Computation Offloading and Wireless Resource Management for Healthcare Monitoring in Fog-Computing-Based Internet of Medical Things

During the COVID-19 pandemic, Internet of Medical Things (IoMT) has been playing an important role in controlling the development of the epidemic, including enabling doctors in different grade hospitals to make a diagnosis and treatment, isolating and care for confirmed and suspected cases promptly, and preventing infection of patients with the novel coronavirus. In this article, we investigate the minimization optimization problem for healthcare monitoring in fog computing-based IoMT (FogC-IoMT), which is nonlinear and nonconvex problem, by considering Quality-of-Service requirement, power limit, and wireless fronthaul constraint. In order to solve the problem effectively, three independent subproblems are decoupled, and the suboptimal low-complexity computation offloading and resource management scheme is proposed in FogC-IoMT. The simulation results reveal the effectiveness of the proposed optimization algorithm in terms of cost utility.

Automated summary

This article investigates the minimization optimization problem for healthcare monitoring in fog computing-based Internet of Medical Things (FogC-IoMT) and proposes a suboptimal low-complexity computation offloading and resource management scheme. Simulation results demonstrate the effectiveness of the proposed optimization algorithm in terms of cost utility.