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QoTa-MPR: QoS-oriented and traffic-aware multi-path routing protocol for internet of remote things


Internet of Remote Things (IoRT) is widely used in both military and civilian applications. However, due to the unique characteristics, which is characterized as long-distance and high-latency, the design of the routing protocol is a great challenge of IoRT. In this paper, a QoS-oriented and traffic-aware multi-path routing protocol (QoTa-MRP) is proposed for IoRT. QoTa-MRP is composed of two parts. The first part is the link traffic-aware based muti-paths source route discovery mechanism, which is used to establish multi-paths with lower link disjoint degree. The second part is path similarity and traffic priority based multi-path selection mechanism, which is used to determine the transmission mode of the traffic flows to enhance the reliability or effectiveness of the transmission. Simultaneously, the protocol is theoretically analyzed in terms of the successful transmission rate of routing transmission data packet. Finally, the dynamic source routing, which is a very representative protocol and is usually used as the baseline comparison protocol, is revisited for the performance verification of the QoTa-MRP in IoRT. It is shown in the simulation results that there are significant superiorities of QoTa-MRP than that of DSR in terms of network throughput, packet loss rate and routing packet header overhead in IoRT .

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  1. Lin, J., Yu, W., Zhang, N., et al. (2017). A survey on internet of things: Architecture. Enabling Technologies, Security and Privacy, and Applications, IEEE Internet Things J., 4(5), 1125–1142.

    Article  Google Scholar 

  2. Zhang, M., & Li, X. (2020). Drone-enabled internet-of-things relay for environmental monitoring in remote areas without public networks. IEEE Internet Things Journal, 7(8), 7648–7662.

    Article  Google Scholar 

  3. Zhen, L., Bashir, A. K., Yu, K., et al. (2020). Energy-efficient random access for LEO satellite-assisted 6G internet of remote things. IEEE Internet Things Journal.

    Article  Google Scholar 

  4. Gavrila, C., Popescu, V., Alexandru, M., et al. (2020). An SDR-based satellite gateway for internet of remote things (IoRT) applications. IEEE Access, 8, 115423–115436.

    Article  Google Scholar 

  5. Chen, K., Shen, H., & Yan, L. (2014). Multicent: A multifunctional incentive scheme adaptive to diverse performance objectives for DTN routing. IEEE Transactions on Parallel and Distributed Systems, 26(6), 1643–1653.

    Article  Google Scholar 

  6. Roy, A., Acharya, T., & DasBit, S. (2018). Quality of service in delay tolerant networks: A survey. Computer Networks, 130, 121–133.

    Article  Google Scholar 

  7. Shin, S., Lee, U., Dressler, F., et al. (2016). Motion-MiX DHT for wireless mobile networks. IEEE Transactions on Mobile Computing, 15(12), 3100–3113.

    Article  Google Scholar 

  8. Liu, J., Shi, Y., Fadlullah, Z. M., et al. (2018). Space-air-ground integrated network: A survey. IEEE Communications Survey and Tutorials, 20(4), 2714–2741.

    Article  Google Scholar 

  9. Clark, S. M., Hoback, K. A., Zogg, S. J. F.(2010). Statistical priority-based multiple access system and method, U.S. Patent 7680077.

  10. Jia, Z., Sheng, M., Li, J., et al. (2020). LEO satellite-assisted UAV: joint trajectory and data collection for internet of remote things in 6G aerial access networks. IEEE Internet Things Journal.

    Article  Google Scholar 

  11. Varshney, S., and Kuma, R. (2018). Variants of LEACH Routing Protocol in WSN: A Comparative Analysis, 8th International Conference on Cloud Computing, Data Science & Engineering (Confluence), 11-12 January, Uttar Pradesh, India, IEEE, 199-204.

  12. Gunjan, P. Maheshwari and A. K. Sharma. (2018). Modified TEEN for Handling Inconsistent Cluster Size Problem in WSN. 2018 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), 22-24 March, Kalavakkam, India, IEEE, 1-6.

  13. Nehra, V., & Sharma Ajay, K. (2020). I-DEEC: Improved DEEC for blanket coverage in heterogeneous wireless sensor networks. Journal of Ambient Intelligence and Humanized Computing, 11, 3687–3698.

    Article  Google Scholar 

  14. Zenia, N. Z., Aseeri, M., & Ahmed, M. R. (2016). Energy-efficiency and reliability in MAC and routing protocols for underwater wireless sensor network: A survey. Journal of Network and Computing Applications, 71, 72–85.

    Article  Google Scholar 

  15. Ponnavaikko, P., Wilson, S. K., Stojanovic, M., Holliday, J., & Yassin, K. (2017). Delay-constrained energy optimization in high-latency sensor networks. IEEE Sensors Journal, 17(13), 4287–4298.

    Article  Google Scholar 

  16. Geng, X., Wang, Y., Feng, H., & Zhang, L. (2017). Lanepost: Lane-based optimal routing protocol for delay-tolerant maritime networks. China Communication, 14(2), 65–78.

    Article  Google Scholar 

  17. Arafat, M. Y., & Moh, S. (2018). Location-Aided delay tolerant routing protocol in UAV networks for post-disaster operation. IEEE Access, 6, 59891–59906.

    Article  Google Scholar 

  18. Qureshi, T. N., and Javaid, N.(2018). Enhanced Adaptive Geographic Opportunistic Routing with Interference Avoidance Assisted with Mobile Sinks for Underwater Wireless Sensor Network, 2018 International Conference on Frontiers of Information Technology (FIT), Islamabad, Pakistan, 367-372.

