KFTO: Kuhn-Munkres based fair task offloading in fog networks

Abstract

In the fog network with multiple terminals and fog nodes, how to make a tradeoff between energy consumption fairness among fog nodes (FNs) and task processing delay of terminal nodes (TNs) is still a challenging problem. To solve this problem, this paper proposes a Kuhn-Munkres (KM) based Fair Task Offloading (KFTO) scheme, which includes two optimization models: FN selection model and task offloading decision model. FN selection model employs the KM algorithm to obtain the optimal matching scheme between TNs and FNs that maximizes the total network potential. The second model is used to obtain the task size offloaded to FN that minimizes the task processing delay of TN while satisfying the energy consumption constraint. Numerical simulation results reveal that the proposed KFTO scheme achieves a satisfactory tradeoff between the energy fairness among FNs and the task processing delay of TNs.