Minimal channel cost‐based energy‐efficient resource allocation algorithm for task offloading under FoG computing environment

Abstract

SummaryThe Internet of Things (IoT) and fog computing (FC) can be integrated to manage massive data processing and complex networks. It can improve communication performance and provide robust computation for resource‐constrained IoT devices by deploying more fog nodes (FNs) at the edge/IoT networks. In this article, the optimal energy‐efficient fog resource allocation (oEeFRA) algorithm is proposed with the help of the minimal channel cost resource allocation (MiCCRA) method to ensure the load balancing and task offloading of the IoT‐FoG network under various constraints. Resource blocks (RBs) should be maintained higher than FNs in this proposed model to enhance the task‐offloading processes. The MiCCRA algorithm is proposed to provide a minimum of one FN and RB for each IoT device used in the IoT‐FoG network and also to ensure that weather each FN should be allotted with one or more RBs and IoT devices for efficient task offloading and load balancing activities. The energy efficiency (EE) of the proposed oEeFRA algorithm is computed through the MiCCRA algorithm by varying RB, FN, and IoT devices. The performance analysis shows that the proposed algorithm achieved the maximum EE of 6.12 × 109 bit/J, 3.019 × 1010 bit/J, and 5.69 × 1010 bit/J for varying RBs, FNs, and IoTs.