Toward Sustainable Micro-Level Fog-Federated Load Sharing in Internet of Vehicles

Abstract

Advancement of technology has enabled access to innovative applications for connected devices. To handle growing computation requirements, the backend cloud data centers become an inefficient solution due to the caused network overhead. This is generally alleviated using edge locations deployed to meet the increasing computing demands. This article proposes a micro-level fog unit deployment to facilitate delay-sensitive applications. To manage imbalanced workloads due to the traffic density, the framework established a fog federation acting as a consortium where underutilized resources are shared to provide service quality. Moreover, we implement a price-based workload balancing algorithm to limit offloading among fog units relative to other consortium members. The experimental results show a balanced offload rate compared to traditional algorithms. Moreover, other measures, such as queue length, end-to-end delay, and workload balancing, demonstrate performance gain under the federation. Overall, 72% energy reduction is achieved through the proposed technique in comparison with the traditional nonfederated model.