ArticleScientific reports2025
MC-LBTO: secure and resilient state-aware multi-controller framework with adaptive load balancing for SD-IoT performance optimization.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rapid expansion of the Internet of Things (IoT) has intensified demands for scalable traffic management, real-time visibility, and resilient control in large, heterogeneous networks. Conventional Software-Defined Networking (SDN) architectures, typically based on centralized control and static forwarding, struggle to address the dynamic, data-intensive behavior of Software-Defined IoT (SD-IoT) systems. To overcome these limitations, this paper proposes MC-LBTO, a modular multi-controller framework that integrates programmable data plane intelligence with adaptive, secure coordination among distributed controllers to optimize load balancing and network efficiency. MC-LBTO comprises three cooperative modules: PDSM (P4-enabled Dynamic State Monitoring) for in-switch traffic observation and analytics; PALB (P4-based Adaptive Load Balancer) for latency-aware and fair traffic distribution; and STAM (Secure Trusted Adaptive Multi-Control) for consistent, fault-tolerant inter-controller operation. Experimental evaluations demonstrate that PDSM reduces controller CPU utilization by 35.7%, enhances flow-state detection accuracy to 98.3%, and lowers monitoring latency by 22.6% compared with OpenFlow-based monitoring. PALB achieves a 36% reduction in request latency, a 25% throughput increase, and a load distribution variance of only 5.5%, outperforming both traditional and modern probabilistic baselines. STAM enhances control-plane robustness with a Mean Time to Recovery (MTTR) of 75 ms, a 70% reduction in packet loss, and state consistency and security indices (SCI/SLI ≥ 9) under failure conditions. Collectively, these results confirm that MC-LBTO enables a scalable, secure, and self-adaptive SD-IoT architecture that maintains low overhead, balanced resource utilization, and fast recovery, offering a technically grounded framework for dependable and high-performance IoT networking.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.