Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
169 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Security-Sensitive Task Offloading in Integrated Satellite-Terrestrial Networks (2404.15278v1)

Published 20 Jan 2024 in eess.SP, cs.CR, and cs.NI

Abstract: 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 \textit{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 \textit{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.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (39)
  1. Z. Zhang, W. Zhang, and F.-H. Tseng, “Satellite mobile edge computing: Improving qos of high-speed satellite-terrestrial networks using edge computing techniques,” IEEE Network, vol. 33, no. 1, pp. 70–76, 2019.
  2. J. P. Choi and C. Joo, “Challenges for efficient and seamless space-terrestrial heterogeneous networks,” IEEE Communications Magazine, vol. 53, no. 5, pp. 156–162, 2015.
  3. X. You, C.-X. Wang, J. Huang, X. Gao, Z. Zhang, M. Wang, Y. Huang, C. Zhang, Y. Jiang, J. Wang et al., “Towards 6g wireless communication networks: Vision, enabling technologies, and new paradigm shifts,” Science China Information Sciences, vol. 64, pp. 1–74, 2021.
  4. M. Giordani and M. Zorzi, “Non-terrestrial networks in the 6g era: Challenges and opportunities,” IEEE Network, vol. 35, no. 2, pp. 244–251, 2020.
  5. S. Chen, S. Sun, and S. Kang, “System integration of terrestrial mobile communication and satellite communication—the trends, challenges and key technologies in b5g and 6g,” China Communications, vol. 17, no. 12, pp. 156–171, 2020.
  6. X. Zhu and C. Jiang, “Integrated satellite-terrestrial networks toward 6g: Architectures, applications, and challenges,” IEEE Internet of Things Journal, vol. 9, no. 1, pp. 437–461, 2021.
  7. N. Pachler, I. del Portillo, E. F. Crawley, and B. G. Cameron, “An updated comparison of four low earth orbit satellite constellation systems to provide global broadband,” in 2021 IEEE International Conference on Communications Workshops (ICC Workshops), 2021, pp. 1–7.
  8. J. Li, H. Lu, K. Xue, and Y. Zhang, “Temporal netgrid model-based dynamic routing in large-scale small satellite networks,” IEEE Transactions on Vehicular Technology, vol. 68, no. 6, pp. 6009–6021, 2019.
  9. B. Di, H. Zhang, L. Song, Y. Li, and G. Y. Li, “Ultra-dense leo: Integrating terrestrial-satellite networks into 5g and beyond for data offloading,” IEEE Transactions on Wireless Communications, vol. 18, no. 1, pp. 47–62, 2019.
  10. X. Cao, B. Yang, Y. Shen, C. Yuen, Y. Zhang, Z. Han, H. V. Poor, and L. Hanzo, “Edge-assisted multi-layer offloading optimization of leo satellite-terrestrial integrated networks,” IEEE Journal on Selected Areas in Communications, vol. 41, no. 2, pp. 381–398, 2023.
  11. D. Han, Q. Ye, H. Peng, W. Wu, H. Wu, W. Liao, and X. Shen, “Two-timescale learning-based task offloading for remote iot in integrated satellite–terrestrial networks,” IEEE Internet of Things Journal, vol. 10, no. 12, pp. 10 131–10 145, 2023.
  12. Y. Mao, C. You, J. Zhang, K. Huang, and K. B. Letaief, “A survey on mobile edge computing: The communication perspective,” IEEE Communications Surveys & Tutorials, vol. 19, no. 4, pp. 2322–2358, 2017.
  13. I. Ahmad, J. Suomalainen, P. Porambage, A. Gurtov, J. Huusko, and M. Höyhtyä, “Security of satellite-terrestrial communications: Challenges and potential solutions,” IEEE Access, vol. 10, pp. 96 038–96 052, 2022.
  14. X. Wang, Y. Han, V. C. M. Leung, D. Niyato, X. Yan, and X. Chen, “Convergence of edge computing and deep learning: A comprehensive survey,” IEEE Communications Surveys & Tutorials, vol. 22, no. 2, pp. 869–904, 2020.
  15. T. Chen, J. Liu, Q. Ye, W. Zhuang, W. Zhang, T. Huang, and Y. Liu, “Learning-based computation offloading for iort through ka/q-band satellite–terrestrial integrated networks,” IEEE Internet of Things Journal, vol. 9, no. 14, pp. 12 056–12 070, 2022.
  16. Q. Tang, Z. Fei, B. Li, and Z. Han, “Computation offloading in leo satellite networks with hybrid cloud and edge computing,” IEEE Internet of Things Journal, vol. 8, no. 11, pp. 9164–9176, 2021.
  17. F. Pervez, L. Zhao, and C. Yang, “Joint user association, power optimization and trajectory control in an integrated satellite-aerial-terrestrial network,” IEEE Transactions on Wireless Communications, vol. 21, no. 5, pp. 3279–3290, 2022.
  18. C. Zhou, W. Wu, H. He, P. Yang, F. Lyu, N. Cheng, and X. Shen, “Deep reinforcement learning for delay-oriented iot task scheduling in sagin,” IEEE Transactions on Wireless Communications, vol. 20, no. 2, pp. 911–925, 2021.
  19. F. Chai, Q. Zhang, H. Yao, X. Xin, R. Gao, and M. Guizani, “Joint multi-task offloading and resource allocation for mobile edge computing systems in satellite iot,” IEEE Transactions on Vehicular Technology, vol. 72, no. 6, pp. 7783–7795, 2023.
