Adaptive mobile path-aware user allocation algorithm under edge computing environment

As a new model, edge computing can effectively solve the problem of insufficient computing power of nearby user equipment. Due to the complex situation in the real world, the location distribution of users in each time period is difficult to be predicted, and the area covered by an edge server equipped with limited resources will be difficult to carry an uneven and uneven number of users in each time period, resulting in users being unable to request services. In addition, unreasonable allocation strategies will reduce the capacity of users in the area and may cause waste of resources. In response to the above problems, an adaptive mobile path-aware user allocation algorithm was proposed. The user's location information and road network data were used to determine the user's travel status through an improved map matching method, and predict a future travel path of the user. Based on the user's expected path, an allocation strategy was proposed to ensure the longer stable connection and less connection loss due to exceeding the signal range by using the expected stay time of server range as the adaptation value. A method for adjusting the allocation strategy based on best-fit was proposed. Through migrating some users from fully loaded servers to nearby servers with free space, the total user capacity of the servers in the area was indirectly increased, and the idleness time of adjacent servers was reduced, thereby the resource utilization was improved. Comparative experiments based on real user trajectory data sets showed that the proposed algorithm was significantly better than existing algorithms in terms of user coverage and resource utilization. © 2021, Editorial Department of CIMS. All right reserved.