A Trusted Resource Allocation Scheme in Fog Environment to Satisfy High Network Demand

Since the beginning of the century, the internet of things (IoT) and cloud computing have dominated industry and academic research by raising the standard of living. In order to meet the demanding expectations of end users, both technologies recently encountered significant challenges. During the pandemic, the entire world experiences unexpected developments that force millions of people to stay at home and rely on remote services to perform both their personal and professional tasks. The use of fog computing is expanding significantly in response to the growing demand for network services. Although the growth of fog nodes around edge devices may also introduce malicious activities that can impair regular service operations. Moreover, it becomes more difficult to select a fog node in a distributed fog environment that will offer facilities that are reliable and secure. As a result, we present a resource allocation mechanism in this study where a resource-constrained user node chooses a trusted fog device that is one hop distant to handle various application service requests. We also provide an overload detection technique for the fog network, which is based on the service deadline and fog node service arrival rate. A fog-to-fog offloading method is proposed in the event of overload to select the best suitable node for preserving service quality. However, the suggested approach significantly outperforms and is more effective than the current baseline offloading methodologies. Results show that with the proposed method, average latency, and energy consumption are reduced by 65.15% and 67.94%, respectively, whereas a total of 91.07% of tasks are executed successfully.