Cooperative user association and resource allocation for task offloading in hybrid GEO-LEO satellite networks,International Journal of Satellite Communications and Networking

当前位置： X-MOL 学术 › Int. J. Satell. Commun. Netw. › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

Cooperative user association and resource allocation for task offloading in hybrid GEO-LEO satellite networks
International Journal of Satellite Communications and Networking ( IF 0.9 ) Pub Date : 2021-11-02 , DOI: 10.1002/sat.1436
Tao Leng _{1,

2} , Pengfei Duan _{1,

2} , Dongwei Hu ₃ , Gaofeng Cui _{1,

2,

3} , Weidong Wang _{1,

2}

Affiliation

Hybrid geosynchronous earth orbit (GEO) and low earth orbit (LEO) satellite networks play an important role in future satellite-assisted internet of things (S-IoT). However, the limited satellite on-board communication and computing resource poses a large challenge for the task offloading in the hybrid GEO-LEO satellite networks. In this paper, the problem of task offloading is formulated as a cooperative user association and resource allocation problem. To tackle the problem, we model it as a Markov decision process and decompose it into two sub-problems, which are sequential decisions for user association and resource allocation with fixed user association conditions. Deep reinforcement learning (DRL) is adopted to make sequential decisions to achieve long-term benefits, and convex optimization method is utilized to obtain optimal communication and computing resource allocation. Simulation results show that the proposed method is superior to other referred schemes.

中文翻译：

混合 GEO-LEO 卫星网络中任务卸载的协作用户关联和资源分配

混合地球同步地球轨道 (GEO) 和低地球轨道 (LEO) 卫星网络在未来的卫星辅助物联网 (S-IoT) 中发挥着重要作用。然而，有限的星载通信和计算资源对混合GEO-LEO卫星网络中的任务卸载提出了巨大挑战。在本文中，任务卸载问题被表述为一个协作的用户关联和资源分配问题。为了解决这个问题，我们将其建模为马尔可夫决策过程，并将其分解为两个子问题，即用户关联的顺序决策和具有固定用户关联条件的资源分配。采用深度强化学习 (DRL) 做出顺序决策以实现长期利益，并利用凸优化方法获得最优的通信和计算资源分配。仿真结果表明，该方法优于其他参考方案。

更新日期：2021-11-02

点击分享查看原文

点击收藏

阅读更多本刊最新论文本刊介绍/投稿指南11