Electromagnetic characterization of a computational asymmetric analysis for wireless networks

Abstract While sensor networks research for terrestrial applications has made significant strides in the past few years, the literature has relatively few examples of papers that have validated the feasibility and reliability issue, for the performance of Wireless Sensor Networks (WSNs) for undergro...
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Gespeichert in:

Autor*in:	Song, Young Seok [verfasserIn] Jeong, Taikyeong [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2014

Schlagwörter:	Sensor Node Wireless Sensor Network Dielectric Permittivity Receive Signal Strength Receive Signal Strength Indicator

Übergeordnetes Werk:	Enthalten in: Microsystem technologies - Berlin : Springer, 1994, 21(2014), 3 vom: 04. Apr., Seite 591-597
Übergeordnetes Werk:	volume:21 ; year:2014 ; number:3 ; day:04 ; month:04 ; pages:591-597

Links:	Volltext

DOI / URN:	10.1007/s00542-013-2051-1

Katalog-ID:	SPR00683289X

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520			\|a Abstract While sensor networks research for terrestrial applications has made significant strides in the past few years, the literature has relatively few examples of papers that have validated the feasibility and reliability issue, for the performance of Wireless Sensor Networks (WSNs) for underground applications. The propagation characteristics of electromagnetic (EM) waves in soil, and significant differences from propagation in air, prevent straightforward characterization of the underground wireless channel. Fundamentals, such as the dielectric permittivity and magnetic permeability, are required to solve the propagation of EM waves in soil. To this end, in this paper, we proposed a new model, Asymmetric Mixture Homogenization, based on the representative volume element concept, to characterize the dielectric permittivity of soil according to the composition of soil, and layout the foundation for efficient communication in this new environment. Further, in this paper we validated that with the latest wireless network system being used for terrestrial applications, challenges exists for the WSN to be used for underground applications. Experiments are performed to examine the link-level quality and received signal strength parameter between under-soil and above soil sensor nodes. The theoretical analysis and the experimental results prove the feasibility for the realization of WSN in underground applications.
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matchkey_str	article:14321858:2014----::lcrmgeicaatrztooaopttoaaymtiaay
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allfields	10.1007/s00542-013-2051-1 doi (DE-627)SPR00683289X (SPR)s00542-013-2051-1-e DE-627 ger DE-627 rakwb eng 510 ASE 50.94 bkl Song, Young Seok verfasserin aut Electromagnetic characterization of a computational asymmetric analysis for wireless networks 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract While sensor networks research for terrestrial applications has made significant strides in the past few years, the literature has relatively few examples of papers that have validated the feasibility and reliability issue, for the performance of Wireless Sensor Networks (WSNs) for underground applications. The propagation characteristics of electromagnetic (EM) waves in soil, and significant differences from propagation in air, prevent straightforward characterization of the underground wireless channel. Fundamentals, such as the dielectric permittivity and magnetic permeability, are required to solve the propagation of EM waves in soil. To this end, in this paper, we proposed a new model, Asymmetric Mixture Homogenization, based on the representative volume element concept, to characterize the dielectric permittivity of soil according to the composition of soil, and layout the foundation for efficient communication in this new environment. Further, in this paper we validated that with the latest wireless network system being used for terrestrial applications, challenges exists for the WSN to be used for underground applications. Experiments are performed to examine the link-level quality and received signal strength parameter between under-soil and above soil sensor nodes. The theoretical analysis and the experimental results prove the feasibility for the realization of WSN in underground applications. Sensor Node (dpeaa)DE-He213 Wireless Sensor Network (dpeaa)DE-He213 Dielectric Permittivity (dpeaa)DE-He213 Receive Signal Strength (dpeaa)DE-He213 Receive Signal Strength Indicator (dpeaa)DE-He213 Jeong, Taikyeong verfasserin aut Enthalten in Microsystem technologies Berlin : Springer, 1994 21(2014), 3 vom: 04. Apr., Seite 591-597 (DE-627)270128182 (DE-600)1476561-5 1432-1858 nnns volume:21 year:2014 number:3 day:04 month:04 pages:591-597 https://dx.doi.org/10.1007/s00542-013-2051-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.94 ASE AR 21 2014 3 04 04 591-597
