Comparative QoS Analysis Between ITU-T Requirements and an Enhanced oneM2M Middleware: A Proof of Concept
TL;DR
An autonomic control architecture based on the Monitor-Analyze-Plan-Execute with Knowledge loop is integrated with a Random Forest classifier that predicts four discrete QoS operational states with 91.9% accuracy, making the compliance gap explicit and quantifiable.
Abstract
The rapid expansion of Internet of Things (IoT) devices requires middleware capable of handling heterogeneous traffic while satisfying strict Quality of Service (QoS) targets. ITU-T Recommendation Y.1541 defines well-established performance thresholds for IP networks; however, baseline oneM2M deployments frequently fail to meet these targets under mixed workloads. This paper evaluates the open-source OM2M platform against ITU-T Y.1541 using eight QoS metrics spanning application and network layers, making the compliance gap explicit and quantifiable. Under the default configuration, the platform achieved only 20% overall compliance. To close this gap, an autonomic control architecture based on the Monitor-Analyze-Plan-Execute with Knowledge (MAPE-K) loop is integrated with a Random Forest (RF) classifier that predicts four discrete QoS operational states with 91.9% accuracy. The optimized configuration improves ITU-T compliance from 20% to 60%, achieving latency reductions of 53 to 71%, jitter mitigation of 93 to 97%, and transaction failure rate decreases of 36 to 64%, all measured during steady-state operation. The paper identifies the mechanisms responsible for the remaining non-compliant metrics and proposes a cross-layer roadmap for achieving full ITU-T compliance.