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QFS-RPL: mobility and energy aware multi path routing protocol for the internet of mobile things data transfer infrastructures

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Abstract

The Internet of Things (IoT) is a network of various interconnected objects capable of collecting and exchanging data without human interaction. These objects have limited processing power, storage space, memory, bandwidth and energy. Therefore, due to these limitations, data transmission and routing are challenging issues where data collection and analysis methods are essential. The Routing Protocol for Low-power and Lossy Networks (RPL) is one of the best alternatives to ensure routing in LoWPAN6 networks. However, RPL lacks scalability and basically designed for non-dynamic devices. Another drawback of the RPL protocol is the lack of load balancing support, leading to unfair distribution of traffic in the network that may decrease network efficiency. This study proposes a novel RPL-based routing protocol, QFS-RPL, using Q-learning algorithm policy and ideation from the Fisheye State Routing protocol. We have developed an algorithm for ease of data transfer in the IoT, which provides better performance than existing protocols, especially when dealing with a mobile network. To evaluate the performance of the proposed method, the Contiki operating system and Cooja simulator have been used in scenarios with mobile and stationary nodes and random network topologies. The results have been compared with RPL and mRPL. We have developed an algorithm for ease of data transfer in the IoT, which provides better performance than existing protocols, especially when dealing with a mobile network. The simulation outputs revealed that our scheme performs more efficiently in load balancing, number of table entries, Packet Delivery Ratio (PDR), End-to-End (E2E) latency, network throughput, convergence speed, control packet overhead and Remaining Useful Lifetime in designed scenarios compared to other methods. Moreover, the simulation results show an out-performance of rival schemes in terms of remaining energy and network lifetime.

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Notes

  1. Received Signal Strength Indicator (RSSI): It measures the RF device's power level from the radio at a specific location and time.

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This research did not receive any specific grant from funding agencies in the public, commercial, or not-forprofit sectors.

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Authors and Affiliations

  1. Department of Computer Engineering, Urmia Branch, Islamic Azad University, Urmia, Iran

    Mahmoud Alilou, Amin Babazadeh Sangar, Kambiz Majidzadeh & Mohammad Masdari

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  1. Mahmoud Alilou
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  2. Amin Babazadeh Sangar
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  3. Kambiz Majidzadeh
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Contributions

MA and MM conceived of the presented idea. MA developed the theory and performed the computations. ASB and KM verified the analytical methods. MM encouraged M., Alilou to investigate "how to create multi-paths in dynamic network models and load balancing with the lowest cost" and supervised the findings of this work. All authors discussed the results and contributed to the final manuscript. MA and MM carried out the experiment. MA wrote the manuscript with support from ASB. KM prepared the required hardware and software infrastructures for conducting experiments and also designed different scenarios for each experiment. MA developed the theoretical formalism, performed the analytic calculations and performed the numerical simulations. Both ASB and MM authors contributed to the final version of the manuscript. MM supervised the project. MA and MM designed the model and the computational framework and analysed the data. MA developed the theoretical formalism, performed the analytic calculations and performed the numerical simulations. Both MA and MM authors contributed to the final version of the manuscript. MM supervised the project. MA, MM, ASB and KM conceived and planned and carried out the experiments. MA, planned and carried out the simulations. MA, MM, KM and ASB contributed to sample preparation. MM and ASB, contributed to the interpretation of the results. MA took the lead in writing the manuscript. All authors provided critical feedback and helped shape the research, analysis and manuscript. MA and MM wrote the manuscript with input from all authors. KM conceived the study and was in charge of overall direction and planning. MA designed and performed the experiments, derived the models and analysed the data. MM assisted with Figs. 8, 9, 10 measurements and ASB helped carry out the Figs. 11, 12 simulations. MA devised the project, the main conceptual ideas and proof outline. MM worked out almost all of the technical details, and performed the numerical calculations for the suggested experiment. All authors discussed the results and commented on the manuscript and contributed to the design and implementation of the research, to the analysis of the results and to the writing of the manuscript .

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Correspondence to Amin Babazadeh Sangar.

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Alilou, M., Babazadeh Sangar, A., Majidzadeh, K. et al. QFS-RPL: mobility and energy aware multi path routing protocol for the internet of mobile things data transfer infrastructures. Telecommun Syst 85, 289–312 (2024). https://doi.org/10.1007/s11235-023-01075-5

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