Cost-Effective Hybrid Computation Offloading in Satellite-Terrestrial Integrated Networks

The Internet of Things (IoT) ecosystem is undergoing a significant evolution through its integration with satellite networks, empowering remote and computation-intensive IoT tasks to leverage computing services via satellite links. Current research in this field predominantly focuses on minimizing latency and energy consumption in computation offloading, yet overlooks the substantial costs incurred by satellite resource utilization. To address this oversight, we introduce a cost-effective hybrid computation offloading (CE-HCO) paradigm in satellite-terrestrial integrated networks (STINs) in this article. First, we propose the 5G-based system framework facilitates gNB and user plane function functionalities on satellites and fosters collaboration between public cloud providers and satellite operators. The framework is in line with the latest 3GPP activities and business models in satellite computing. Then, we formulate the CE-HCO problem, aiming to minimize total computation offloading costs while satisfying diverse user latency requirements and adhering to satellite energy constraints. To tackle this NP-hard problem, we develop an algorithm employing the penalty method and successive convex approximation to simplify the complex mixed-integer nonlinear programming into tractable convex iterations. Simulation results show that our approach outperforms existing baselines in balancing performance and cost, and offer guidance on pricing policies for satellite computing services to promote future commercial growth.