Disorder Analytic Model-Based CMT Algorithms in Vehicular Sensor Networks.
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| Title: | Disorder Analytic Model-Based CMT Algorithms in Vehicular Sensor Networks. |
|---|---|
| Authors: | Changqiao Xu1,2 cqxu@bupt.edu.cn, Xiangzhou Xia3, Jianfeng Guan2, Hongke Zhang2,4, Gabriel-Miro Muntean5 |
| Source: | International Journal of Distributed Sensor Networks. 2013, p1-11. 11p. |
| Subjects: | Vehicular ad hoc networks, Concurrent Aggregates (Computer program language), Heterogeneity, Traffic engineering, Road safety measures |
| Abstract: | Recently, vehicular sensor networks (VSNs) have emerged as a new intelligent transport networking paradigm in the Internet of Things. By sensing, collecting, and delivering traffic-related information, VSNs can significantly improve both driving experience and traffic flow control, especially in constrained urban environments. Latest technological advances enable vehicular devices to be equipped with multiple wireless interfaces, which can support cooperative communications for concurrent multipath transfer (CMT) in VSNs. However, path heterogeneity and vehicle mobilitycause CMT not to achieve the same high transport efficiency recorded in wired nonmobile network environments. This paper proposes a novel vehicular network-based CMT solution (VN-CMT) to address the above issues and improve data delivery efficiency. VN-CMT is based on a CMT disorder analytic model which can effectively and accurately evaluate the degree of out-of-order data. Based on this proposed model, a series of mechanisms are introduced as follows: (1) a packet disorder-reducing retransmission policy to reduce retransmission delay; (2) a path group selection algorithm to find the best path set for data multipath concurrent transfer; and (3) a data scheduling mechanism to distribute data according to each path's capacity. Simulation results show how VN-CMT improves data delivery efficiency in comparison with an existing state-of-the-art solution. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Distributed Sensor Networks 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 |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Disorder Analytic Model-Based CMT Algorithms in Vehicular Sensor Networks. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Changqiao+Xu%22">Changqiao Xu</searchLink><relatesTo>1,2</relatesTo><i> cqxu@bupt.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Xiangzhou+Xia%22">Xiangzhou Xia</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Jianfeng+Guan%22">Jianfeng Guan</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Hongke+Zhang%22">Hongke Zhang</searchLink><relatesTo>2,4</relatesTo><br /><searchLink fieldCode="AR" term="%22Gabriel-Miro+Muntean%22">Gabriel-Miro Muntean</searchLink><relatesTo>5</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Distributed+Sensor+Networks%22">International Journal of Distributed Sensor Networks</searchLink>. 2013, p1-11. 11p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Vehicular+ad+hoc+networks%22">Vehicular ad hoc networks</searchLink><br /><searchLink fieldCode="DE" term="%22Concurrent+Aggregates+%28Computer+program+language%29%22">Concurrent Aggregates (Computer program language)</searchLink><br /><searchLink fieldCode="DE" term="%22Heterogeneity%22">Heterogeneity</searchLink><br /><searchLink fieldCode="DE" term="%22Traffic+engineering%22">Traffic engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Road+safety+measures%22">Road safety measures</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Recently, vehicular sensor networks (VSNs) have emerged as a new intelligent transport networking paradigm in the Internet of Things. By sensing, collecting, and delivering traffic-related information, VSNs can significantly improve both driving experience and traffic flow control, especially in constrained urban environments. Latest technological advances enable vehicular devices to be equipped with multiple wireless interfaces, which can support cooperative communications for concurrent multipath transfer (CMT) in VSNs. However, path heterogeneity and vehicle mobilitycause CMT not to achieve the same high transport efficiency recorded in wired nonmobile network environments. This paper proposes a novel vehicular network-based CMT solution (VN-CMT) to address the above issues and improve data delivery efficiency. VN-CMT is based on a CMT disorder analytic model which can effectively and accurately evaluate the degree of out-of-order data. Based on this proposed model, a series of mechanisms are introduced as follows: (1) a packet disorder-reducing retransmission policy to reduce retransmission delay; (2) a path group selection algorithm to find the best path set for data multipath concurrent transfer; and (3) a data scheduling mechanism to distribute data according to each path's capacity. Simulation results show how VN-CMT improves data delivery efficiency in comparison with an existing state-of-the-art solution. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Distributed Sensor Networks 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: 10.1155/2013/460164 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 1 Subjects: – SubjectFull: Vehicular ad hoc networks Type: general – SubjectFull: Concurrent Aggregates (Computer program language) Type: general – SubjectFull: Heterogeneity Type: general – SubjectFull: Traffic engineering Type: general – SubjectFull: Road safety measures Type: general Titles: – TitleFull: Disorder Analytic Model-Based CMT Algorithms in Vehicular Sensor Networks. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Changqiao Xu – PersonEntity: Name: NameFull: Xiangzhou Xia – PersonEntity: Name: NameFull: Jianfeng Guan – PersonEntity: Name: NameFull: Hongke Zhang – PersonEntity: Name: NameFull: Gabriel-Miro Muntean IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: 2013 Type: published Y: 2013 Identifiers: – Type: issn-print Value: 15501329 Titles: – TitleFull: International Journal of Distributed Sensor Networks Type: main |
| ResultId | 1 |
