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Journal of Discrete Mathematical Sciences and Cryptography cover

Journal of Discrete Mathematical Sciences and Cryptography

(Since 1998)
Open Access ·Peer-reviewed·ISSN (Online): 2169-0065·ISSN (Print): 0972-0529

CiteScore 2025: 2.7 (Q1)

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Monthly Journal: Publishes theoretical and applied research in all areas of Discrete Mathematical Sciences, Cryptography, Combinatorics, Elliptic Curves and Information Security.

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Journal of Discrete Mathematical Sciences and Cryptography
Open Access Research Article

Enhancing wireless network performance using discrete structures and graph theory for efficient data transmission and routing

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pp. 857–865Vol. 29Issue 2-BFebruary 2026DOI: 10.47974/JDMSC-2536 Crossmark XML
Received:
14 May 2025
Published Online:
31 Dec 2025
Article type:
Research Article
Language:
EN
Article no.:
JDMSC-2536
Pages:
857–865

Abstract

Modern communication depends on wireless networks, which allow data to be transmitted across multiple devices and sites. Still, efficiently passing data through such networks is a major problem due to constantly evolving network structures, changing signal conditions, and poor routing. Current methods for routing, frequently do not manage to optimize network operation, which results in higher latency and lower throughput. Also, limited adaptive systems to address real-time network alterations contribute to reduced data performance. This paper responds to these challenges by developing a new approach called Graph-Theoretic Wireless Network Optimization (GTWNO). Graph theory and discrete structures are employed by the proposed method to present wireless networks as graphs, treating access points as nodes and signal links as weighted edges. The model improves routing by reducing delay, response time, and energy use, and by increasing the throughput of the network. Precise network modeling is achieved by the optimization process through the use of graph construction, topology preprocessing, and temporal data aggregation. Experimental data indicate that GTWNO is superior to Model A, Model B, and Model C in improving wireless network performance. The model results in a 6.8-second reduction in end-to-end delay, a 3.2-second improvement in response time, a 1.1-second drop in waiting time, a 5.2 Mbps rise in throughput, and energy consumption of only 0.95 J. The results confirm that GTWNO is effective at improving wireless network performance and deliver a reliable system for data routing and transmission. 

Keywords

Wireless networksGraph theoryDiscrete structuresData transmissionRouting optimization

Subject Classifications

Primary 93A30Secondary 49K15

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