Stable Matching Assisted Resource Allocation in Fog Computing Based IoT Networks

Abstract

Future Internet of Things (IoT) will be a connected network of sensors enabling applications such as industrial automation and autonomous driving. To manage such a large number of applications, efficient computing techniques using fog nodes will be required. A major challenge in such IoT networks is to manage the resource allocation of fog computing nodes considering security and system efficiency. A secure selection of fog nodes will be needed for forwarding the tasks without interception by the eavesdropper and minimizing the task delay. However, challenges such as the secure selection of fog nodes for forwarding the tasks without interception by the eavesdropper and minimizing the task delay are critical in IoT-based fog computing. In this paper, an efficient technique is proposed that solves the formulated problem of allocation of the tasks to the fog node resources using a stable matching algorithm. The proposed technique develops preference profiles for both IoT and fog nodes based on factors such as delay and secrecy rate. Finally, Gale–Shapley matching is used for task offloading. Detailed simulation results show that the performance of the proposed technique is significantly higher than the recent techniques in the literature.