Data scheduling and resource allocation in LEO satellite networks for IoT task offloading

With the development of the Internet of Things (IoT), mobile edge computing based on Low Earth Orbit (LEO) satellites has attracted extensive attention. LEO satellites can break through the geographical restrictions, which have wide coverage and flexible deployment. They are the choice of future mobile communications. In this article, we consider the three-tier architecture of LEO satellites, relay nodes, and IoT devices with sensors. In this architecture, the IoT devices can choose devices with better communication conditions or base stations as relay nodes to assist task and data scheduling, which can effectively reduce system energy consumption and delay in the process of task and data scheduling. Moreover, we study computational resource allocation strategies and data scheduling strategies to minimize system energy consumption. Based on Lyapunov technology, we transform the problem into three sub-problems, namely local scheduling, data scheduling from IoT devices to relay devices and data scheduling from relay devices to LEO satellite. To solve three sub-problems, we design the sensory data scheduling algorithm (SDSA). Finally, we carry out simulation experiments to verify the performance of the algorithm.