2026· EPJ Web of Conferences· 1 citation· 4 references
TL;DR
The proposed IoTScal-CoM middleware employs only native oneM2M capabilities such as RTT, packet loss rate, CPU, and memory usage in order to guarantee the SLA conformity without changing the main standard specifications.
Abstract
Recently, the Internet of Things (IoT) has expanded rapidly thanks to significant achievements in multiple fields. Each new device adds more data requests, demand, and network pressure [1]. Handling scale and QoS for IoT middleware platforms gets harder under high or irregular traffic loads. In most oneM2M-based middleware platforms, there are no external resource-usage mechanisms for overload conditions. Our new approach, IoTScal-CoM, presents a collaborative middleware architecture that enables QoS-based request redirection among independent oneM2M systems with the help of performance monitoring. In contrast to current techniques, the proposed solution employs only native oneM2M capabilities such as RTT, packet loss rate, CPU, and memory usage in order to guarantee the SLA conformity without changing the main standard specifications. The IoTScal-CoM middleware is deployed and tested in a simulated oneM2M environment by conducting a comparative analysis of both collaborative and non-collaborative scenarios. Experimental results demonstrate that the collaboration leads to increased stability and successful request processing as well as to improved system scalability.
The rapid proliferation of IoT devices and ecosystems creates significant challenges in managing increasing data traffic and service requests while maintaining system performance [1]– [3]. In oneM2M-based IoT systems, overloaded Common Service Entities (CSEs) can become bottlenecks, leading to resource saturation, higher latency, and request loss [4]. To address these challenges, this paper proposes IoTScal-2CoM-ALO, an adaptive load orchestration framework that introduces a two-level collaboration model (2CoM) enabling distributed CSEs to cooperate within and across domains. The framework incorporates an Adaptive Load Orchestration (ALO) mechanism that continuously monitors key performance indicators, including CPU utilization, memory consumption, round-trip time (RTT), and packet loss, to detect overload conditions and dynamically redirect traffic to suitable neighboring CSEs. The proposed approach is evaluated in a simulated distributed oneM2M environment under heterogeneous traffic conditions. Experimental results demonstrate significant performance improvements compared with non-collaborative and static collaboration approaches, achieving up to 73% reduction in memory consumption, RTT peak reductions of up to 4750 ms, and success rate improvements of approximately 4.8%. These results highlight the effectiveness of IoTScal-2CoM-ALO in improving resource utilization and maintaining service continuity in scalable IoT systems.
S. Abourriche, A. Zyane, A. Ghammaz· International Conference on...· 0 citations
In the last years, the Internet of Things (IoT) has become a key part of today’s digital infrastructure. From industrial automation to smart home devices, IoT systems connect physical sensors to cloud analytics and change how we interact with our environment. As these systems become larger and more complex, there is a growing need for communication methods that can manage unpredictable network errors, hardware limits, and frequent failures. Right now, MQTT and CoAP are the main protocols for IoT-to-cloud communication. But most systems use a fixed protocol, which makes it hard to adapt when problems like network traffic congestion or backend outages happen. In this paper, we introduce an adaptive edge gateway for ZigBee-based IoT networks that can switch between MQTT and CoAP as needed. The gateway monitors real-time performance, such as latency, packet loss, and backend availability, and chooses the best protocol and mode automatically. We tested our approach with in-depth simulations in ns-3, covering 180 scenarios including different types of failures, like link problems and broker outages. Our results show that adaptive switching improves packet delivery by 15–20% during faults in comparison to static setups and reduces recovery time without much extra overhead. This suggests that adapting protocols at the gateway is an effective way to make IoT systems more reliable.
Ali H. BenHusein, Mohamed Buker· Comprehensive Journal of Sci...· 0 citations
Distributed ledger technologies (DLT) can enhance trust and auditability in the Internet of Things (IoT). Among them, IOTA has been specifically designed to support machine-to-machine interactions and IoT data anchoring through scalable DLT architectures. However, their integration with Low-Power Wide-Area Networks (LPWANs) remains limited due to device constraints, strict timing requirements, and the operational costs of on-chain transactions. The transition from the fee-less Stardust to the fee-based IOTA Rebased model introduces explicit transaction costs, questioning the viability of continuous IoT data anchoring. IOTA provides a suitable platform to examine the challenges of integrating distributed ledger technologies with LPWAN-based IoT systems. Its transition to a fee-based execution model raises important questions regarding cost predictability and performance in continuous data anchoring scenarios, particularly under the constraints of resource-limited and latency-sensitive environments. This article investigates the practicality of the execution and payment model introduced by IOTA Rebased for IoT scenarios requiring continuous data notarization. We provide an empirical evaluation of continuous IoT data notarization on the public IOTA Rebased Mainnet and characterize the performance implications on edge-oriented deployments, including resource-constrained and resource-rich devices. We implement a notarization oracle that ingests LoRaWAN uplinks from The Things Network (TTN), canonicalizes payloads, generates SHA-256 commitments, and records them on-chain through reusable notarization objects. The oracle enables continuous anchoring of IoT telemetry while minimizing transaction overhead through object reuse. Two 24-h experimental campaigns compare a notarization oracle on resource-constrained and resource-rich hardware under periodic workloads. Results show consistent steady-state gas consumption for UPDATE operations, indicating that object reuse enables stable on-chain cost behavior in IOTA Rebased regardless of the deployment platform. From a performance perspective, both environments achieve stable execution; however, the resource-constrained edge deployment exhibits higher median and tail latency, alongside tighter memory margins compared to the resource-rich centralized baseline. These findings confirm the feasibility of deploying notarization services on constrained edge infrastructure under the new fee-based model.
Edison A. Arteaga López, G. R. Ramírez González, Andrea Sabbioni et al.· Annals of Telecommunications· 0 citations
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.
Jamal Et-Tousy, A. Zyane· EPJ Web of Conferences· 0 citations
The findings suggest that the modular API-driven architecture not only improves the flexibility and scalability of multi-device IoT integration but also maintains reliable data consistency and efficient communication performance.
A. M. Elhanafi, Dedy Irwan, Kissi Lola et al.· 0 citations
The exponential growth of the Internet of Things (IoT) applications is revealing critical limitations in current fifth generation networks (5G), especially with respect to scalability, latency, energy efficiency and intelligent resource management. These concerns make sixth-generation (6G) communication systems a near-future solution to facilitate intelligent, autonomous, and sustainable IoT ecosystems by amalgamating artificial intelligence (AI), terahertz (THz) communication, edge intelligence, semantic communication, and ultra-reliable low-latency communication (URLLC). But the research environment regarding 6G enabled IoT is still fragmented with the non-existence of a common analytical framework. In this paper, we present a structured survey and taxonomy based analytical framework for the 6G enabled IoT ecosystem. It classifies the recent works into enabling technologies, intelligent architectures, emerging applications, deployment challenges and future research directions. The requisite advancements in technologies needed for future IoT infrastructures are also highlighted through a comparison of 5G and 6G capabilities. The results of the analysis indicate that 6G can contribute to a substantial improvement of IoT performance in smart cities, healthcare, industrial automation and control applications (manufacturing science), autonomous transportation and precision agriculture. However, issues concerning cybersecurity, interoperability, sustainability, spectrum management and infrastructure cost still remain. This study is expected to enable the development of secure, scalable, intelligent and sustainable next-generation IoT systems based on collaborative edge computing.
Md Asaduzaman, Ferdous Hossain, T. K. Geok· International Journal of Ele...· 0 citations