Simulation study demonstrates lower operational costs and energy consumption in low Earth orbit satellite edge computing networks, highlighting viable efficiency gains for orbital data processing.
In view of the future of the Internet of Things (IoT), the number of edge devices and the amount of sensing data and communication data are expected to increase exponentially. With the emergence of new computing-intensive tasks and delay-sensitive application scenarios, terminal devices need to offload new business computing tasks to the cloud for processing. This paper proposes a joint transmission and offloading task scheduling strategy for the edge computing-enabled low Earth orbit satellite networks, aiming to minimize system costs. The proposed system model incorporates both data service transmission and computational task scheduling, which is framed as a long-term cost function minimization problem with constraints. The simulation results demonstrate that the proposed strategy can significantly reduce the average system cost, queue length, energy consumption, and task completion rate, compared to baseline strategies, thus highlighting the strategy’s effectiveness and efficiency.
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Li et al. (2025) studied this question.
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