CogTRA: a deployable mechanism for cognitive transmission rate adaptation in IEEE 802.11 networks

Abstract Wireless local area networks have become vastly popular, and IEEE 802.11 is the chosen standard for almost all wireless devices. This standard specifies several modulation and channel coding techniques that must be implemented by all wireless interfaces to adapt to changes in wireless chann...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Chaves, Luciano J. [verfasserIn] Madeira, Edmundo R. M. Garcia, Islene C.

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2013

Schlagwörter:	IEEE 802.11 networks Rate adaptation Self-configuration Cognitive algorithms

Anmerkung:	© The Brazilian Computer Society 2013

Übergeordnetes Werk:	Enthalten in: Journal of the Brazilian Computer Society - London : Springer, 1996, 19(2013), 4 vom: 12. Juni, Seite 493-510
Übergeordnetes Werk:	volume:19 ; year:2013 ; number:4 ; day:12 ; month:06 ; pages:493-510

Links:	Volltext

DOI / URN:	10.1007/s13173-013-0113-y

Katalog-ID:	SPR03074363X

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allfields	10.1007/s13173-013-0113-y doi (DE-627)SPR03074363X (SPR)s13173-013-0113-y-e DE-627 ger DE-627 rakwb eng Chaves, Luciano J. verfasserin aut CogTRA: a deployable mechanism for cognitive transmission rate adaptation in IEEE 802.11 networks 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Brazilian Computer Society 2013 Abstract Wireless local area networks have become vastly popular, and IEEE 802.11 is the chosen standard for almost all wireless devices. This standard specifies several modulation and channel coding techniques that must be implemented by all wireless interfaces to adapt to changes in wireless channels. As a result, these interfaces support multiple transmission data rates. However, this standard does not define how to dynamically select the appropriate data rate; instead, manufacturers can design and implement their own algorithms. Although several solutions have been proposed in the literature, only a few are used in practice. Moreover, their performance is still limited to specific conditions, such as highly dynamic environments. To tackle these challenges, this paper introduces CogTRA, which is a deployable mechanism built upon an existing cognitive framework called CogProt. Due to its self-adjustment functionality, CogTRA can work not only in stable but also in dynamic environments. It was implemented in the OpenWrt Linux distribution for embedded devices and evaluated through experiments using real network equipment. The results underline performance benefits with respect to existing data rate adaptation algorithms, with CogTRA exhibiting better performance especially in such dynamic networks. IEEE 802.11 networks (dpeaa)DE-He213 Rate adaptation (dpeaa)DE-He213 Self-configuration (dpeaa)DE-He213 Cognitive algorithms (dpeaa)DE-He213 Madeira, Edmundo R. M. aut Garcia, Islene C. aut Enthalten in Journal of the Brazilian Computer Society London : Springer, 1996 19(2013), 4 vom: 12. Juni, Seite 493-510 (DE-627)324613377 (DE-600)2028746-X 1678-4804 nnns volume:19 year:2013 number:4 day:12 month:06 pages:493-510 https://dx.doi.org/10.1007/s13173-013-0113-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 19 2013 4 12 06 493-510
spelling	10.1007/s13173-013-0113-y doi (DE-627)SPR03074363X (SPR)s13173-013-0113-y-e DE-627 ger DE-627 rakwb eng Chaves, Luciano J. verfasserin aut CogTRA: a deployable mechanism for cognitive transmission rate adaptation in IEEE 802.11 networks 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Brazilian Computer Society 2013 Abstract Wireless local area networks have become vastly popular, and IEEE 802.11 is the chosen standard for almost all wireless devices. This standard specifies several modulation and channel coding techniques that must be implemented by all wireless interfaces to adapt to changes in wireless channels. As a result, these interfaces support multiple transmission data rates. However, this standard does not define how to dynamically select the appropriate data rate; instead, manufacturers can design and implement their own algorithms. Although several solutions have been proposed in the literature, only a few are used in practice. Moreover, their performance is still limited to specific conditions, such as highly dynamic environments. To tackle these challenges, this paper introduces CogTRA, which is a deployable mechanism built upon an existing cognitive framework called CogProt. Due to its self-adjustment functionality, CogTRA can work not only in stable but also in dynamic environments. It was implemented in the OpenWrt Linux distribution for embedded devices and evaluated through experiments using real network equipment. The results underline performance benefits with respect to existing data rate adaptation algorithms, with CogTRA exhibiting better performance especially in such dynamic networks. IEEE 802.11 networks (dpeaa)DE-He213 Rate adaptation (dpeaa)DE-He213 Self-configuration (dpeaa)DE-He213 Cognitive algorithms (dpeaa)DE-He213 Madeira, Edmundo R. M. aut Garcia, Islene C. aut Enthalten in Journal of the Brazilian Computer Society London : Springer, 1996 19(2013), 4 vom: 12. Juni, Seite 493-510 (DE-627)324613377 (DE-600)2028746-X 1678-4804 nnns volume:19 year:2013 number:4 day:12 month:06 pages:493-510 https://dx.doi.org/10.1007/s13173-013-0113-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 19 2013 4 12 06 493-510
