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Journal of Information and Optimization Sciences cover
Hybrid ·Peer-reviewed·ISSN (Online): 2169-0103·ISSN (Print): 0252-2667

WoS  JIF 2026 : 0.4 (Q4)

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Monthly Journal: Publishes theoretical and applied research on topics in information and optimization sciences.

Issues up to 2022 co-published with and available at:Taylor & Francis
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Open Access Research Article

Computational mathematics for improving IoT network efficiency and resource management

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pp. 2305–2317Vol. 47Issue 6June 2026DOI: 10.47974/JIOS-2124XML
Received:
01 Nov 2024
Published Online:
11 Jun 2026
Article type:
Research Article
Language:
EN
Article no.:
JIOS-2124
Pages:
2305–2317

Abstract

Network densification has rapidly emerged as a critical aspect of the IoT since IoT networks are rapidly expanding, and there are immense difficulties in allocating resources, controlling latency, and improving energy efficiency. Accordingly, this research work presents a computational mathematics approach that seeks to improve the IoT network performance and resource utilization. Linear programming is used to control the use of resources, stochastic modeling is used to forecast loads, and calculus is used for optimization of power. The model’s implementation on IoT networks shows enhanced network performance in terms of the latency, dropped packet rates and energy utilization. According to quantitative results, there is an improvement on the latency with a value less than twenty percent and on the power that differs by less than thirty percent, which proves that the proposed model can fulfil the growing IoT system requirements. 

Keywords

Subject Classifications

Primary 05C8218M3534B45Secondary 35R0260K2068M10

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