Fuzzy Logic-Based Directional Location Routing in Vehicular Ad Hoc Network
Abstract The vehicular ad hoc network (VANET) is an autonomous system of mobile vehicles where mobile vehicles can transmit or receive data packet over the wireless link. Due to the movable nature and limited communication, range of vehicles causes breaking the link between them very frequently, whi...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Rana, Kamlesh Kumar [verfasserIn] Tripathi, Sachin [verfasserIn] Raw, Ram Shringar [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Proceedings of the National Academy of Sciences - New York, NY : Springer, 2012, 91(2019), 1 vom: 26. Okt., Seite 135-146 |
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| Übergeordnetes Werk: |
volume:91 ; year:2019 ; number:1 ; day:26 ; month:10 ; pages:135-146 |
| Links: |
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| DOI / URN: |
10.1007/s40010-019-00641-4 |
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| Katalog-ID: |
SPR043352987 |
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| 245 | 1 | 0 | |a Fuzzy Logic-Based Directional Location Routing in Vehicular Ad Hoc Network |
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| 520 | |a Abstract The vehicular ad hoc network (VANET) is an autonomous system of mobile vehicles where mobile vehicles can transmit or receive data packet over the wireless link. Due to the movable nature and limited communication, range of vehicles causes breaking the link between them very frequently, which in turn causes failure in the data delivery. Therefore, a stable path should be established from the source to the destination node to deliver data packets at the intended destination node. Therefore, for a stable route from source to the destination node selection of the next hop should be appropriate. The proposed work in this paper has been made to discuss how the best next hop node can be selected to deliver data packet successfully at the destination node D. A mathematical model fuzzy logic-based directional location routing (FLDLR) has been proposed to select a remarkable next hop node in the VANET. To select next hop, FLDLR has considered fuzzy logic sets of the routing metrics, i.e., next hop distance, node speed, closeness, the data transmission rate of the node, and node movement direction. To investigate the performance of FLDLR, the simulation work has been done through network simulator-2 and compared with existing LAR and D-LAR protocols. Through simulated results has shown that the FLDLR outperforms existing protocols from the standpoints routing overhead and packet delivery delay. | ||
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| 650 | 4 | |a D-LAR |7 (dpeaa)DE-He213 | |
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| 700 | 1 | |a Tripathi, Sachin |e verfasserin |4 aut | |
| 700 | 1 | |a Raw, Ram Shringar |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Proceedings of the National Academy of Sciences |d New York, NY : Springer, 2012 |g 91(2019), 1 vom: 26. Okt., Seite 135-146 |w (DE-627)73921358X |w (DE-600)2707742-1 |x 2250-1762 |7 nnns |
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10.1007/s40010-019-00641-4 doi (DE-627)SPR043352987 (DE-599)SPRs40010-019-00641-4-e (SPR)s40010-019-00641-4-e DE-627 ger DE-627 rakwb eng Rana, Kamlesh Kumar verfasserin aut Fuzzy Logic-Based Directional Location Routing in Vehicular Ad Hoc Network 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The vehicular ad hoc network (VANET) is an autonomous system of mobile vehicles where mobile vehicles can transmit or receive data packet over the wireless link. Due to the movable nature and limited communication, range of vehicles causes breaking the link between them very frequently, which in turn causes failure in the data delivery. Therefore, a stable path should be established from the source to the destination node to deliver data packets at the intended destination node. Therefore, for a stable route from source to the destination node selection of the next hop should be appropriate. The proposed work in this paper has been made to discuss how the best next hop node can be selected to deliver data packet successfully at the destination node D. A mathematical model fuzzy logic-based directional location routing (FLDLR) has been proposed to select a remarkable next hop node in the VANET. To select next hop, FLDLR has considered fuzzy logic sets of the routing metrics, i.e., next hop distance, node speed, closeness, the data transmission rate of the node, and node movement direction. To investigate the performance of FLDLR, the simulation work has been done through network simulator-2 and compared with existing LAR and D-LAR protocols. Through simulated results has shown that the FLDLR outperforms existing protocols from the standpoints routing overhead and packet delivery delay. VANET (dpeaa)DE-He213 FLDLR (dpeaa)DE-He213 Next hop (dpeaa)DE-He213 Fuzzy logic (dpeaa)DE-He213 D-LAR (dpeaa)DE-He213 LAR (dpeaa)DE-He213 Tripathi, Sachin verfasserin aut Raw, Ram Shringar verfasserin aut Enthalten in Proceedings of the National Academy of Sciences New York, NY : Springer, 2012 91(2019), 1 vom: 26. Okt., Seite 135-146 (DE-627)73921358X (DE-600)2707742-1 2250-1762 nnns volume:91 year:2019 number:1 day:26 month:10 pages:135-146 https://dx.doi.org/10.1007/s40010-019-00641-4 lizenzpflichtig 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_32 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_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_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 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_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 AR 91 2019 1 26 10 135-146 |