spelling	10.1007/s00542-013-2051-1 doi (DE-627)SPR00683289X (SPR)s00542-013-2051-1-e DE-627 ger DE-627 rakwb eng 510 ASE 50.94 bkl Song, Young Seok verfasserin aut Electromagnetic characterization of a computational asymmetric analysis for wireless networks 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract While sensor networks research for terrestrial applications has made significant strides in the past few years, the literature has relatively few examples of papers that have validated the feasibility and reliability issue, for the performance of Wireless Sensor Networks (WSNs) for underground applications. The propagation characteristics of electromagnetic (EM) waves in soil, and significant differences from propagation in air, prevent straightforward characterization of the underground wireless channel. Fundamentals, such as the dielectric permittivity and magnetic permeability, are required to solve the propagation of EM waves in soil. To this end, in this paper, we proposed a new model, Asymmetric Mixture Homogenization, based on the representative volume element concept, to characterize the dielectric permittivity of soil according to the composition of soil, and layout the foundation for efficient communication in this new environment. Further, in this paper we validated that with the latest wireless network system being used for terrestrial applications, challenges exists for the WSN to be used for underground applications. Experiments are performed to examine the link-level quality and received signal strength parameter between under-soil and above soil sensor nodes. The theoretical analysis and the experimental results prove the feasibility for the realization of WSN in underground applications. Sensor Node (dpeaa)DE-He213 Wireless Sensor Network (dpeaa)DE-He213 Dielectric Permittivity (dpeaa)DE-He213 Receive Signal Strength (dpeaa)DE-He213 Receive Signal Strength Indicator (dpeaa)DE-He213 Jeong, Taikyeong verfasserin aut Enthalten in Microsystem technologies Berlin : Springer, 1994 21(2014), 3 vom: 04. Apr., Seite 591-597 (DE-627)270128182 (DE-600)1476561-5 1432-1858 nnns volume:21 year:2014 number:3 day:04 month:04 pages:591-597 https://dx.doi.org/10.1007/s00542-013-2051-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.94 ASE AR 21 2014 3 04 04 591-597
allfields_unstemmed	10.1007/s00542-013-2051-1 doi (DE-627)SPR00683289X (SPR)s00542-013-2051-1-e DE-627 ger DE-627 rakwb eng 510 ASE 50.94 bkl Song, Young Seok verfasserin aut Electromagnetic characterization of a computational asymmetric analysis for wireless networks 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract While sensor networks research for terrestrial applications has made significant strides in the past few years, the literature has relatively few examples of papers that have validated the feasibility and reliability issue, for the performance of Wireless Sensor Networks (WSNs) for underground applications. The propagation characteristics of electromagnetic (EM) waves in soil, and significant differences from propagation in air, prevent straightforward characterization of the underground wireless channel. Fundamentals, such as the dielectric permittivity and magnetic permeability, are required to solve the propagation of EM waves in soil. To this end, in this paper, we proposed a new model, Asymmetric Mixture Homogenization, based on the representative volume element concept, to characterize the dielectric permittivity of soil according to the composition of soil, and layout the foundation for efficient communication in this new environment. Further, in this paper we validated that with the latest wireless network system being used for terrestrial applications, challenges exists for the WSN to be used for underground applications. Experiments are performed to examine the link-level quality and received signal strength parameter between under-soil and above soil sensor nodes. The theoretical analysis and the experimental results prove the feasibility for the realization of WSN in underground applications. Sensor Node (dpeaa)DE-He213 Wireless Sensor Network (dpeaa)DE-He213 Dielectric Permittivity (dpeaa)DE-He213 Receive Signal Strength (dpeaa)DE-He213 Receive Signal Strength Indicator (dpeaa)DE-He213 Jeong, Taikyeong verfasserin aut Enthalten in Microsystem technologies Berlin : Springer, 1994 21(2014), 3 vom: 04. Apr., Seite 591-597 (DE-627)270128182 (DE-600)1476561-5 1432-1858 nnns volume:21 year:2014 number:3 day:04 month:04 pages:591-597 https://dx.doi.org/10.1007/s00542-013-2051-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.94 ASE AR 21 2014 3 04 04 591-597
allfieldsGer	10.1007/s00542-013-2051-1 doi (DE-627)SPR00683289X (SPR)s00542-013-2051-1-e DE-627 ger DE-627 rakwb eng 510 ASE 50.94 bkl Song, Young Seok verfasserin aut Electromagnetic characterization of a computational asymmetric analysis for wireless networks 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract While sensor networks research for terrestrial applications has made significant strides in the past few years, the literature has relatively few examples of papers that have validated the feasibility and reliability issue, for the performance of Wireless Sensor Networks (WSNs) for underground applications. The propagation characteristics of electromagnetic (EM) waves in soil, and significant differences from propagation in air, prevent straightforward characterization of the underground wireless channel. Fundamentals, such as the dielectric permittivity and magnetic permeability, are required to solve the propagation of EM waves in soil. To this end, in this paper, we proposed a new model, Asymmetric Mixture Homogenization, based on the representative volume element concept, to characterize the dielectric permittivity of soil according to the composition