  19. Bujari, A., Palazzi, C. E., & Ronzani, D. (2018). A comparison of stateless position-based packet routing algorithms for FANETs. IEEE Transactions on Mobile Computing, 17(11), 2468–2482.

    Article  Google Scholar 

  20. Huang, H., Yin, H., Min, G., et al. (2018). Energy-aware dual-path geographic routing to bypass routing holes in wireless sensor networks. IEEE Transactions on Mobile Computing, 17(6), 1339–1352.

    Article  Google Scholar 

  21. Jin, W., Gu, R., & Ji, Y. (2019). Reward function learning for Q-learning-based geographic routing protocol. IEEE Communications Letters, 23(7), 1236–1239.

    Article  Google Scholar 

  22. Ibrar, M., Wang, L., Muntean, G. M., et al. (2020). IHSF: An intelligent solution for improved performance of reliable and time-sensitive flows in hybrid SDN-based FC IoT systems. IEEE Internet Things Journal, 8(5), 3130–3142.

    Article  Google Scholar 

  23. Dhurandher, S. K., Singh, J., and Obaidat, M. S. et al. (2020) Reinforcement Learning-Based Routing Protocol for Opportunistic Networks, 2020 IEEE International Conference on Communications (ICC), 7-11 June,Dublin, Ireland, IEEE, 1-6.

  24. Awais, M., Ali, I., Alghamdi, T. A., et al. (2020). Towards void hole alleviation: Enhanced geographic and opportunistic routing protocols in harsh underwater WSNs. IEEE Access, 8, 96592–96605.

    Article  Google Scholar 

  25. Toso, G., Masiero, R., Casari, P., et al. (2018). Revisiting source routing for underwater networking: The SUN protocol. IEEE Access, 6, 1525–1541.

    Article  Google Scholar 

  26. Luo, Q., & Wang, J. (2018). FRUDP: A reliable data transport protocol for aeronautical Ad Hoc networks. IEEE Journal on Selected Areas Communication, 36(2), 257–267.

    Article  Google Scholar 

  27. Tang, F., Zhang, H., & Yang, L. T. (2019). Multipath cooperative routing with efficient acknowledgement for LEO satellite networks. IEEE Transactions on Mobile Computing, 18(1), 179–192.

    Article  Google Scholar 

  28. Jung, S., Kim, K., & Roh, B. (2019). Load Balancing Algorithm for Multiple UAVs Relayed Tactical Ad Hoc Networks, 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC), Milwaukee (pp. 944–945). USA: WI.

  29. Pu, C. (2019). Stochastic Packet Forwarding Algorithm in Flying Ad Hoc Networks, IEEE Military Communications Conference (MILCOM), Norfolk (pp. 490–495). USA: VA.

  30. Tang, F.(2020). Dynamically Adaptive Cooperation Transmission among Satellite-Ground Integrated Networks, IEEE INFOCOM 2020 -IEEE Conference on Computer Communications, Toronto, ON, Canada, 1559-1568.

  31. Jiang, Z. Q., Liu, C. H., He, S. B., et al. (2018). A QoS routing strategy using fuzzy logic for NGEO satellite IP networks. Wireless Networks, 24(1), 295–307.

    Article  Google Scholar 

  32. Kim, H., Cho, J., & Cho, H. (2019). Topology-Aware Reinforcement Learning Routing Protocol in Underwater Wireless Sensor Networks, International Conference on Information and Communication Technology Convergence (ICTC) (pp. 124–126). Korea(South): Jeju Island.

  33. Pelekanakis, K., Petroccia, R., Fountzoulas, Y., et al. (2019). A simulation study for long-range underwater acoustic networks in the high North. IEEE Journal of Oceanic Engineering, 44(4), 850–864.

    Article  Google Scholar 

  34. Luo, Q., & Wang, J. (2017). Multiple QoS parameters-based routing for civil aeronautical ad hoc networks. IEEE Internet Things Journal, 4(3), 804–814.

    Article  Google Scholar 

  35. Pu, C. (2018). Jamming-resilient multipath routing protocol for flying ad hoc networks. IEEE Access, 6, 68472–68486.

    Article  Google Scholar 

  36. Faheem, M., Tuna, G., & Gungor, V. C. (2018). QERP: Quality-of-service (QoS) aware evolutionary routing protocol for underwater wireless sensor networks. IEEE Systems Journal, 12(3), 2066–2073.

    Article  Google Scholar 

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Correspondence to Qun Guo.

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The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work in this paper.


This work was supported in part by National Natural Science Foundations of China (Grant No. 61762079, 61662070 and 71961028), Key Science and Technology Development Foundation of Gansu (Grant No. 1604FKCA097 and 17YF1GA015), Key Research and Development Foundation of Gansu (Grant No. 20YF8GA048), Western Light Foundation of Chinese Academy of Sciences, Lanzhou Science and Technology Planning Projects (Grant No. 2017-4-101, 2018-01-58 and 2019-RC-114), Innovation Ability Promotion Project of Gansu Universities (Grant No. 2019B-038), Young Teachers’ Scientific Research Ability Promotion Fund of Northwest Normal University (Grant No. NWNU-LKQN2021-04), Open Project of Gansu Provincial Research Center for Conservation of Dunhang Cultural Heritage (Grant No. GDW2021ZD04) and Open Project for Gansu Key Laboratory of Cloud Computing (Grant No. 2021KLCCGP002).

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Ma, Z., Liu, Y., Guo, Q. et al. QoTa-MPR: QoS-oriented and traffic-aware multi-path routing protocol for internet of remote things. Telecommun Syst 78, 515–530 (2021).

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  • Internet of remote things
  • QoS-oriented
  • Traffic-aware
  • Multi-path routing