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K-Trickle: performance evaluation and impact on quality of service in resource-constrained networks

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Abstract

The Internet of Things is an emerging domain in the field of establishing the effective communications. Routing protocols are crucial for ensuring dependable data transmission in networks with limited resources. RPL is a standardized protocol used in low power lossy networks. However, it encounters difficulties in effectively managing energy usage while maintaining a satisfactory level of quality of service. The Trickle algorithm is an integral part of RPL that minimizes the frequency of control message transmission, further enhancing its efficiency and scalability. The redundancy level of transmissions is determined by the impact on the redundancy constant K in the trickle, default higher K value leads to more frequent transmissions, ensuring messages are received even in unreliable networks in the standard trickle. The research investigates the variants of K with different values and optimizes the value as K-Trickle. We evaluate K-Trickle using simulation in Contiki 3.0 of Cooja under various network configurations along with mobility. Our results demonstrate that K-Trickle significantly improves network performance compared to standard trickle and reduces energy consumption by up to 3% while maintaining improved metric of packet delivery rates.

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PA and GRK are contributed to the design and methodology of this study, the assessment of the outcomes and the writing of the manuscript.

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Correspondence to P. Arivubrakan.

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Arivubrakan, P., Kanagachidambaresan, G.R. K-Trickle: performance evaluation and impact on quality of service in resource-constrained networks. Int J Data Sci Anal (2024). https://doi.org/10.1007/s41060-024-00531-y

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