Abstract
It is a hot topic to investigate resource allocation in fog computing. However, currently resource allocation in fog computing mostly supports only fixed resources, that is, the resource requirements of users are satisfied with a fixed amount of resources during the usage time, which may result in low utility of resource providers and even cause a waste of resources. Therefore, we establish an integer programming model for the time-varying multidimensional resource allocation problem in fog computing to maximize the utility of the fog resource pool. We also design a heuristic algorithm to approximate the solution of the model. We apply a dominant-resource-based strategy for resource allocation to improve resource utilization as well as critical value theory for resource pricing to enhance the utility of the fog resource pool. We also prove that the algorithm satisfies truthful and individual rationality. Finally, we give some numerical examples to demonstrate the performance of the algorithm. Compared with existing studies, our approach can improve resource utilization and maximize the utility of the fog resource pool.