Satellite-assisted internet of things (IoT) networks have emerged as a beacon of promise, offering global coverage and uninterrupted connectivity. However, the challenges of resource allocation and task offloading in such networks are intricate due to the unique characteristics of satellite communication systems. This research’s findings enrich the landscape of energy-efficient and dependable satellite-assisted IoT networks. The paper navigates the delicate balance between energy efficiency, network throughput, and fairness in distributing resources among IoT devices. The proposed techniques, notably the Outer Approximation Algorithm (OAA), usher in seamless connectivity and resource optimization. The central challenge at hand, a concave fractional programming problem, transforms through the Charnes–Cooper transformation, presenting as a concave optimization enigma. Herein, the proposed outer approximation algorithm takes flight, navigating the intricate paths of concave optimization. The performance of the epsilon-optimal solution faces scrutiny under diverse system parameters—the constellation of IoT devices, their affiliations, fairness considerations, and the equitable distribution of resource blocks. This contribution not only enriches research but also opens doors to the boundless possibilities of satellite-assisted IoT networks.

中文翻译：

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卫星协同：物联网网络中的资源分配和能源效率


卫星辅助物联网 (IoT) 网络已成为希望的灯塔，提供全球覆盖和不间断的连接。然而，由于卫星通信系统的独特特性，此类网络中资源分配和任务卸载的挑战非常复杂。这项研究的结果丰富了节能且可靠的卫星辅助物联网网络的前景。该论文探讨了能源效率、网络吞吐量和物联网设备之间资源分配公平性之间的微妙平衡。所提出的技术，特别是外部近似算法（OAA），带来了无缝连接和资源优化。当前的核心挑战是凹分数规划问题，通过 Charnes-Cooper 变换进行转换，呈现为凹优化之谜。在此，所提出的外近似算法开始飞行，导航凹优化的复杂路径。 epsilon 最优解决方案的性能面临着不同系统参数下的审查——物联网设备群、它们的从属关系、公平性考虑以及资源块的公平分配。这一贡献不仅丰富了研究，还为卫星辅助物联网网络的无限可能性打开了大门。