auction algorithm

A modern architecture called fog computing is used in IoT-based network systems. Providing data services is economical and low latent in fog computing architecture. This paper addresses the main challenge of allocating computing resources in fog computing. Solving the resource allocation challenge leads to the increased profits, economic savings, and optimal use of the computing systems. In this survey, resource allocation has been improved by using the combined Nash equilibrium algorithm and the auction algorithm. In the proposed method, each player is assigned a specific matrix. Each player’s matrix includes fog nodes, data service subscribers, and data service operators. At each stage of the algorithm, each player generates the best strategy based on the strategy of the other players. The results show the superiority of fog node utility and data service operator utility in the proposed method compared with the Stackelberg game algorithm. The first comparison is based on the changes of subscribers in which the productivity of the node with 240 used subscribers in the proposed method is 6852.8 and it is 5510.2 in the Stackelberg method with the same conditions. The second comparison is based on the service rate of the resource control blocks (μ) in which the productivity of the data service operator with μ=4 in the proposed method is 1.35E + 07 and it is 1E + 7 in the Stackelberg method with the same conditions.