Edge–Cloud Collaborative Control Models for Large-Scale Industrial Internet of Things Systems
Keywords:
Industrial Internet of Things, Edge Computing, Cloud Orchestration, Systems Architecture, Cyber-Physical Systems, Socio-Technical Governance, Distributed Control.Abstract
The rapid proliferation of the Industrial Internet of Things (IIoT) has necessitated a fundamental shift in how control logic and data processing are distributed across global manufacturing and infrastructure networks. Traditional centralized cloud computing architectures increasingly fail to meet the stringent latency, reliability, and security requirements of mission-critical industrial operations. Conversely, purely localized edge solutions lack the computational breadth and cross-facility intelligence necessary for global optimization. This paper proposes and analyzes a robust Systems Architecture Framework for Edge–Cloud Collaborative Control (ECCC), designed to harmonize the strengths of decentralized responsiveness with centralized systemic intelligence. We explore the structural trade-offs inherent in partitioning control tasks, emphasizing the transition from rigid hierarchical automation to dynamic, software-defined infrastructures. The research provides a deep analytical investigation into the socio-technical implications of these models, focusing on governance, infrastructure resilience, and the sustainability of high-compute industrial environments. By examining the interplay between algorithmic fairness in resource allocation and the policy frameworks governing data sovereignty, this work offers a comprehensive roadmap for the deployment of scalable IIoT systems. We argue that the future of industrial autonomy lies not in the choice between edge or cloud, but in the sophisticated orchestration of both, supported by a governance layer that ensures operational robustness and societal alignment.
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