Resource-sharing allocation method based on dwarf mongoose optimization algorithm in vehicle computing

In vehicle computing, the intelligent vehicle which has strong computing capability and abundant sensing devices provides services for users. Many sensing devices can provide services for users without the limits of time and place. Intelligent vehicles have large amount computing and sensing resources, where computing resources are used individually by users while sensing resources can be shared by multiple users. According to the characteristics of intelligent vehicles, a new resource allocation model based on resource sharing was proposed. A resource sharing allocation method based on dwarf mongoose optimization was proposed. A repairing algorithm was proposed to transform infeasible solutions into feasible solutions. A new solution generation algorithm based on the random and greedy strategy was proposed to address the problem of the dwarf mongoose optimization algorithm being prone to getting stuck in local optima, to improve the convergence speed and obtain the optimal solution. The experimental results show that the proposed strategy performs well in different allocation environments and is adaptable.