[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content

Advertisement

Springer Nature Link
Log in

Cooperative content offloading scheme in air-ocean integrated networks

  • Published:
Peer-to-Peer Networking and Applications Aims and scope Submit manuscript

Abstract

As one of the most promising networks, the air-ocean integrated networks (AOINs) composed of unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs) meet a variety of requests from different maritime missions with the characteristics of seamless, high-rate, and reliable transmission. However, due to the limited storage capacities of UAVs and uncertain navigation paths of USVs, it is challenging to accomplish the ocean observation mission. In this paper, a UAV and USV cooperative content offloading scheme in AOINs with Q-learning and game theory is proposed. Specifically, the state evaluation mechanism for both UAV and USV is first designed to make cooperation strategies. Afterward, the interaction between UAV and USV is modeled as the bargaining game, where the Nash equilibrium as the optimal transaction price is obtained by the backward induction method. To realize the maximization of revenue, we devise a Q-learning based algorithm to make path planning for each USV to offload contents as many as possible under the limited energy. Finally, the effectiveness and efficiency of the proposed scheme is conducted by extensive simulations.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Qu H, Luo Y, Zhao J, Luan Z (2020) An LBMRE-OLSR routing algorithm under the emergency scenarios in the Space-Air-Ground integrated networks. In: 2020 Information communication technologies conference (ICTC), Nanjing, China, pp 103– 107

  2. Qu H, Xu X, Zhao J, Yue P, An SDN-based space-air-ground integrated network architecture and controller deployment strategy (2020). In: 2020 IEEE 3rd international conference on computer and communication engineering technology (CCET), Beijing, China, pp 138–142

  3. Zhou C, et al. (2021) Deep reinforcement learning for delay-oriented IoT task scheduling in space-air-ground integrated network. IEEE Trans Wirel Commun 20(2):911–925

    Article  Google Scholar 

  4. Wu B, Xu Z (2017) Research on integrated space-air-ground TTC and communication network based on space tracking ship. In: 2017 16th International conference on optical communications and networks (ICOCN). Wuzhen, pp 1–3

  5. Azari M M, Geraci G, Garcia-Rodriguez A, Pollin S (2020) UAV-to-UAV communications in cellular networks. IEEE Trans Wirel Commun 19(9):6130–6144

    Article  Google Scholar 

  6. Xu Q, Su Z, Dai M, Yu S (2020) APIS: privacy-preserving incentive for sensing task allocation in cloud and edge-cooperation mobile internet of things with SDN. IEEE Internet Things J 7(7):5892–5905

    Article  Google Scholar 

  7. Yang T, Jiang Z, Sun R, Cheng N, Feng H (2020) Maritime search and rescue based on group mobile computing for unmanned aerial vehicles and unmanned surface vehicles. IEEE Trans Ind Inform 16 (12):7700–7708

    Article  Google Scholar 

  8. Xu Q, Su Z, Lu R (2020) Game theory and reinforcement learning based secure edge caching in mobile social networks. IEEE Trans Inf Forensics Secur 15:3415–3429

    Article  Google Scholar 

  9. Guo H, Liu J (2020) UAV-enhanced intelligent offloading for internet of things at the edge. IEEE Trans Ind Inform 16(4):2737–2746

    Article  Google Scholar 

  10. Xu Q, Su Z, Yang Q (2020) Blockchain-based trustworthy edge caching scheme for mobile cyber-physical system. IEEE Internet Things J 7(2):1098–1110

    Article  Google Scholar 

  11. Liu X, Wang W, Yang B, Fan Y (2019) Incentive mechanism for data uploading in mobile crowdsensing. In: 2019 International conference on networking and network applications (NaNA). https://doi.org/10.1109/NaNA.2019.00074, pp 391–395

  12. Yin H, et al. (2020) A blockchain-based storage system with financial incentives for load-balancing. IEEE Trans Netw Sci Eng

  13. Yao P, Zhao R, Zhu Q (2020) A hierarchical architecture using biased min-consensus for USV path planning. IEEE Trans Veh Technol 69(9):9518–9527

    Article  Google Scholar 

  14. Xu Q, Su Z, Zhang K, Li P (2020) Intelligent cache pollution attacks detection for edge computing enabled mobile social networks. IEEE Trans Emerg Top Comput Intell 4(3):241–252

    Article  Google Scholar 

  15. Yi C, Cai J, Su Z (2020) A multi-user mobile computation offloading and transmission scheduling mechanism for delay-sensitive applications. IEEE Trans Mob Comput 1(1):29–43

    Article  Google Scholar 

  16. Sun W, Liu J, Yue Y, Wang P (2020) Joint resource allocation and incentive design for blockchain-based mobile edge computing. IEEE Trans Wirel Commun 1(9):6050–6064. https://doi.org/10.1109/TWC.2020.2999721

    Article  Google Scholar 

  17. Thi Le T H, Tran N H, Tun Y K, Tran Thi Kim O, Kim K, Hong C S (2020) Sharing incentive mechanism, Task assignment and resource allocation for task offloading in vehicular mobile edge computing. In: NOMS 2020 - 2020 IEEE/IFIP Network operations and management symposium, pp 1–8, DOI https://doi.org/10.1109/NOMS47738.2020.9110346, (to appear in print)

  18. Mao G, Zhang Z, Anderson B D O (2016) Cooperative content dissemination and offloading in heterogeneous mobile networks. IEEE Trans Veh Technol 65(8):6573–6587

