Joint Optimization of Computational Tasks Offloading for Efficient and Secure Manufacturing Through Cloud-Fog-Edge-Terminal Architecture

Within the realm of smart manufacturing, the growing complexity and scale of computational tasks expose the limitations of conventional computing architectures with rigid task allocation and fragmented collaboration, which impede the efficiency and security of smart manufacturing systems. To address these challenges, this paper presents an innovative cloud-fog-edge-terminal collaborative strategy that provides an adaptive and comprehensive offloading solution for tasks with complex dependencies and large scale, thereby enhancing the seamless collaborative potential of hierarchical computing structures. Additionally, a joint optimization mathematical model for collaborative computational offloading is developed, aiming to minimize task offloading time and assess manufacturing risk. To refine the solution, an advanced multi-objective optimization algorithm is formulated to identify the optimal solutions. The effectiveness and practical applicability of the proposed method are substantiated through simulation experiments and empirical case studies, demonstrating a performance enhancement of 12–29% over other benchmarks. The joint optimization method effectively synchronizes cloud-fog-edge-terminal computing resources, realizing efficient and secure task offloading and execution in smart manufacturing scenarios.