Dynamic Connectivity Hub: Multiple ISPs Smart Aggregation for Optimized IoT Connectivity
The increasing complexity of Internet of Things (IoT) networks demands scalable and adaptive solutions to ensure reliable and efficient connectivity. As IoT ecosystems grow increasingly complex, multiple Internet Service Providers (ISPs) aggregation and dynamic traffic optimization have become criti...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10840185/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832576777502851072 |
|---|---|
| author | Hany Ali Mohamed A. Abouelatta Khaled Y. Youssef |
| author_facet | Hany Ali Mohamed A. Abouelatta Khaled Y. Youssef |
| author_sort | Hany Ali |
| collection | DOAJ |
| description | The increasing complexity of Internet of Things (IoT) networks demands scalable and adaptive solutions to ensure reliable and efficient connectivity. As IoT ecosystems grow increasingly complex, multiple Internet Service Providers (ISPs) aggregation and dynamic traffic optimization have become critical for ensuring reliable, cost-effective, and high-performance network services. This paper proposes the Dynamic Connectivity Hub (DCH), a novel system that aggregates services from multiple ISPs - ranging from terrestrial (e.g., fiber optics, mobile 4G/5G), and satellite networks (e.g., LEO, GEO) - to dynamically distribute traffic to IoT devices. DCH uses an Artificial Neural Network (ANN) model to continuously optimize load balancing by assigning data rates to the most efficient ISPs in real time. By analyzing performance metrics such as latency, data rate, congestion, and cost, the ANN ensures that traffic is routed through the best-performing ISPs while discarding sub-optimal connections. The DCH is optimized for urban deployments, filling gaps in connectivity and providing backup coverage in areas with limited ISP infrastructure. While for rural deployments, DCH is optimized to serve as a primary connectivity provider. Extensive simulations demonstrate that the DCH outperforms traditional static ISP models in terms of latency reduction, cost efficiency, and resilience to outages. Validation through MATLAB simulations highlights the DCH’s ability to outperform baseline models by demonstrating a 50% reduction in latency, a 25% improvement in data rate allocation, and a 20% reduction in operational costs compared to traditional static models. This paper not only highlights the DCH’s potential as a flexible, scalable, and efficient solution but also presents it as a transformative solution for next-generation IoT networks, addressing connectivity challenges across diverse deployment scenarios. |
| format | Article |
| id | doaj-art-b02a8a4b2ea64b3b858174a05bff598c |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-b02a8a4b2ea64b3b858174a05bff598c2025-01-31T00:01:06ZengIEEEIEEE Access2169-35362025-01-0113187341874810.1109/ACCESS.2025.352948610840185Dynamic Connectivity Hub: Multiple ISPs Smart Aggregation for Optimized IoT ConnectivityHany Ali0https://orcid.org/0000-0001-5358-372XMohamed A. Abouelatta1https://orcid.org/0000-0002-8035-9915Khaled Y. Youssef2Electronics and Communications Engineering Department, Faculty of Engineering, Ain Shams University, Cairo, EgyptElectronics and Communications Engineering Department, Faculty of Engineering, Ain Shams University, Cairo, EgyptCommunications Engineering Department, Faculty of Navigation Science and Space Technology, Beni-Suef University, Beni Suef, EgyptThe increasing complexity of Internet of Things (IoT) networks demands scalable and adaptive solutions to ensure reliable and efficient connectivity. As IoT ecosystems grow increasingly complex, multiple Internet Service Providers (ISPs) aggregation and dynamic traffic optimization have become critical for ensuring reliable, cost-effective, and high-performance network services. This paper proposes the Dynamic Connectivity Hub (DCH), a novel system that aggregates services from multiple ISPs - ranging from terrestrial (e.g., fiber optics, mobile 4G/5G), and satellite networks (e.g., LEO, GEO) - to dynamically distribute traffic to IoT devices. DCH uses an Artificial Neural Network (ANN) model to continuously optimize load balancing by assigning data rates to the most efficient ISPs in real time. By analyzing performance metrics such as latency, data rate, congestion, and cost, the ANN ensures that traffic is routed through the best-performing ISPs while discarding sub-optimal connections. The DCH is optimized for urban deployments, filling gaps in connectivity and providing backup coverage in areas with limited ISP infrastructure. While for rural deployments, DCH is optimized to serve as a primary connectivity provider. Extensive simulations demonstrate that the DCH outperforms traditional static ISP models in terms of latency reduction, cost efficiency, and resilience to outages. Validation through MATLAB simulations highlights the DCH’s ability to outperform baseline models by demonstrating a 50% reduction in latency, a 25% improvement in data rate allocation, and a 20% reduction in operational costs compared to traditional static models. This paper not only highlights the DCH’s potential as a flexible, scalable, and efficient solution but also presents it as a transformative solution for next-generation IoT networks, addressing connectivity challenges across diverse deployment scenarios.https://ieeexplore.ieee.org/document/10840185/ISP aggregationartificial neural networks (ANN)load balancingIoT connectivitymulti-ISP optimizationtraffic-aware routing |
| spellingShingle | Hany Ali Mohamed A. Abouelatta Khaled Y. Youssef Dynamic Connectivity Hub: Multiple ISPs Smart Aggregation for Optimized IoT Connectivity IEEE Access ISP aggregation artificial neural networks (ANN) load balancing IoT connectivity multi-ISP optimization traffic-aware routing |
| title | Dynamic Connectivity Hub: Multiple ISPs Smart Aggregation for Optimized IoT Connectivity |
| title_full | Dynamic Connectivity Hub: Multiple ISPs Smart Aggregation for Optimized IoT Connectivity |
| title_fullStr | Dynamic Connectivity Hub: Multiple ISPs Smart Aggregation for Optimized IoT Connectivity |
| title_full_unstemmed | Dynamic Connectivity Hub: Multiple ISPs Smart Aggregation for Optimized IoT Connectivity |
| title_short | Dynamic Connectivity Hub: Multiple ISPs Smart Aggregation for Optimized IoT Connectivity |
| title_sort | dynamic connectivity hub multiple isps smart aggregation for optimized iot connectivity |
| topic | ISP aggregation artificial neural networks (ANN) load balancing IoT connectivity multi-ISP optimization traffic-aware routing |
| url | https://ieeexplore.ieee.org/document/10840185/ |
| work_keys_str_mv | AT hanyali dynamicconnectivityhubmultipleispssmartaggregationforoptimizediotconnectivity AT mohamedaabouelatta dynamicconnectivityhubmultipleispssmartaggregationforoptimizediotconnectivity AT khaledyyoussef dynamicconnectivityhubmultipleispssmartaggregationforoptimizediotconnectivity |