Multi-objective task offloading optimization in fog computing environment using INSCSA algorithm

The presence of limitations such as processing and energy in many of end devices has resulted in task offloading to other sources. To address these limitations, offloading can be performed in diverse environments such as fog or cloud. This article reviews the multi-objective optimization of task offloading, which is a crucial challenge in fog computing. First, a task offloading model is presented for the simultaneous optimization of response time, energy consumption, and cost criteria, while considering availability criteria. This model utilizes a virtual controller to monitor all three layers of IoT, Fog, and Cloud. In the following, a developed version of the multi-objective crow search algorithm called the Improved Non-Dominated Sorting Crow Search Algorithm (INSCSA) is presented. An advantage of this research, compared to previous works, is the investigation of the optimality of the whole system. Evaluations demonstrate that our method has achieved superior results compared to the other methods.