allfields_unstemmed	10.1007/s13173-013-0113-y doi (DE-627)SPR03074363X (SPR)s13173-013-0113-y-e DE-627 ger DE-627 rakwb eng Chaves, Luciano J. verfasserin aut CogTRA: a deployable mechanism for cognitive transmission rate adaptation in IEEE 802.11 networks 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Brazilian Computer Society 2013 Abstract Wireless local area networks have become vastly popular, and IEEE 802.11 is the chosen standard for almost all wireless devices. This standard specifies several modulation and channel coding techniques that must be implemented by all wireless interfaces to adapt to changes in wireless channels. As a result, these interfaces support multiple transmission data rates. However, this standard does not define how to dynamically select the appropriate data rate; instead, manufacturers can design and implement their own algorithms. Although several solutions have been proposed in the literature, only a few are used in practice. Moreover, their performance is still limited to specific conditions, such as highly dynamic environments. To tackle these challenges, this paper introduces CogTRA, which is a deployable mechanism built upon an existing cognitive framework called CogProt. Due to its self-adjustment functionality, CogTRA can work not only in stable but also in dynamic environments. It was implemented in the OpenWrt Linux distribution for embedded devices and evaluated through experiments using real network equipment. The results underline performance benefits with respect to existing data rate adaptation algorithms, with CogTRA exhibiting better performance especially in such dynamic networks. IEEE 802.11 networks (dpeaa)DE-He213 Rate adaptation (dpeaa)DE-He213 Self-configuration (dpeaa)DE-He213 Cognitive algorithms (dpeaa)DE-He213 Madeira, Edmundo R. M. aut Garcia, Islene C. aut Enthalten in Journal of the Brazilian Computer Society London : Springer, 1996 19(2013), 4 vom: 12. Juni, Seite 493-510 (DE-627)324613377 (DE-600)2028746-X 1678-4804 nnns volume:19 year:2013 number:4 day:12 month:06 pages:493-510 https://dx.doi.org/10.1007/s13173-013-0113-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 19 2013 4 12 06 493-510
allfieldsGer	10.1007/s13173-013-0113-y doi (DE-627)SPR03074363X (SPR)s13173-013-0113-y-e DE-627 ger DE-627 rakwb eng Chaves, Luciano J. verfasserin aut CogTRA: a deployable mechanism for cognitive transmission rate adaptation in IEEE 802.11 networks 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Brazilian Computer Society 2013 Abstract Wireless local area networks have become vastly popular, and IEEE 802.11 is the chosen standard for almost all wireless devices. This standard specifies several modulation and channel coding techniques that must be implemented by all wireless interfaces to adapt to changes in wireless channels. As a result, these interfaces support multiple transmission data rates. However, this standard does not define how to dynamically select the appropriate data rate; instead, manufacturers can design and implement their own algorithms. Although several solutions have been proposed in the literature, only a few are used in practice. Moreover, their performance is still limited to specific conditions, such as highly dynamic environments. To tackle these challenges, this paper introduces CogTRA, which is a deployable mechanism built upon an existing cognitive framework called CogProt. Due to its self-adjustment functionality, CogTRA can work not only in stable but also in dynamic environments. It was implemented in the OpenWrt Linux distribution for embedded devices and evaluated through experiments using real network equipment. The results underline performance benefits with respect to existing data rate adaptation algorithms, with CogTRA exhibiting better performance especially in such dynamic networks. IEEE 802.11 networks (dpeaa)DE-He213 Rate adaptation (dpeaa)DE-He213 Self-configuration (dpeaa)DE-He213 Cognitive algorithms (dpeaa)DE-He213 Madeira, Edmundo R. M. aut Garcia, Islene C. aut Enthalten in Journal of the Brazilian Computer Society London : Springer, 1996 19(2013), 4 vom: 12. Juni, Seite 493-510 (DE-627)324613377 (DE-600)2028746-X 1678-4804 nnns volume:19 year:2013 number:4 day:12 month:06 pages:493-510 https://dx.doi.org/10.1007/s13173-013-0113-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 19 2013 4 12 06 493-510
allfieldsSound	10.1007/s13173-013-0113-y doi (DE-627)SPR03074363X (SPR)s13173-013-0113-y-e DE-627 ger DE-627 rakwb eng Chaves, Luciano J. verfasserin aut CogTRA: a deployable mechanism for cognitive transmission rate adaptation in IEEE 802.11 networks 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Brazilian Computer Society 2013 Abstract Wireless local area networks have become vastly popular, and IEEE 802.11 is the chosen standard for almost all wireless devices. This standard specifies several modulation and channel coding techniques that must be implemented by all wireless interfaces to adapt to changes in wireless channels. As a result, these interfaces support multiple transmission data rates. However, this standard does not define how to dynamically select the appropriate data rate; instead, manufacturers can design and implement their own algorithms. Although several solutions have been proposed in the literature, only a few are used in practice. Moreover, their performance is still limited to specific conditions, such as highly dynamic environments. To tackle these challenges, this paper introduces CogTRA, which is a deployable mechanism built upon an existing cognitive framework called CogProt. Due to its self-adjustment functionality, CogTRA can work not only in stable but also in dynamic environments. It was implemented in the OpenWrt Linux distribution for embedded devices and evaluated through experiments using real network equipment. The results underline performance benefits with respect to existing data rate adaptation algorithms, with CogTRA exhibiting better performance especially in such dynamic networks. IEEE 802.11 networks (dpeaa)DE-He213 Rate adaptation (dpeaa)DE-He213 Self-configuration (dpeaa)DE-He213 Cognitive algorithms (dpeaa)DE-He213 Madeira, Edmundo R. M. aut Garcia, Islene C. aut Enthalten in Journal of the Brazilian Computer Society London : Springer, 1996 19(2013), 4 vom: 12. Juni, Seite 493-510 (DE-627)324613377 (DE-600)2028746-X 1678-4804 nnns volume:19 year:2013 number:4 day:12 month:06 pages:493-510 https://dx.doi.org/10.1007/s13173-013-0113-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 19 2013 4 12 06 493-510
