Digital Twins at the Edge: A High-Availability Framework for Resilient Data Processing in IoT Sensor Networks

The expansion of Internet-of-Things deployments at the network edge challenges service continuity, as single points of failure can interrupt critical data-processing pipelines. This paper introduces the Operational Digital Twin (ODT) —a live, state-synchronized standby system designed for node-level failover in resource-constrained edge environments. In contrast to Digital Twins designed for modeling and analysis, an ODT is designed for operational continuity, standing ready to assume control when the primary node fails. We instantiate this concept through a self-configuring, high-availability architecture that implements the ODT for node-level redundancy. To ground this new conceptual category empirically, we define and validate four measurable criteria for ODT fidelity—state fidelity, synchronization timeliness, behavioral mirroring, and failover validation—establishing a framework that extends beyond passive replication. The design adopts a primary–secondary model with automated node discovery, configuration mirroring, and Virtual IP-based failover. Fault-injection experiments demonstrate low failover latency, prompt service restoration, limited message loss during transitions, and minimal resource overhead. These findings demonstrate that the proposed Operational Digital Twin mechanism reduces single points of failure and provides a lightweight, cost-efficient approach to sustaining reliable data processing in distributed edge environments.