Research on the Checkpoint Server Selection Strategy Based on the Mobile Prediction in Autonomous Vehicular Cloud

Abstract

With the continuous development of wireless communication technology and the improvement in the performance of the vehicular device, the concept of Autonomous Vehicular Cloud (AVC) has emerged. Vehicular Cloud can provide abundant resources and services, but the high mobility of highway vehicle nodes leads to the network communication time is short, therefore allocated resources lost easily. This paper will focus on solving the problem of the low efficiency of the resource aggregation and distribution of the vehicle nodes in the highway scene. Based on the particularity of the Vehicular cloud in the highway, this paper introduces the checkpoint server selection mechanism which is based on mobility prediction and proposes two checkpoint server selection schemes, one is the choice of relative task initiating node stability of the vehicle node, the other is the choice of relative task executing node stability of the vehicle node. This paper uses OPNET Network simulation tool to evaluate the two schemes mentioned above based on various scenarios of different node density. Finally, the empirical conclusion is that the selected checkpoint based on mobility prediction methods is more stable, can improve the efficiency of resource aggregation and allocation, and vehicle node is more sparse, the enhanced effect is more obvious.