Bio-inspired packet dropping for ad-hoc social networks.
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| Title: | Bio-inspired packet dropping for ad-hoc social networks. |
|---|---|
| Authors: | Liaqat, Hannan Bin1, Xia, Feng1, Yang, Qiuyuan1, Xu, Zhenzhen1 xzz@dlut.edu.cn, Ahmed, Ahmedin Mohammed1, Rahim, Azizur1 |
| Source: | International Journal of Communication Systems. 1/10/2017, Vol. 30 Issue 1, pn/a-N.PAG. 22p. |
| Subjects: | Biologically inspired computing, Computer simulation of immune system, Ad hoc computer networks, Data packeting, Epitopes |
| Abstract: | Ad-hoc social networks (ASNETs) explore social properties of nodes in communications. The usage of various social applications in a resource-scarce environment and the dynamic nature of the network create unnecessary congestion that might degrade the quality of service dramatically. Traditional approaches use drop-tail or random-early discard techniques to drop data packets from the intermediate node queue. Nonetheless, because of the unavailability of the social properties, these techniques are not suitable for ASNETs. In this paper, we propose a Bio-inspired packet dropping (BPD) algorithm for ASNETS. BPD imitates the matching procedure of receptors and epitopes in immune systems to detect congestions. The drop probability settings depend on the selection of data packets, which is based on node popularity level. BPD selects the most prioritized node through social properties, which is inspired by the B-cell stimulation in immune systems. To fairly prioritize data packets, two social properties are used: (1) similarity and (2) closeness centrality between nodes. Extensive simulations are carried out to evaluate and compare BPD to other existing schemes in terms of mean goodput, mean loss rate, throughput, delay, attained bandwidth, and overhead ratio. The results show that the proposed scheme outperforms these existing schemes. Copyright © 2014 John Wiley & Sons, Ltd. [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: 120262904 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Bio-inspired packet dropping for ad-hoc social networks. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Liaqat%2C+Hannan+Bin%22">Liaqat, Hannan Bin</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Xia%2C+Feng%22">Xia, Feng</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Yang%2C+Qiuyuan%22">Yang, Qiuyuan</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Xu%2C+Zhenzhen%22">Xu, Zhenzhen</searchLink><relatesTo>1</relatesTo><i> xzz@dlut.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Ahmed%2C+Ahmedin+Mohammed%22">Ahmed, Ahmedin Mohammed</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Rahim%2C+Azizur%22">Rahim, Azizur</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Communication+Systems%22">International Journal of Communication Systems</searchLink>. 1/10/2017, Vol. 30 Issue 1, pn/a-N.PAG. 22p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Biologically+inspired+computing%22">Biologically inspired computing</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+simulation+of+immune+system%22">Computer simulation of immune system</searchLink><br /><searchLink fieldCode="DE" term="%22Ad+hoc+computer+networks%22">Ad hoc computer networks</searchLink><br /><searchLink fieldCode="DE" term="%22Data+packeting%22">Data packeting</searchLink><br /><searchLink fieldCode="DE" term="%22Epitopes%22">Epitopes</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Ad-hoc social networks (ASNETs) explore social properties of nodes in communications. The usage of various social applications in a resource-scarce environment and the dynamic nature of the network create unnecessary congestion that might degrade the quality of service dramatically. Traditional approaches use drop-tail or random-early discard techniques to drop data packets from the intermediate node queue. Nonetheless, because of the unavailability of the social properties, these techniques are not suitable for ASNETs. In this paper, we propose a Bio-inspired packet dropping (BPD) algorithm for ASNETS. BPD imitates the matching procedure of receptors and epitopes in immune systems to detect congestions. The drop probability settings depend on the selection of data packets, which is based on node popularity level. BPD selects the most prioritized node through social properties, which is inspired by the B-cell stimulation in immune systems. To fairly prioritize data packets, two social properties are used: (1) similarity and (2) closeness centrality between nodes. Extensive simulations are carried out to evaluate and compare BPD to other existing schemes in terms of mean goodput, mean loss rate, throughput, delay, attained bandwidth, and overhead ratio. The results show that the proposed scheme outperforms these existing schemes. Copyright © 2014 John Wiley & Sons, Ltd. [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.2857 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 22 StartPage: n/a Subjects: – SubjectFull: Biologically inspired computing Type: general – SubjectFull: Computer simulation of immune system Type: general – SubjectFull: Ad hoc computer networks Type: general – SubjectFull: Data packeting Type: general – SubjectFull: Epitopes Type: general Titles: – TitleFull: Bio-inspired packet dropping for ad-hoc social networks. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Liaqat, Hannan Bin – PersonEntity: Name: NameFull: Xia, Feng – PersonEntity: Name: NameFull: Yang, Qiuyuan – PersonEntity: Name: NameFull: Xu, Zhenzhen – PersonEntity: Name: NameFull: Ahmed, Ahmedin Mohammed – PersonEntity: Name: NameFull: Rahim, Azizur IsPartOfRelationships: – BibEntity: Dates: – D: 10 M: 01 Text: 1/10/2017 Type: published Y: 2017 Identifiers: – Type: issn-print Value: 10745351 Numbering: – Type: volume Value: 30 – Type: issue Value: 1 Titles: – TitleFull: International Journal of Communication Systems Type: main |
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