A drone-assisted method based on DPC clustering in MEC

With the development of Mobile Edge Computing (MEC), the placement of edge servers has become a hot issue in the current research. In Mobile Edge Computing, the access range of the edge server is limited, those mobile devices which are not in the range execute the tasks locally and can’t offload the task to the edge server. In order to solve this problem, we used a DCP-based mobile device classification algorithm assisted by drones. In this paper, drones can assign the task of mobile devices in its range and its range is larger than edge servers. First, we classify the mobile devices which are not in any server’s range by the DESCAN algorithm. The DPC algorithm can classify these devices through their location without knowing the number of kinds in advance. Then, the drones arrive at their nearby location and assign tasks to edge servers. Finally, compared with the other two situations where there are no drones without a classification algorithm and drones without a classification algorithm, the DPC algorithm assisted by drones has better performance in the task completion delay, the mobile device energy consumption and the server loading rate.