This article discusses latency-driven parallel task data offloading in fog computing networks for industrial applications. Fog computing brings cloud computing capabilities to the edge of networks to help support latency-sensitive industrial IoT applications. However, limited resources at fog nodes mean tasks are sometimes offloaded to neighboring fog nodes or the remote cloud for additional resources, which can increase latency. The article formulates an optimization problem to jointly determine how much of tasks to offload to neighboring fog nodes versus the remote cloud while meeting latency deadlines, considering transmission delays and service rates. It solves the problem using semidefinite relaxation to demonstrate effectiveness under different simulation settings.

Latency-Driven Parallel Task Data Offloading in Fog Computing Networks For Industrial Applications PDF

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