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

Author:

Ateya Abdelhamied A.12ORCID,Bushelenkov Sergey3,Muthanna Ammar34ORCID,Paramonov Alexander3ORCID,Koucheryavy Andrey3,Allaoua Chelloug Samia5ORCID,Abd El-Latif Ahmed A.16

Affiliation:

1. EIAS Data Science Lab, College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia

2. Department of Electronics and Communications Engineering, Zagazig University, Zagazig 44519, Egypt

3. Department of Telecommunication Networks and Data Transmission, The Bonch-Bruevich Saint-Petersburg State University of Telecommunications, 193232 Saint Petersburg, Russia

4. Applied Probability and Informatics, Peoples’ Friendship University of Russia (RUDN University), 117198 Moscow, Russia

5. Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh 11671, Saudi Arabia

6. Department of Mathematics and Computer Science, Faculty of Science, Menoufia University, Shibin El-Kom 32511, Egypt

Abstract

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.

Funder

Ministry of Science and High Education of the Russian Federation

Princess Nourah bint Abdulrahman University

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

Reference28 articles.

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