Minimization of Task Offloading Latency for COVID-19 IoT Devices

The tasks offloaded by COVID-19 IoT (Internet of Things) devices are very important when they are new. Therefore, latency is a significant problem in time-sensitive IoT applications. On the other hand, wireless sensor devices are better suited for computationally intensive applications based in urban environments. However, these wireless sensor devices are limited in energy. In this paper, we consider an Edge Computing scenario consisting of two subsets of users: COVID-19 devices and sensor devices, while they use Multi-access Edge Computing (MEC) for computation offloading (CO). Network slicing seeks to suit their diverse needs, whereas the deployment of an edge server seeks to achieve reduced communication latency under the orthogonal multiple access (OMA) approach. Then, an optimization problem is built to reduce the MEC offloading latency for COVID-19 IoT devices subject to the energy consumption requirement of sensor devices. The numerical results show that our proposed method for task offloading on COVID-19 devices has much lower latency than other proposals.