Efficient Throughput Allocation for Emergency Data Transmission in IoMT-Based Smart Hospitals

In recent years, the healthcare field has been boosted by the use of new technologies such as the Internet of Medical Things (IoMT), Artificial Intelligence, and Big Data. Furthermore, with the spread of the COVID-19 pandemic, the need for smart and remote healthcare services was greatly amplified leading to the accelerated adoption of digital health solutions. Nevertheless, with the increasing amount of data generated by IoMT devices, the network can undergo the problem of packet latency, packet loss, and congestion leading to delays in the transmission of data that may be urgent. Thus, it becomes essential to develop effective algorithms that can manage notifications’ flow based on their importance levels and delay tolerance. In this paper, we propose an effective algorithm to dynamically allocate the throughput in an IoMT-based smart hospital in response to data emergencies. The algorithm takes into account the criticality of the data and the available bandwidth to allocate the necessary throughput to IoMT devices to ensure that the critical data is transmitted without delay.