Toward Sustainable Interconnected Metrological Networks: Synchronized Multi-Resource Coordination

Advances in low-power electronics and wireless communication have fueled the proliferation of interconnected metrological networks, increasing the need for traceable, networked measurement systems. This expansion, however, has created a surge in heterogeneous calibration tasks, while a scarcity of qualified experts and reference standards imposes severe resource constraints on remote calibration. Existing scheduling methods, though effective in homogeneous environments, typically lack integration of high-precision time-synchronization with heterogeneous resource coordination, limiting their use in time-critical metrology. To address this gap, we propose a multi-resource synchronized scheduling framework for remote calibration. We formulate the problem as a dual-container model that concurrently optimizes task mapping and temporal dependencies between edge instruments and cloud services. A two-stage heuristic algorithm is developed to efficiently map and schedule tasks in distributed client-server architectures by leveraging critical path analysis and hierarchical scheduling strategies. Simulations across diverse workloads and scales show our method outperforms existing baselines, achieving superior scheduling efficiency, scalability, and calibration accuracy.