| spelling |
10.1007/s40010-019-00641-4 doi (DE-627)SPR043352987 (DE-599)SPRs40010-019-00641-4-e (SPR)s40010-019-00641-4-e DE-627 ger DE-627 rakwb eng Rana, Kamlesh Kumar verfasserin aut Fuzzy Logic-Based Directional Location Routing in Vehicular Ad Hoc Network 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The vehicular ad hoc network (VANET) is an autonomous system of mobile vehicles where mobile vehicles can transmit or receive data packet over the wireless link. Due to the movable nature and limited communication, range of vehicles causes breaking the link between them very frequently, which in turn causes failure in the data delivery. Therefore, a stable path should be established from the source to the destination node to deliver data packets at the intended destination node. Therefore, for a stable route from source to the destination node selection of the next hop should be appropriate. The proposed work in this paper has been made to discuss how the best next hop node can be selected to deliver data packet successfully at the destination node D. A mathematical model fuzzy logic-based directional location routing (FLDLR) has been proposed to select a remarkable next hop node in the VANET. To select next hop, FLDLR has considered fuzzy logic sets of the routing metrics, i.e., next hop distance, node speed, closeness, the data transmission rate of the node, and node movement direction. To investigate the performance of FLDLR, the simulation work has been done through network simulator-2 and compared with existing LAR and D-LAR protocols. Through simulated results has shown that the FLDLR outperforms existing protocols from the standpoints routing overhead and packet delivery delay. VANET (dpeaa)DE-He213 FLDLR (dpeaa)DE-He213 Next hop (dpeaa)DE-He213 Fuzzy logic (dpeaa)DE-He213 D-LAR (dpeaa)DE-He213 LAR (dpeaa)DE-He213 Tripathi, Sachin verfasserin aut Raw, Ram Shringar verfasserin aut Enthalten in Proceedings of the National Academy of Sciences New York, NY : Springer, 2012 91(2019), 1 vom: 26. Okt., Seite 135-146 (DE-627)73921358X (DE-600)2707742-1 2250-1762 nnns volume:91 year:2019 number:1 day:26 month:10 pages:135-146 https://dx.doi.org/10.1007/s40010-019-00641-4 lizenzpflichtig 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_32 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_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_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 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_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 AR 91 2019 1 26 10 135-146 |
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10.1007/s40010-019-00641-4 doi (DE-627)SPR043352987 (DE-599)SPRs40010-019-00641-4-e (SPR)s40010-019-00641-4-e DE-627 ger DE-627 rakwb eng Rana, Kamlesh Kumar verfasserin aut Fuzzy Logic-Based Directional Location Routing in Vehicular Ad Hoc Network 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The vehicular ad hoc network (VANET) is an autonomous system of mobile vehicles where mobile vehicles can transmit or receive data packet over the wireless link. Due to the movable nature and limited communication, range of vehicles causes breaking the link between them very frequently, which in turn causes failure in the data delivery. Therefore, a stable path should be established from the source to the destination node to deliver data packets at the intended destination node. Therefore, for a stable route from source to the destination node selection of the next hop should be appropriate. The proposed work in this paper has been made to discuss how the best next hop node can be selected to deliver data packet successfully at the destination node D. A mathematical model fuzzy logic-based directional location routing (FLDLR) has been proposed to select a remarkable next hop node in the VANET. To select next hop, FLDLR has considered fuzzy logic sets of the routing metrics, i.e., next hop distance, node speed, closeness, the data transmission rate of the node, and node movement direction. To investigate the performance of FLDLR, the simulation work has been done through network simulator-2 and compared with existing LAR and D-LAR protocols. Through simulated results has shown that the FLDLR outperforms existing protocols from the standpoints routing overhead and packet delivery delay. VANET (dpeaa)DE-He213 FLDLR (dpeaa)DE-He213 Next hop (dpeaa)DE-He213 Fuzzy logic (dpeaa)DE-He213 D-LAR (dpeaa)DE-He213 LAR (dpeaa)DE-He213 Tripathi, Sachin verfasserin aut Raw, Ram Shringar verfasserin aut Enthalten in Proceedings of the National Academy of Sciences New York, NY : Springer, 2012 91(2019), 1 vom: 26. Okt., Seite 135-146 (DE-627)73921358X (DE-600)2707742-1 2250-1762 nnns volume:91 year:2019 number:1 day:26 month:10 pages:135-146 https://dx.doi.org/10.1007/s40010-019-00641-4 lizenzpflichtig 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_32 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_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_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 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_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 AR 91 2019 1 26 10 135-146 |