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source	Enthalten in Journal of the Brazilian Computer Society 19(2013), 4 vom: 12. Juni, Seite 493-510 volume:19 year:2013 number:4 day:12 month:06 pages:493-510
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topic_facet	IEEE 802.11 networks Rate adaptation Self-configuration Cognitive algorithms
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authorswithroles_txt_mv	Chaves, Luciano J. @@aut@@ Madeira, Edmundo R. M. @@aut@@ Garcia, Islene C. @@aut@@
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title_full	CogTRA: a deployable mechanism for cognitive transmission rate adaptation in IEEE 802.11 networks
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title_sort	cogtra: a deployable mechanism for cognitive transmission rate adaptation in ieee 802.11 networks
title_auth	CogTRA: a deployable mechanism for cognitive transmission rate adaptation in IEEE 802.11 networks
abstract	Abstract Wireless local area networks have become vastly popular, and IEEE 802.11 is the chosen standard for almost all wireless devices. This standard specifies several modulation and channel coding techniques that must be implemented by all wireless interfaces to adapt to changes in wireless channels. As a result, these interfaces support multiple transmission data rates. However, this standard does not define how to dynamically select the appropriate data rate; instead, manufacturers can design and implement their own algorithms. Although several solutions have been proposed in the literature, only a few are used in practice. Moreover, their performance is still limited to specific conditions, such as highly dynamic environments. To tackle these challenges, this paper introduces CogTRA, which is a deployable mechanism built upon an existing cognitive framework called CogProt. Due to its self-adjustment functionality, CogTRA can work not only in stable but also in dynamic environments. It was implemented in the OpenWrt Linux distribution for embedded devices and evaluated through experiments using real network equipment. The results underline performance benefits with respect to existing data rate adaptation algorithms, with CogTRA exhibiting better performance especially in such dynamic networks. © The Brazilian Computer Society 2013
abstractGer	Abstract Wireless local area networks have become vastly popular, and IEEE 802.11 is the chosen standard for almost all wireless devices. This standard specifies several modulation and channel coding techniques that must be implemented by all wireless interfaces to adapt to changes in wireless channels. As a result, these interfaces support multiple transmission data rates. However, this standard does not define how to dynamically select the appropriate data rate; instead, manufacturers can design and implement their own algorithms. Although several solutions have been proposed in the literature, only a few are used in practice. Moreover, their performance is still limited to specific conditions, such as highly dynamic environments. To tackle these challenges, this paper introduces CogTRA, which is a deployable mechanism built upon an existing cognitive framework called CogProt. Due to its self-adjustment functionality, CogTRA can work not only in stable but also in dynamic environments. It was implemented in the OpenWrt Linux distribution for embedded devices and evaluated through experiments using real network equipment. The results underline performance benefits with respect to existing data rate adaptation algorithms, with CogTRA exhibiting better performance especially in such dynamic networks. © The Brazilian Computer Society 2013
abstract_unstemmed	Abstract Wireless local area networks have become vastly popular, and IEEE 802.11 is the chosen standard for almost all wireless devices. This standard specifies several modulation and channel coding techniques that must be implemented by all wireless interfaces to adapt to changes in wireless channels. As a result, these interfaces support multiple transmission data rates. However, this standard does not define how to dynamically select the appropriate data rate; instead, manufacturers can design and implement their own algorithms. Although several solutions have been proposed in the literature, only a few are used in practice. Moreover, their performance is still limited to specific conditions, such as highly dynamic environments. To tackle these challenges, this paper introduces CogTRA, which is a deployable mechanism built upon an existing cognitive framework called CogProt. Due to its self-adjustment functionality, CogTRA can work not only in stable but also in dynamic environments. It was implemented in the OpenWrt Linux distribution for embedded devices and evaluated through experiments using real network equipment. The results underline performance benefits with respect to existing data rate adaptation algorithms, with CogTRA exhibiting better performance especially in such dynamic networks. © The Brazilian Computer Society 2013
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title_short	CogTRA: a deployable mechanism for cognitive transmission rate adaptation in IEEE 802.11 networks
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CogTRA: a deployable mechanism for cognitive transmission rate adaptation in IEEE 802.11 networks

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