An Emergency Resource Scheduling Model Based on Edge Computing

In recent years, more and more researches are focusing on the field of disaster emergency management, especially in emergency resource dispatching. In a disaster scenario, a control center needs to obtain a large amount of real-time information at the scene to make decisions timely and accurately. Traditional Cloud Computing has many shortcomings in terms of delay and bandwidth, and Edge Computing (EC) will be more suitable for this scenario. We apply EC to the emergency rescue to cope with the problem of latency needs. First, we propose an edge-based emergency rescue architecture that consists of three layers: Cloud Layer, Edge Layer, and Resource Layer. Based on this, we give a resource scheduling model that requires the collaboration of Cloud and Edge Layers. The Cloud Layer gives a partition for these tasks, and all sub-tasks are assigning to the edge servers to get a locally optimal solution. Finally, these solutions from different edge servers are summarized to the Cloud Layer to get a globally optimal solution. We compare our algorithm with CS-GA and VRP. The simulation results show that RSE has good performance in scheduling time and cost.