    Article  Google Scholar 

  19. Ning Z, et al. (2021) Intelligent edge computing in internet of vehicles: a joint computation offloading and caching solution. IEEE Trans Intell Transp Syst 22(4):2212–2225. https://doi.org/10.1109/TITS.2020.2997832

    Article  Google Scholar 

  20. Bai T, Wang J, Ren Y, Hanzo L (2019) Energy-efficient computation offloading for secure UAV-edge-computing systems. IEEE Trans Veh Technol 68(6):6074–6087

    Article  Google Scholar 

  21. Yao H, Zeng D, Huang H, Guo S, Barnawi A, Stojmenovic I (2015) Opportunistic offloading of deadline-constrained bulk cellular traffic in vehicular DTNs. IEEE Trans Comput 1(12):3515–3527

    Article  MathSciNet  Google Scholar 

  22. Wang Y, Wang K, Huang H, Miyazaki T, Guo S (2019) Traffic and computation co-offloading with reinforcement learning in fog computing for industrial applications. IEEE Trans Ind Inform 15 (2):976–986

    Article  Google Scholar 

  23. Ning Z, et al. (2020) Intelligent edge computing in internet of vehicles: a joint computation offloading and caching solution. IEEE Trans Intell Transp Syst

  24. Liu M, Yu F R, Teng Y, Leung V C M, Song M (2018) Computation offloading and content caching in wireless blockchain networks with mobile edge computing. IEEE Trans Veh Technol 67(11):11008–11021

    Article  Google Scholar 

  25. Wang C, Liang C, Yu F R, Chen Q, Tang L (2017) Computation offloading and resource allocation in wireless cellular networks with mobile edge computing. IEEE Trans Wirel Commun 16(8):4924–4938

    Article  Google Scholar 

  26. Wu H, Liu L, Zhang X, Ma H (2016) Quality of video oriented pricing incentive for mobile video offloading. In: IEEE INFOCOM 2016—the 35th annual IEEE international conference on computer communications. San Francisco, pp 1–9

  27. Chen H, Lou W, Wang Z, Wang Q (2016) A secure credit-based incentive mechanism for message forwarding in noncooperative DTNs. IEEE Trans Veh Technol 65(8):6377–6388

    Article  Google Scholar 

  28. Chen K, Shen H, Yan L (2015) Multicent: a multifunctional incentive scheme adaptive to diverse performance objectives for DTN routing. IEEE Trans Parallel Distrib Syst 1(6):1643–1653

    Article  Google Scholar 

  29. He J, Wang H, Chu X, Zhang T (2019) Incentive mechanism and content provider selection for device-to-device-based content sharing. IEEE Trans Veh Technol 68(3):2946–2957

    Article  Google Scholar 

  30. Lai C, Zhang K, Cheng N, Li H, Shen X (2017) SIRC: a secure incentive scheme for reliable cooperative downloading in highway VANETs. IEEE Trans Intell Transp Syst 18(6):1559–1574

    Google Scholar 

  31. Kontoudis G P, Vamvoudakis K G (2019) Kinodynamic motion planning with continuous-time q-learning: an online, model-free, and safe navigation framework. IEEE Trans Neural Netw Learn Syst 30(12):3803–3817

    Article  MathSciNet  Google Scholar 

  32. Hu Y, Li D, He Y, Han J Incremental learning framework for autonomous robots based on q-learning and the adaptive kernel linear model. IEEE Trans Cogn Dev Syst. https://doi.org/10.1109/TCDS.2019.2962228

  33. Ou X, Chang Q, Chakraborty N (2021) A method integrating q-learning with approximate dynamic programming for gantry work cell scheduling. IEEE Trans Autom Sci Eng 18(1):85–93. https://doi.org/10.1109/TASE.2020.2984739

    Article  Google Scholar 

  34. Ebrahimi D, Sharafeddine S, Ho P, Assi C (2021) Autonomous UAV trajectory for localizing ground objects: a reinforcement learning approach. IEEE Trans Mob Comput 20(4):1312–1324. https://doi.org/10.1109/TMC.2020.2966989

    Article  Google Scholar 

  35. Kawamoto Y, Kamei T, Takahashi M, Kato N, Miura A, Toyoshima M (2020) Flexible resource allocation with inter-beam interference in satellite communication systems with a digital channelizer. IEEE Trans Wirel Commun 19(5):2934–2945

    Article  Google Scholar 

  36. Li X, Feng W, Chen Y, Wang C, Ge N (2020) Maritime coverage enhancement using UAVs coordinated with hybrid satellite-terrestrial networks. IEEE Trans Commun 68(4):2355–2369

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, 200444, People’s Republic of China

    Junjie Zhou, Zhou Su, Qichao Xu & Weiwei Chen

Authors
  1. Junjie Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhou Su
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Qichao Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Weiwei Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zhou Su.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article is part of the Topical Collection: Special Issue on Space-Air-Ground Integrated Networks for Future IoT: Architecture, Management, Service and Performance

Guest Editors: Feng Lyu, Wenchao Xu, Quan Yuan, and Katsuya Suto

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhou, J., Su, Z., Xu, Q. et al. Cooperative content offloading scheme in air-ocean integrated networks. Peer-to-Peer Netw. Appl. 14, 3388–3404 (2021). https://doi.org/10.1007/s12083-021-01160-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12083-021-01160-z

Keywords

Search

Navigation