A Taylor Flamingo Shark Optimization–Based Traffic Aware Content Caching Vehicular Social Networks.
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| Title: | A Taylor Flamingo Shark Optimization–Based Traffic Aware Content Caching Vehicular Social Networks. |
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| Authors: | D., Vedha Vinodha1 (AUTHOR) dvedha1975@gmail.com, Subramanium, Malathy2 (AUTHOR) |
| Source: | International Journal of Communication Systems. 9/10/2025, Vol. 38 Issue 13, p1-18. 18p. |
| Subjects: | Optimization algorithms, Routing algorithms, Content delivery networks, Traffic monitoring, Telecommunication |
| Abstract: | Vehicular Social Networking (VSN) is an emerging and developing application of the Internet of Vehicles (IoV) that aims to integrate vehicular networks with social networks seamlessly. Nevertheless, unique vehicular network features, namely, high mobility as well as frequent communication interruptions, make content delivery to end users under strict delay constraints very problematic. The Taylor Flamingo Shark Optimization (TFSO) method is introduced to address the limitations of existing caching and routing strategies in VSN under real‐time traffic conditions. With the amalgamation of FSA and WSO with the Taylor series, TFSO provides a powerful tool for accurate, delay‐aware, and mobility‐sensitive content caching, thereby improving content delivery efficiency in VSNs. The proposed optimization‐based traffic‐aware content caching is implemented using several stages. Initially, the shortest path with the vehicular content provider is found based on the proposed hybrid Flamingo Shark Optimization (FSO). The FSO is devised by using the Flamingo Search Algorithm (FSA) as well as White Shark Optimization (WSO). Subsequently, traffic‐aware content recommendations are carried out based on conditional likelihood probability. Additionally, the vehicular distribution managed by the content provider is optimized across the network by using the proposed TFSO, which is devised using the proposed FSO along with the Taylor series concept. Moreover, the effectiveness of the developed TFSO approach is assessed by leveraging metrics including computational cost, delivery delay, and delivery rate. The computational cost recorded value is 1.057, which shows that the algorithm operates with low computational overhead; the delivery delay of TFSO is 0.611 s, which indicates that the system required less time to deliver content to end users in high‐mobility scenarios; and the delivery rate is 85.996, which reflects the high success rate of content delivery across the network using 2000 rounds with 150 vehicles. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Communication Systems is the property of Wiley-Blackwell 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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| Header | DbId: egs DbLabel: Engineering Source An: 187278358 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A Taylor Flamingo Shark Optimization–Based Traffic Aware Content Caching Vehicular Social Networks. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22D%2E%2C+Vedha Vinodha%22">D., Vedha Vinodha</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> dvedha1975@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Subramanium%2C+Malathy%22">Subramanium, Malathy</searchLink><relatesTo>2</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Communication+Systems%22">International Journal of Communication Systems</searchLink>. 9/10/2025, Vol. 38 Issue 13, p1-18. 18p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Optimization+algorithms%22">Optimization algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Routing+algorithms%22">Routing algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Content+delivery+networks%22">Content delivery networks</searchLink><br /><searchLink fieldCode="DE" term="%22Traffic+monitoring%22">Traffic monitoring</searchLink><br /><searchLink fieldCode="DE" term="%22Telecommunication%22">Telecommunication</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Vehicular Social Networking (VSN) is an emerging and developing application of the Internet of Vehicles (IoV) that aims to integrate vehicular networks with social networks seamlessly. Nevertheless, unique vehicular network features, namely, high mobility as well as frequent communication interruptions, make content delivery to end users under strict delay constraints very problematic. The Taylor Flamingo Shark Optimization (TFSO) method is introduced to address the limitations of existing caching and routing strategies in VSN under real‐time traffic conditions. With the amalgamation of FSA and WSO with the Taylor series, TFSO provides a powerful tool for accurate, delay‐aware, and mobility‐sensitive content caching, thereby improving content delivery efficiency in VSNs. The proposed optimization‐based traffic‐aware content caching is implemented using several stages. Initially, the shortest path with the vehicular content provider is found based on the proposed hybrid Flamingo Shark Optimization (FSO). The FSO is devised by using the Flamingo Search Algorithm (FSA) as well as White Shark Optimization (WSO). Subsequently, traffic‐aware content recommendations are carried out based on conditional likelihood probability. Additionally, the vehicular distribution managed by the content provider is optimized across the network by using the proposed TFSO, which is devised using the proposed FSO along with the Taylor series concept. Moreover, the effectiveness of the developed TFSO approach is assessed by leveraging metrics including computational cost, delivery delay, and delivery rate. The computational cost recorded value is 1.057, which shows that the algorithm operates with low computational overhead; the delivery delay of TFSO is 0.611 s, which indicates that the system required less time to deliver content to end users in high‐mobility scenarios; and the delivery rate is 85.996, which reflects the high success rate of content delivery across the network using 2000 rounds with 150 vehicles. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Communication Systems is the property of Wiley-Blackwell 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: 10.1002/dac.70188 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 18 StartPage: 1 Subjects: – SubjectFull: Optimization algorithms Type: general – SubjectFull: Routing algorithms Type: general – SubjectFull: Content delivery networks Type: general – SubjectFull: Traffic monitoring Type: general – SubjectFull: Telecommunication Type: general Titles: – TitleFull: A Taylor Flamingo Shark Optimization–Based Traffic Aware Content Caching Vehicular Social Networks. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: D., Vedha Vinodha – PersonEntity: Name: NameFull: Subramanium, Malathy IsPartOfRelationships: – BibEntity: Dates: – D: 10 M: 09 Text: 9/10/2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 10745351 Numbering: – Type: volume Value: 38 – Type: issue Value: 13 Titles: – TitleFull: International Journal of Communication Systems Type: main |
| ResultId | 1 |
