Event-Selective Fog Microbatching for Wireless Sensor IoT
Devices: A Data-Driven Study Using Edge-IIoTset Features
Raden Aur Aachman Azakiyullah1,∗ Aiswan Aumanti2
1 Faculty of Science, Engineering and Technology, Department of Information System, Universitas Alma Ata, Yogyakarta, Indonesia
2 Institut Bakti Nusantara, Lampung, Indonesia
Emails: nurrachmandzakiyullah@almaata.ac.id · mgumanti0205@gmail.com
Received: February 22, 2026 Revised: April 02, 2026 Accepted: May 05, 2026 ⋆ Corresponding author
ABSTRACT
Wireless sensor IoT devices increasingly operate under strict energy, latency, and security constraints while generating
high-frequency telemetry that cannot be forwarded continuously to remote clouds. This paper presents
an event-selective fog microbatching model for wireless sensor streams in which local novelty scoring, fog-side
buffering, risk-preserving retention, and energy-aware scheduling are jointly optimized. Unlike conventional
anomaly-detection pipelines, the proposed method treats communication reduction as a primary design objective
and binds it mathematically to attack-evidence preservation. A reduced feature-level experimental file following the
public Edge-IIoTset label structure and selected network/sensor attributes is used to evaluate traffic selectivity, uplink
reduction, fog latency, energy saving, and detection performance. The model assigns each observation window a
novelty score, suppresses redundant low-information traffic, and groups retained events into load-aware microbatches
at the nearest fog node. The proposed model is extended with stochastic retention bounds, microbatch-delay stability,
radio-energy equations, and risk-constrained threshold calibration. Experimental results show that the design reduces
uplink load and radio-energy consumption while preserving strong attack discrimination across distributed wireless
sensor traffic. The findings support a broader use of fog computing as a selective communication-control layer for
dense, security-sensitive wireless sensor IoT deployments.
Keywords: Wireless sensor IoT Fog computing Event-selective transmission Microbatching Edge-IIoTset
Anomaly-aware scheduling