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Group-Based Consensus Scheme for Sensor-Event Consistency in Industrial IoT Environments
Soowang Lee1, Seungbin Lee2, Jiyoon Kim1,2
1Department of AI Convergence Engineering, Gyeongsang National University, Jinju 52828, Republic of Korea.
Abstract:
Industrial IoT (Internet of Things) systems increasingly depend on sensor reports for monitoring, automation, and operational decisions. However, sensor faults or Byzantine behavior can produce inconsistent or missing reports. PBFT (practical Byzantine fault tolerance) can maintain consistent processing among replicas despite a bounded number of Byzantine faults. Its overhead grows when many factory sensors participate in one expanding consensus group. Processing complete sensor-event records also increases local computation as record size grows. This paper proposes independent PBFT groups using fixed-length SHA-256 sensor-event digests. Groups are formed according to production processes or sensor characteristics. Each group limits consensus participation, while digests keep consensus-command size fixed. Raspberry Pi experiments separated grouping benefits from digest-processing benefits. Fixed-size groups moderated aggregate replica-local computation growth across 10-100 logical sensors. Digest processing became more beneficial as original sensor-event records increased in size. A four-device deployment also maintained consensus under evaluated Byzantine backup and primary faults. These results indicate that the scheme can reduce PBFT processing burden in resource-constrained IIoT deployments.