Security-Sensitive Task Offloading in Integrated Satellite-Terrestrial Networks

被引:0
|
作者
Lan, Wenjun [1 ,2 ]
Chen, Kongyang [1 ,3 ]
Cao, Jiannong [4 ]
Li, Yikai [1 ]
Li, Ning [1 ]
Chen, Qi [1 ]
Sahni, Yuvraj [5 ]
机构
[1] Guangzhou Univ, Sch Artificial Intelligence, Guangzhou 510006, Peoples R China
[2] Univ Elect Sci & Technol China, Shenzhen Inst Adv Study, Shenzhen 518110, Peoples R China
[3] Pazhou Lab, Guangzhou 510330, Peoples R China
[4] Hong Kong Polytech Univ, Res Inst Artificial Intelligence Things RIAIoT, Dept Comp, Hong Kong 999077, Peoples R China
[5] Hong Kong Polytech Univ, Dept Bldg Environm & Energy Engn, Hong Kong 999077, Peoples R China
基金
中国国家自然科学基金;
关键词
Satellites; Low earth orbit satellites; Security; Optimization; Space-air-ground integrated networks; Resource management; Reliability; Energy consumption; Encryption; Edge computing; Integrated satellite-terrestrial networks; task offloading; information security; deep reinforcement learning; COMMUNICATION; OPTIMIZATION; 5G;
D O I
10.1109/TMC.2024.3489619
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the rapid development of sixth-generation (6G) communication technology, global communication networks are moving towards the goal of comprehensive and seamless coverage. In particular, low earth orbit (LEO) satellites have become a critical component of satellite communication networks. The emergence of LEO satellites has brought about new computational resources known as the LEO satellite edge, enabling ground users (GU) to offload computing tasks to the resource-rich LEO satellite edge. However, existing LEO satellite computational offloading solutions primarily focus on optimizing system performance, neglecting the potential issue of malicious satellite attacks during task offloading. In this paper, we propose the deployment of LEO satellite edge in an integrated satellite-terrestrial networks (ISTN) structure to support security-sensitive computing task offloading. We model the task allocation and offloading order problem as a joint optimization problem to minimize task offloading delay, energy consumption, and the number of attacks while satisfying reliability constraints. To achieve this objective, we model the task offloading process as a Markov decision process (MDP) and propose a security-sensitive task offloading strategy optimization algorithm based on proximal policy optimization (PPO). Experimental results demonstrate that our algorithm significantly outperforms other benchmark methods in terms of performance.
引用
收藏
页码:2220 / 2233
页数:14
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