STATE AWARE MULTI-HOP ROUTING VIA DIGITAL TWIN FOR IOT NETWORKS

March 2026
Vol-12, Issue-2
Paper ID: 28162
ISSN: 2395-4396
Downloads: 0

Abstract & Details

Research Area
INTERNET OF THINGS (WSN)
Keywords
Digital Twin IoT Networks State-Aware Routing Multi-Hop Routing Energy Efficiency Real-Time Monitoring Network Simulation Predictive Analytics Optimization Algorithms Dynamic Topology Link Quality Routing Protocol Cyber-Physical Systems (CPS) Load Balancing Quality of Service (QoS) Reliability Data Transmission
Abstract
The Internet of Things (IoT) has become a key technology enabling applications in healthcare, transportation, manufacturing, and smart cities. However, managing the vast, dynamic IoT networks presents challenges, particularly in energy-efficient routing. Traditional routing protocols, such as static and Distance Vector (DV) routing, are inadequate for IoT networks, which are constrained by energy limitations and dynamic conditions like node mobility and congestion. This paper presents a state-aware multi-hop routing scheme integrated with Digital Twin (DT) technology to optimize routing performance in IoT networks. DT, a real-time virtual replica of physical systems, enables the continuous monitoring and prediction of network conditions, such as energy levels, traffic status, and potential failures. The proposed model utilizes metaheuristic optimization algorithms like Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Ant Colony Optimization (ACO) to dynamically select the optimal routing paths, considering the state of each node and the network as a whole. This approach enhances IoT network performance, reduces energy consumption, and mitigates network failures. Additionally, DT contributes to security by simulating potential threats and proactively preventing attacks. The model's efficiency is demonstrated through a comparative analysis with existing protocols, showing significant improvements in network throughput, energy efficiency, and latency. Keywords: Digital Twin (DT), IoT Networks, State-Aware Routing, Multi-Hop Routing, Energy Efficiency, Metaheuristic Optimization, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Network Performance.
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author Information

# Name Institute / Affiliation
1 PATEL NENSI RAKESHBHAI GTU-SET
2 Dr. S.K. HADIA GTU-SET

How to Cite

Use the following formats to cite this article in your research.

APA Style
RAKESHBHAI, PATEL NENSI & HADIA, Dr. S.K. (2026). STATE AWARE MULTI-HOP ROUTING VIA DIGITAL TWIN FOR IOT NETWORKS. International Journal of Advance Research and Innovative Ideas In Education, 12(2), 437-445.
MLA Style
RAKESHBHAI, PATEL NENSI, and Dr. S.K. HADIA. "STATE AWARE MULTI-HOP ROUTING VIA DIGITAL TWIN FOR IOT NETWORKS." International Journal of Advance Research and Innovative Ideas In Education, vol. 12, no. 2, 2026, pp. 437-445.
IEEE Style
PATEL NENSI RAKESHBHAI and Dr. S.K. HADIA, "STATE AWARE MULTI-HOP ROUTING VIA DIGITAL TWIN FOR IOT NETWORKS," International Journal of Advance Research and Innovative Ideas In Education, vol. 12, no. 2, pp. 437-445, 2026.
Vancouver Style
RAKESHBHAI PATEL NENSI, HADIA Dr. S.K.. STATE AWARE MULTI-HOP ROUTING VIA DIGITAL TWIN FOR IOT NETWORKS. International Journal of Advance Research and Innovative Ideas In Education. 2026;12(2):437-445.
Harvard Style
RAKESHBHAI, PATEL NENSI & HADIA, Dr. S.K. (2026) 'STATE AWARE MULTI-HOP ROUTING VIA DIGITAL TWIN FOR IOT NETWORKS', International Journal of Advance Research and Innovative Ideas In Education, 12(2), pp. 437-445.
Chicago Style
RAKESHBHAI, PATEL NENSI and Dr. S.K. HADIA. "STATE AWARE MULTI-HOP ROUTING VIA DIGITAL TWIN FOR IOT NETWORKS." International Journal of Advance Research and Innovative Ideas In Education 12, no. 2 (2026): 437-445.
Turabian Style
RAKESHBHAI, PATEL NENSI and Dr. S.K. HADIA. "STATE AWARE MULTI-HOP ROUTING VIA DIGITAL TWIN FOR IOT NETWORKS." International Journal of Advance Research and Innovative Ideas In Education 12, no. 2 (2026): 437-445.

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