  20. G. Cui, P. Duan, L. Xu, and W. Wang, “Latency optimization for hybrid geo–leo satellite-assisted iot networks,” IEEE Internet of Things Journal, vol. 10, no. 7, pp. 6286–6297, 2023.
  21. C. Ding, J.-B. Wang, H. Zhang, M. Lin, and G. Y. Li, “Joint optimization of transmission and computation resources for satellite and high altitude platform assisted edge computing,” IEEE Transactions on Wireless Communications, vol. 21, no. 2, pp. 1362–1377, 2022.
  22. H. Zhang, R. Liu, A. Kaushik, and X. Gao, “Satellite edge computing with collaborative computation offloading: An intelligent deep deterministic policy gradient approach,” IEEE Internet of Things Journal, vol. 10, no. 10, pp. 9092–9107, 2023.
  23. P. Yue, J. An, J. Zhang, J. Ye, G. Pan, S. Wang, P. Xiao, and L. Hanzo, “Low earth orbit satellite security and reliability: Issues, solutions, and the road ahead,” IEEE Communications Surveys & Tutorials, vol. 25, no. 3, pp. 1604–1652, 2023.
  24. Z. Liu, J. Weng, J. Guo, J. Ma, F. Huang, H. Sun, and Y. Cheng, “Pptm: A privacy-preserving trust management scheme for emergency message dissemination in space–air–ground-integrated vehicular networks,” IEEE Internet of Things Journal, vol. 9, no. 8, pp. 5943–5956, 2022.
  25. C. Liao, K. Xu, H. Zhu, X. Xia, Q. Su, and N. Sha, “Secure transmission in satellite-uav integrated system against eavesdropping and jamming: A two-level stackelberg game model,” China Communications, vol. 19, no. 7, pp. 53–66, 2022.
  26. C. Li, X. Sun, and Z. Zhang, “Effective methods and performance analysis of a satellite network security mechanism based on blockchain technology,” IEEE Access, vol. 9, pp. 113 558–113 565, 2021.
  27. M. Lin, Q. Huang, T. de Cola, J.-B. Wang, J. Wang, M. Guizani, and J.-Y. Wang, “Integrated 5g-satellite networks: A perspective on physical layer reliability and security,” IEEE Wireless Communications, vol. 27, no. 6, pp. 152–159, 2020.
  28. J. Xiong, D. Ma, H. Zhao, and F. Gu, “Secure multicast communications in cognitive satellite-terrestrial networks,” IEEE Communications Letters, vol. 23, no. 4, pp. 632–635, 2019.
  29. F. Tang, C. Wen, L. Luo, M. Zhao, and N. Kato, “Blockchain-based trusted traffic offloading in space-air-ground integrated networks (sagin): A federated reinforcement learning approach,” IEEE Journal on Selected Areas in Communications, vol. 40, no. 12, pp. 3501–3516, 2022.
  30. H. Liao, Z. Wang, Z. Zhou, Y. Wang, H. Zhang, S. Mumtaz, and M. Guizani, “Blockchain and semi-distributed learning-based secure and low-latency computation offloading in space-air-ground-integrated power iot,” IEEE Journal of Selected Topics in Signal Processing, vol. 16, no. 3, pp. 381–394, 2022.
  31. S. Sthapit, S. Lakshminarayana, L. He, G. Epiphaniou, and C. Maple, “Reinforcement learning for security-aware computation offloading in satellite networks,” IEEE Internet of Things Journal, vol. 9, no. 14, pp. 12 351–12 363, 2022.
  32. H. Xiao, J. Zhao, J. Feng, L. Liu, Q. Pei, and W. Shi, “Joint optimization of security strength and resource allocation for computation offloading in vehicular edge computing,” IEEE Transactions on Wireless Communications, pp. 1–1, 2023.
  33. M. Haleem, C. Mathur, R. Chandramouli, and K. Subbalakshmi, “Opportunistic encryption: A trade-off between security and throughput in wireless networks,” IEEE Transactions on Dependable and Secure Computing, vol. 4, no. 4, pp. 313–324, 2007.
  34. Z. Liao, J. Peng, J. Huang, J. Wang, J. Wang, P. K. Sharma, and U. Ghosh, “Distributed probabilistic offloading in edge computing for 6g-enabled massive internet of things,” IEEE Internet of Things Journal, vol. 8, no. 7, pp. 5298–5308, 2021.
  35. A. A. Al-Habob, A. Ibrahim, O. A. Dobre, and A. G. Armada, “Collision-free sequential task offloading for mobile edge computing,” IEEE Communications Letters, vol. 24, no. 1, pp. 71–75, 2020.
  36. M. Tong, X. Wang, S. Li, and L. Peng, “Joint offloading decision and resource allocation in mobile edge computing-enabled satellite-terrestrial network,” Symmetry, vol. 14, no. 3, 2022.
  37. M. Hua, Y. Wang, M. Lin, C. Li, Y. Huang, and L. Yang, “Joint comp transmission for uav-aided cognitive satellite terrestrial networks,” IEEE Access, vol. 7, pp. 14 959–14 968, 2019.
  38. J. Liu and Q. Zhang, “Offloading schemes in mobile edge computing for ultra-reliable low latency communications,” IEEE Access, vol. 6, pp. 12 825–12 837, 2018.
  39. J. Schulman, F. Wolski, P. Dhariwal, A. Radford, and O. Klimov, “Proximal policy optimization algorithms,” arXiv preprint arXiv:1707.06347, 2017.
Citations (1)
View on Semantic Scholar

Summary

We haven't generated a summary for this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Summarize Now
X Twitter Logo Streamline Icon: https://streamlinehq.com

Tweets