aspg-20-4360-1791307680 20261006172800 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group International Journal of Wireless and Ad Hoc Communication IJWAC 2692-4056 2026 10 2 Arash Salehpour Department of Cybersecurity, Haliç University, Istanbul, Türkiye Tamara Zhukabayeva Eurasian National University, Kazakhstan Wireless sensor Internet of Things (IoT) devices increasingly generate time-sensitive traffic that cannot be efficiently inspected only in a remote cloud. Fog computing reduces the distance between sensing devices and decision logic, but fog nodes must jointly manage latency, queue pressure, wireless channel variability, energy use and security risk. This paper presents FogSense-TSA, a trust-aware and anomaly-aware scheduling model for wireless sensor IoT traffic in fog computing environments. The model integrates traffic intensity, wireless link behaviour, fog-resource state and temporal trust into a local decision process that determines whether a device-window should be accepted, quarantined at the fog layer or escalated to cloud inspection. The empirical analysis is conducted using a reduced analysis-ready file aligned with a recent public IoT device-identification and anomaly-detection setting. The proposed formulation introduces three algorithmic components: online trust-risk scheduling, load-aware fog placement and adaptive threshold calibration. Mathematical analysis is provided for evidence aggregation, trust stability, latency decomposition, energy cost, constrained placement and computational complexity. The results show that fog placement substantially reduces service latency relative to cloud-only routing while preserving high anomaly-discrimination capability. The strongest predictors are trust score, flow intensity, jitter, fog CPU load, payload entropy and queue pressure, indicating that fog-layer security should be coupled with wireless access and resource conditions rather than treated as a separate classifier. The study provides a reproducible and interpretable basis for designing lightweight security and scheduling modules for wireless sensor IoT deployments. 2026 11 17 4360 https://creativecommons.org/licenses/by/4.0/ 10.54216/IJWAC.100202 https://americaspg.com/journal/20/article/4360 https://americaspg.com/storage/articles/manuscripts/01M20SZC2X580QPCD9E3FQ3MK2.pdf