An optimized congestion control protocol in cellular network for improving quality of service.
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| Title: | An optimized congestion control protocol in cellular network for improving quality of service. |
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| Authors: | V, Sandhya S.1 (AUTHOR) sandhyasdmcet@gmail.com, Joshi, S. M.1 (AUTHOR) joshshree@gmail.com |
| Source: | Multimedia Tools & Applications. Jul2025, Vol. 84 Issue 23, p26267-26292. 26p. |
| Subjects: | Long-Term Evolution (Telecommunications), Quality of service, Network performance, Machine learning, Load balancing (Computer networks), Metaheuristic algorithms, Cell phone systems, Energy consumption |
| Abstract: | In recent decades, Cellular Networks (CN) have been used broadly in communication technologies. The most critical challenge in the CN was congestion control due to the distributed mobile environment. Some approaches, like mobile edge computing, congesting controlling systems, machine learning, and heuristic models, have failed to prevent congestion in CN. The reason for this problem is the lack of continuous monitoring function at every time interval. So, in this present study, a novel Golden Eagle-based Primal–dual Congestion Management (GEbPDCM) has been developed for the Long-Term Evolution (LTE) Ad hoc On-demand Vector (AODV) network. Here, the Golden Eagle function features will afford the continuous monitoring function to monitor data congestion. Hence, the main objective of this research is to improve the Quality of service (QoS) by optimizing congestion controls. Here, the QoS is measured by different metrics, such as delay, packet delivery ratio (PDR), throughput, packet loss, and energy consumption. Initially, the nodes were created in the MATLAB environment, and the GEbPDCM was activated to predict the data load and estimate the node density to measure the node status. Then, the high data overload was migrated to another free status node to control congestion. Finally, the proposed model efficiency was measured regarding delay, packet delivery ratio (PDR), throughput, packet loss, and energy consumption. The proposed model has scored high throughput at 97.1 Mbps and 97.1 PDR, reducing delay to 67.4 ms and 50.6 mJ energy consumption. Hence, the present model is suitable for the LTE network. [ABSTRACT FROM AUTHOR] |
| Copyright of Multimedia Tools & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Items | – Name: Title Label: Title Group: Ti Data: An optimized congestion control protocol in cellular network for improving quality of service. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22V%2C+Sandhya+S%2E%22">V, Sandhya S.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> sandhyasdmcet@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Joshi%2C+S%2E+M%2E%22">Joshi, S. M.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> joshshree@gmail.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Multimedia+Tools+%26+Applications%22">Multimedia Tools & Applications</searchLink>. Jul2025, Vol. 84 Issue 23, p26267-26292. 26p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Long-Term+Evolution+%28Telecommunications%29%22">Long-Term Evolution (Telecommunications)</searchLink><br /><searchLink fieldCode="DE" term="%22Quality+of+service%22">Quality of service</searchLink><br /><searchLink fieldCode="DE" term="%22Network+performance%22">Network performance</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22Load+balancing+%28Computer+networks%29%22">Load balancing (Computer networks)</searchLink><br /><searchLink fieldCode="DE" term="%22Metaheuristic+algorithms%22">Metaheuristic algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Cell+phone+systems%22">Cell phone systems</searchLink><br /><searchLink fieldCode="DE" term="%22Energy+consumption%22">Energy consumption</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In recent decades, Cellular Networks (CN) have been used broadly in communication technologies. The most critical challenge in the CN was congestion control due to the distributed mobile environment. Some approaches, like mobile edge computing, congesting controlling systems, machine learning, and heuristic models, have failed to prevent congestion in CN. The reason for this problem is the lack of continuous monitoring function at every time interval. So, in this present study, a novel Golden Eagle-based Primal–dual Congestion Management (GEbPDCM) has been developed for the Long-Term Evolution (LTE) Ad hoc On-demand Vector (AODV) network. Here, the Golden Eagle function features will afford the continuous monitoring function to monitor data congestion. Hence, the main objective of this research is to improve the Quality of service (QoS) by optimizing congestion controls. Here, the QoS is measured by different metrics, such as delay, packet delivery ratio (PDR), throughput, packet loss, and energy consumption. Initially, the nodes were created in the MATLAB environment, and the GEbPDCM was activated to predict the data load and estimate the node density to measure the node status. Then, the high data overload was migrated to another free status node to control congestion. Finally, the proposed model efficiency was measured regarding delay, packet delivery ratio (PDR), throughput, packet loss, and energy consumption. The proposed model has scored high throughput at 97.1 Mbps and 97.1 PDR, reducing delay to 67.4 ms and 50.6 mJ energy consumption. Hence, the present model is suitable for the LTE network. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Multimedia Tools & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11042-024-20126-w Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 26 StartPage: 26267 Subjects: – SubjectFull: Long-Term Evolution (Telecommunications) Type: general – SubjectFull: Quality of service Type: general – SubjectFull: Network performance Type: general – SubjectFull: Machine learning Type: general – SubjectFull: Load balancing (Computer networks) Type: general – SubjectFull: Metaheuristic algorithms Type: general – SubjectFull: Cell phone systems Type: general – SubjectFull: Energy consumption Type: general Titles: – TitleFull: An optimized congestion control protocol in cellular network for improving quality of service. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: V, Sandhya S. – PersonEntity: Name: NameFull: Joshi, S. M. IsPartOfRelationships: – BibEntity: Dates: – D: 11 M: 07 Text: Jul2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 13807501 Numbering: – Type: volume Value: 84 – Type: issue Value: 23 Titles: – TitleFull: Multimedia Tools & Applications Type: main |
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