Predictive offloading in mobile-fog-cloud enabled cyber-manufacturing systems

Abstract

An industrial cyber-physical system (ICPS) integrates the physical processes, systems and networks with the computation resources to provide reliable and responsive computation services. A cyber-manufacturing system (CMS), which is generated from ICPS, poses significant challenges on reliability, accuracy and responsiveness of computation services for manufacturing decision making. In this paper, we focus on reliability and responsiveness. Due to the heterogeneities of the computation and communication capacities and conditions, demanding computation services may not be completed in a timely manner. To facilitate reliable and responsive computation services, we propose a deadline constrained predictive offloading method based on a mobile-fog-cloud (MFC) network. This method optimizes the offloading decisions by solving a quadratically constrained integer linear programming constrained by latency requirements and predicted availability of devices. A newly constructed hybrid cyber-additive manufacturing network is used to test the performance of the proposed predictive offloading method and the MFC network. The results show that the proposed method outperforms mobile computing, fog computing, cloud computing, and fog-cloud computing benchmarks to minimize resource consumption and comply with latency requirements.