of soil, and layout the foundation for efficient communication in this new environment. Further, in this paper we validated that with the latest wireless network system being used for terrestrial applications, challenges exists for the WSN to be used for underground applications. Experiments are performed to examine the link-level quality and received signal strength parameter between under-soil and above soil sensor nodes. The theoretical analysis and the experimental results prove the feasibility for the realization of WSN in underground applications. Sensor Node (dpeaa)DE-He213 Wireless Sensor Network (dpeaa)DE-He213 Dielectric Permittivity (dpeaa)DE-He213 Receive Signal Strength (dpeaa)DE-He213 Receive Signal Strength Indicator (dpeaa)DE-He213 Jeong, Taikyeong verfasserin aut Enthalten in Microsystem technologies Berlin : Springer, 1994 21(2014), 3 vom: 04. Apr., Seite 591-597 (DE-627)270128182 (DE-600)1476561-5 1432-1858 nnns volume:21 year:2014 number:3 day:04 month:04 pages:591-597 https://dx.doi.org/10.1007/s00542-013-2051-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.94 ASE AR 21 2014 3 04 04 591-597
allfieldsSound	10.1007/s00542-013-2051-1 doi (DE-627)SPR00683289X (SPR)s00542-013-2051-1-e DE-627 ger DE-627 rakwb eng 510 ASE 50.94 bkl Song, Young Seok verfasserin aut Electromagnetic characterization of a computational asymmetric analysis for wireless networks 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract While sensor networks research for terrestrial applications has made significant strides in the past few years, the literature has relatively few examples of papers that have validated the feasibility and reliability issue, for the performance of Wireless Sensor Networks (WSNs) for underground applications. The propagation characteristics of electromagnetic (EM) waves in soil, and significant differences from propagation in air, prevent straightforward characterization of the underground wireless channel. Fundamentals, such as the dielectric permittivity and magnetic permeability, are required to solve the propagation of EM waves in soil. To this end, in this paper, we proposed a new model, Asymmetric Mixture Homogenization, based on the representative volume element concept, to characterize the dielectric permittivity of soil according to the composition of soil, and layout the foundation for efficient communication in this new environment. Further, in this paper we validated that with the latest wireless network system being used for terrestrial applications, challenges exists for the WSN to be used for underground applications. Experiments are performed to examine the link-level quality and received signal strength parameter between under-soil and above soil sensor nodes. The theoretical analysis and the experimental results prove the feasibility for the realization of WSN in underground applications. Sensor Node (dpeaa)DE-He213 Wireless Sensor Network (dpeaa)DE-He213 Dielectric Permittivity (dpeaa)DE-He213 Receive Signal Strength (dpeaa)DE-He213 Receive Signal Strength Indicator (dpeaa)DE-He213 Jeong, Taikyeong verfasserin aut Enthalten in Microsystem technologies Berlin : Springer, 1994 21(2014), 3 vom: 04. Apr., Seite 591-597 (DE-627)270128182 (DE-600)1476561-5 1432-1858 nnns volume:21 year:2014 number:3 day:04 month:04 pages:591-597 https://dx.doi.org/10.1007/s00542-013-2051-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.94 ASE AR 21 2014 3 04 04 591-597
language	English
source	Enthalten in Microsystem technologies 21(2014), 3 vom: 04. Apr., Seite 591-597 volume:21 year:2014 number:3 day:04 month:04 pages:591-597
sourceStr	Enthalten in Microsystem technologies 21(2014), 3 vom: 04. Apr., Seite 591-597 volume:21 year:2014 number:3 day:04 month:04 pages:591-597
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Sensor Node Wireless Sensor Network Dielectric Permittivity Receive Signal Strength Receive Signal Strength Indicator
dewey-raw	510
isfreeaccess_bool	false
container_title	Microsystem technologies
authorswithroles_txt_mv	Song, Young Seok @@aut@@ Jeong, Taikyeong @@aut@@
publishDateDaySort_date	2014-04-04T00:00:00Z
hierarchy_top_id	270128182
dewey-sort	3510
id	SPR00683289X
language_de	englisch
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author	Song, Young Seok
spellingShingle	Song, Young Seok ddc 510 bkl 50.94 misc Sensor Node misc Wireless Sensor Network misc Dielectric Permittivity misc Receive Signal Strength misc Receive Signal Strength Indicator Electromagnetic characterization of a computational asymmetric analysis for wireless networks
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topic_title	510 ASE 50.94 bkl Electromagnetic characterization of a computational asymmetric analysis for wireless networks Sensor Node (dpeaa)DE-He213 Wireless Sensor Network (dpeaa)DE-He213 Dielectric Permittivity (dpeaa)DE-He213 Receive Signal Strength (dpeaa)DE-He213 Receive Signal Strength Indicator (dpeaa)DE-He213
topic	ddc 510 bkl 50.94 misc Sensor Node misc Wireless Sensor Network misc Dielectric Permittivity misc Receive Signal Strength misc Receive Signal Strength Indicator
topic_unstemmed	ddc 510 bkl 50.94 misc Sensor Node misc Wireless Sensor Network misc Dielectric Permittivity misc Receive Signal Strength misc Receive Signal Strength Indicator
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title	Electromagnetic characterization of a computational asymmetric analysis for wireless networks
