus under 6% for existing approaches, while reducing tail latency by up to 122×.
View the full NSDI '26 program at usenix.org/conference/nsdi26/technical-sessions
