Ultra-Dense Internet of Things Model Network

Marochkina, A.; Paramonov, Alexander; Tatarnikova, T. M.

doi:10.1007/978-3-030-97110-6_8

Cited by 6 publications

(1 citation statement)

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“…According to the forecasts of leading manufacturers, the number of wireless devices connected to communication networks will grow in the foreseeable future [3]. A large number of connected devices leads to the formation of high-density networks, which have several features associated with significant mutual influences between nodes [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Multipath Routing Scheme for Optimum Data Transmission in Dense Internet of Things

Ateya,

Bushelenkov,

Muthanna

et al. 2023

Mathematics

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The Internet of Things (IoT) is an emerging technology that has recently gained significant interest, especially with the dramatic increase in connected devices. However, IoT networks are not yet standardized, and the design of such networks faces many challenges, including scalability, flexibility, reliability, and availability of such networks. Routing is among the significant problems facing IoT network design because of the dramatic increase in connected devices and the network requirements regarding availability, reliability, latency, and flexibility. To this end, this work investigates deploying a multipath routing scheme for dense IoT networks. The proposed method selects a group of routes from all available routes to forward data at a maximum rate. The choice of data transmission routes is a complex problem for which numerical optimization methods can be used. A novel method for selecting the optimum group of routes and coefficients of traffic distribution along them is proposed. The proposed method is implemented using dynamic programming. The proposed method outperforms the traditional route selection methods, e.g., random route selection, especially for dense IoT networks. The model significantly reduced the number of intermediate nodes involved in routing paths over dense IoT networks by 34%. Moreover, it effectively demonstrated a significant decrease of 52% in communication overhead and 40% in data delivery time in dense IoT networks compared to traditional models.

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