Cost optimization of cloud-edge-fog federated systems with bidirectional offloading: one-hop versus two-hop

Edge and fog computing technologies are akin to cloud computing but operate in closer proximity to users, offering similar services on a more widely distributed and localized scale. To enhance the computing environment and enable efficient offloading of computing requests, we propose a unified federation of these technologies, forming a federated cloud-edge-fog (CEF) system. Unlike current offloading models limited to single-hop and unidirectional vertical scenarios, our model facilitates two-hop, bidirectional (horizontal and vertical) offloading. The CEF model enables not only fog and edge devices to offload tasks to the cloud but also allows the cloud to offload tasks to the edges and fogs, creating a more dynamic and flexible computing ecosystem. To optimize this system, we formulate an optimization problem focused on minimizing the total cost while adhering to latency constraints. We employ simulated annealing as the solution approach. By adopting the proposed CEF model and optimization strategy, organizations can effectively leverage the strengths of cloud, edge, and fog computing while achieving significant cost reductions and improved task offloading efficiency. The findings from our study indicate that adopting a two-hop offloading approach can result in cost savings of 10–20% compared to the traditional one-hop method. Furthermore, when incorporating horizontal and bidirectional offloading, cost savings of approximately 12% and 20% can be achieved, respectively, in contrast to scenarios without horizontal offloading and only unidirectional vertical offloading. This advancement holds promise for optimizing computing resources and enhancing the overall performance of distributed systems in real-world applications.