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Congestion Aware Data Transmission in Mobile and Constrained IoT Network

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Abstract

The growth and adoption of Internet of Things (IoT) have been increasing at a rapid pace over the past few years. IoT is a network of huge number of connected devices which are mobile and constrained in nature. These IoT devices communicate and transmit data over the Internet. This huge amount of transmission causes congestion in the network, resulting in packet delivery delay and high packet loss. Handling the problem of congestion requires transmission of data effectively in a congestion-aware manner. This paper proposes an approach for congestion-aware data transmission in mobile and constrained IoT networks. In this study, we have performed hop-to-hop communication and the process of next hop selection considers the multiple parameters to make it congestion-aware and effective. The proposed method uses the Analytic Hierarchy Process (AHP) to perform multiparameter based decision making to pick the best suitable next hop. The proposed method is ideal for the environment where nodes have limited resources, high traffic and need timely delivery of data packets. The results are compared with state-of-the-art methods, and the performance of the proposed method was better in terms of throughput by 6%, packet delivery rate by 7.5%, and reduced average delay by 4% as well as buffer overflow condition by 2%.

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References

  1. https://www.edureka.co/blog/iot-applications.

  2. Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., & Ayyash, M. (2015). Internet of things: A survey on enabling technologies, protocols, and applications. IEEE Communications Surveys and Tutorials, 17(4), 2347–2376. https://doi.org/10.1109/COMST.2015.2444095

    Article  Google Scholar 

  3. Al-Kashoash, H. A., Kharrufa, H., Al-Nidawi, Y., & Kemp, A. H. (2019). Congestion control in wireless sensor and 6LoWPAN networks: Toward the Internet of Things. Wireless Networks, 25(8), 4493–4522.

    Article  Google Scholar 

  4. Maheshwari, A., & Yadav, R. K. (2020). Analysis of congestion control mechanism for iot. In 2020 10th international conference on cloud computing, data science & engineering (Confluence) (pp. 288–293). IEEE.

  5. Jain, V. K., Mazumdar, A. P., Faruki, P., & Govil, M. C. (2022). Congestion control in Internet of Things: Classification, challenges, and future directions. Sustainable Computing: Informatics and Systems, 35, 100678.

    Google Scholar 

  6. Alzahrani, & Salha, M. (2017). Sensing for the Internet of Things and its applications. In: 2017 5th international conference on future internet of things and cloud workshops (FiCloudW), (pp. 88–92).

  7. Yang, F., Shen, Y., & Cui, X. et al. (2018). Voltage sag severity assessment based on multi-objective decision analytic hierarchy process.

  8. Sun, H., Qiao, F., Wang, Z., & Guo, L. (2019). A two-level identification model for selecting the coordination strategy for the urban arterial road based on fuzzy logic. International Journal of Simulation and Process Modelling, 14(6), 478–487.

    Article  Google Scholar 

  9. Li, W., Ye, Y., Hu, N., Wang, X., & Wang, Q. (2019). Real-time warning and risk assessment of tailings dam disaster status based on dynamic hierarchy-grey relation analysis. Complexity, 2019(9), 1–14.

    Google Scholar 

  10. Kim, H. S., Kim, H., Paek, J., & Bahk, S. (2016). Load balancing under heavy traffic in RPL routing protocol for low power and lossy networks. IEEE Transactions on Mobile Computing, 16(4), 964–979.

    Article  Google Scholar 

  11. Elappila, M., Chinara, S., & Parhi, D. R. (2018). Survivable path routing in WSN for IoT applications. Pervasive and Mobile Computing, 43, 49–63.

    Article  Google Scholar 

  12. Elappila, M. & Chinara, S. (2018). Dynamic survivable path routing for fast changing IoT network topologies. In 2018 17th IEEE international conference on trust, security and privacy in computing and communications/12th IEEE international conference on big data science and engineering (TrustCom/BigDataSE) (pp. 92–97). IEEE.

  13. Gozuacik, N., & Oktug, S. (2015). Parent-aware routing for iot networks. In S. Balandin, S. Andreev, & Y. Koucheryavy (Eds.), Internet of Things, Smart Spaces, and Next Generation Networks and Systems: 15th International Conference, NEW2AN 2015, and 8th Conference, ruSMART 2015, St. Petersburg, Russia, August 26-28, 2015, Proceedings (pp. 23–33). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-23126-6_3

    Chapter  Google Scholar 

  14. Bhandari, K. S., Hosen, A. S. M., & Cho, G. H. (2018). CoAR: Congestion-aware routing protocol for low power and lossy networks for IoT applications. Sensors, 18(11), 3838.

    Article  Google Scholar 

  15. Jain, A., Pattanaik, K. K., Kumar, A., & Bellavista, P. (2021). Energy and congestion aware routing based on hybrid gradient fields for wireless sensor networks. Wireless Networks, 27(1), 175–193.

    Article  Google Scholar 

  16. Benyahia, A., Bilami, A., & Sedrati, M. (2020). CARTEE: Congestion avoidance with reliable transport and energy efficiency for multimedia applications in wireless sensor networks. Wireless Networks, 26(3), 1803–1822.

    Article  Google Scholar 

  17. Sunitha, G. P., Kumar, S. D., & Kumar, B. V. (2017). Energy balanced zone based routing protocol to mitigate congestion in wireless sensor networks. Wireless Personal Communications, 97(2), 2683–2711.

    Article  Google Scholar 

  18. Pushpa Mettilsha, J., Sandhya, M. K., & Murugan, K. (2021). RPR: Reliable path routing protocol to mitigate congestion in critical IoT applications. Wireless Networks, 27, 5229–5243.

    Article  Google Scholar 

  19. Musaddiq, A., Zikria, Y. B., & Kim, S. W. (2020). Routing protocol for Low-Power and Lossy Networks for heterogeneous traffic network. EURASIP Journal on Wireless Communications and Networking, 2020(1), 1–23.

    Article  Google Scholar 

  20. Kaviani, F., & Soltanaghaei, M. (2022). CQARPL: Congestion and QoS-aware RPL for IoT applications under heavy traffic. The Journal of Supercomputing, 78(14), 16136–16166.

    Article  Google Scholar 

  21. Maheshwari, A., Yadav, R. K., & Nath, P. (2022). Data congestion control using offloading in IoT network. Wireless Personal Communications, 125(3), 2147–2166.

    Article  Google Scholar 

  22. Saaty, T. L. (2010). Principia mathematica decernendi: Mathematical principles of decision making. RWS Publications.

    Google Scholar 

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Funding

The authors declare that they don’t have competing interests and funding.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Delhi Technological University, New Delhi, India

    Aastha Maheshwari & Rajesh Kumar Yadav

  2. Department of Computer Science and Engineering, H.N.B. Garhwal University, Srinagar, Uttarakhand, India

    Prem Nath

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  1. Aastha Maheshwari
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  2. Rajesh Kumar Yadav
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  3. Prem Nath
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Correspondence to Aastha Maheshwari.

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Maheshwari, A., Yadav, R.K. & Nath, P. Congestion Aware Data Transmission in Mobile and Constrained IoT Network. Wireless Pers Commun 130, 2121–2136 (2023). https://doi.org/10.1007/s11277-023-10374-8

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