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title_full	Electromagnetic characterization of a computational asymmetric analysis for wireless networks
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title_sort	electromagnetic characterization of a computational asymmetric analysis for wireless networks
title_auth	Electromagnetic characterization of a computational asymmetric analysis for wireless networks
abstract	Abstract While sensor networks research for terrestrial applications has made significant strides in the past few years, the literature has relatively few examples of papers that have validated the feasibility and reliability issue, for the performance of Wireless Sensor Networks (WSNs) for underground applications. The propagation characteristics of electromagnetic (EM) waves in soil, and significant differences from propagation in air, prevent straightforward characterization of the underground wireless channel. Fundamentals, such as the dielectric permittivity and magnetic permeability, are required to solve the propagation of EM waves in soil. To this end, in this paper, we proposed a new model, Asymmetric Mixture Homogenization, based on the representative volume element concept, to characterize the dielectric permittivity of soil according to the composition of soil, and layout the foundation for efficient communication in this new environment. Further, in this paper we validated that with the latest wireless network system being used for terrestrial applications, challenges exists for the WSN to be used for underground applications. Experiments are performed to examine the link-level quality and received signal strength parameter between under-soil and above soil sensor nodes. The theoretical analysis and the experimental results prove the feasibility for the realization of WSN in underground applications.
abstractGer	Abstract While sensor networks research for terrestrial applications has made significant strides in the past few years, the literature has relatively few examples of papers that have validated the feasibility and reliability issue, for the performance of Wireless Sensor Networks (WSNs) for underground applications. The propagation characteristics of electromagnetic (EM) waves in soil, and significant differences from propagation in air, prevent straightforward characterization of the underground wireless channel. Fundamentals, such as the dielectric permittivity and magnetic permeability, are required to solve the propagation of EM waves in soil. To this end, in this paper, we proposed a new model, Asymmetric Mixture Homogenization, based on the representative volume element concept, to characterize the dielectric permittivity of soil according to the composition of soil, and layout the foundation for efficient communication in this new environment. Further, in this paper we validated that with the latest wireless network system being used for terrestrial applications, challenges exists for the WSN to be used for underground applications. Experiments are performed to examine the link-level quality and received signal strength parameter between under-soil and above soil sensor nodes. The theoretical analysis and the experimental results prove the feasibility for the realization of WSN in underground applications.
abstract_unstemmed	Abstract While sensor networks research for terrestrial applications has made significant strides in the past few years, the literature has relatively few examples of papers that have validated the feasibility and reliability issue, for the performance of Wireless Sensor Networks (WSNs) for underground applications. The propagation characteristics of electromagnetic (EM) waves in soil, and significant differences from propagation in air, prevent straightforward characterization of the underground wireless channel. Fundamentals, such as the dielectric permittivity and magnetic permeability, are required to solve the propagation of EM waves in soil. To this end, in this paper, we proposed a new model, Asymmetric Mixture Homogenization, based on the representative volume element concept, to characterize the dielectric permittivity of soil according to the composition of soil, and layout the foundation for efficient communication in this new environment. Further, in this paper we validated that with the latest wireless network system being used for terrestrial applications, challenges exists for the WSN to be used for underground applications. Experiments are performed to examine the link-level quality and received signal strength parameter between under-soil and above soil sensor nodes. The theoretical analysis and the experimental results prove the feasibility for the realization of WSN in underground applications.
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container_issue	3
title_short	Electromagnetic characterization of a computational asymmetric analysis for wireless networks
url	https://dx.doi.org/10.1007/s00542-013-2051-1
remote_bool	true
author2	Jeong, Taikyeong
author2Str	Jeong, Taikyeong
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doi_str	10.1007/s00542-013-2051-1
up_date	2024-07-04T00:52:41.820Z
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Electromagnetic characterization of a computational asymmetric analysis for wireless networks

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