HRAS: Hybrid Resource Allocation System for Large-Scale Disasters

With the advancement of health care and technology, establishing a highly fast, accurate, and efficient medical system has been an ultimate goal for a country or a government. When a large-scale disaster with dozens of patients or more occurs, it often results in short supply of immediate medical resources to the patients, such as long waiting time for ambulances that causes a patient's death. In this paper, we establish a hybrid resource allocation system to model the problem as a hard real-time problem, and analyze two current scheduling algorithms for real-time system, namely clock driven (e.g. hospital assignment for emergency patients, HAEP) and priority driven (e.g. earliest deadline first, EDF). We further design a medical resource allocation algorithm which aims to reduce the computing time of the system and improve the accuracy of the allocation of medical resources. By making it suitable for large-scale disaster, it is hoped to be adopted by the disaster relief personnel and the government.