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10.1007/s40010-019-00641-4 doi (DE-627)SPR043352987 (DE-599)SPRs40010-019-00641-4-e (SPR)s40010-019-00641-4-e DE-627 ger DE-627 rakwb eng Rana, Kamlesh Kumar verfasserin aut Fuzzy Logic-Based Directional Location Routing in Vehicular Ad Hoc Network 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The vehicular ad hoc network (VANET) is an autonomous system of mobile vehicles where mobile vehicles can transmit or receive data packet over the wireless link. Due to the movable nature and limited communication, range of vehicles causes breaking the link between them very frequently, which in turn causes failure in the data delivery. Therefore, a stable path should be established from the source to the destination node to deliver data packets at the intended destination node. Therefore, for a stable route from source to the destination node selection of the next hop should be appropriate. The proposed work in this paper has been made to discuss how the best next hop node can be selected to deliver data packet successfully at the destination node D. A mathematical model fuzzy logic-based directional location routing (FLDLR) has been proposed to select a remarkable next hop node in the VANET. To select next hop, FLDLR has considered fuzzy logic sets of the routing metrics, i.e., next hop distance, node speed, closeness, the data transmission rate of the node, and node movement direction. To investigate the performance of FLDLR, the simulation work has been done through network simulator-2 and compared with existing LAR and D-LAR protocols. Through simulated results has shown that the FLDLR outperforms existing protocols from the standpoints routing overhead and packet delivery delay. VANET (dpeaa)DE-He213 FLDLR (dpeaa)DE-He213 Next hop (dpeaa)DE-He213 Fuzzy logic (dpeaa)DE-He213 D-LAR (dpeaa)DE-He213 LAR (dpeaa)DE-He213 Tripathi, Sachin verfasserin aut Raw, Ram Shringar verfasserin aut Enthalten in Proceedings of the National Academy of Sciences New York, NY : Springer, 2012 91(2019), 1 vom: 26. Okt., Seite 135-146 (DE-627)73921358X (DE-600)2707742-1 2250-1762 nnns volume:91 year:2019 number:1 day:26 month:10 pages:135-146 https://dx.doi.org/10.1007/s40010-019-00641-4 lizenzpflichtig 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_32 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_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_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 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_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 AR 91 2019 1 26 10 135-146 |
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10.1007/s40010-019-00641-4 doi (DE-627)SPR043352987 (DE-599)SPRs40010-019-00641-4-e (SPR)s40010-019-00641-4-e DE-627 ger DE-627 rakwb eng Rana, Kamlesh Kumar verfasserin aut Fuzzy Logic-Based Directional Location Routing in Vehicular Ad Hoc Network 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The vehicular ad hoc network (VANET) is an autonomous system of mobile vehicles where mobile vehicles can transmit or receive data packet over the wireless link. Due to the movable nature and limited communication, range of vehicles causes breaking the link between them very frequently, which in turn causes failure in the data delivery. Therefore, a stable path should be established from the source to the destination node to deliver data packets at the intended destination node. Therefore, for a stable route from source to the destination node selection of the next hop should be appropriate. The proposed work in this paper has been made to discuss how the best next hop node can be selected to deliver data packet successfully at the destination node D. A mathematical model fuzzy logic-based directional location routing (FLDLR) has been proposed to select a remarkable next hop node in the VANET. To select next hop, FLDLR has considered fuzzy logic sets of the routing metrics, i.e., next hop distance, node speed, closeness, the data transmission rate of the node, and node movement direction. To investigate the performance of FLDLR, the simulation work has been done through network simulator-2 and compared with existing LAR and D-LAR protocols. Through simulated results has shown that the FLDLR outperforms existing protocols from the standpoints routing overhead and packet delivery delay. VANET (dpeaa)DE-He213 FLDLR (dpeaa)DE-He213 Next hop (dpeaa)DE-He213 Fuzzy logic (dpeaa)DE-He213 D-LAR (dpeaa)DE-He213 LAR (dpeaa)DE-He213 Tripathi, Sachin verfasserin aut Raw, Ram Shringar verfasserin aut Enthalten in Proceedings of the National Academy of Sciences New York, NY : Springer, 2012 91(2019), 1 vom: 26. Okt., Seite 135-146 (DE-627)73921358X (DE-600)2707742-1 2250-1762 nnns volume:91 year:2019 number:1 day:26 month:10 pages:135-146 https://dx.doi.org/10.1007/s40010-019-00641-4 lizenzpflichtig 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_32 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_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_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 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_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 AR 91 2019 1 26 10 135-146 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">SPR043352987</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20210228064733.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">210228s2019 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s40010-019-00641-4</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR043352987</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)SPRs40010-019-00641-4-e</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s40010-019-00641-4-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Rana, Kamlesh Kumar</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Fuzzy Logic-Based Directional Location Routing in Vehicular Ad Hoc Network</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2019</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract The vehicular ad hoc network (VANET) is an autonomous system of mobile vehicles where mobile vehicles can transmit or receive data packet over the wireless link. Due to the movable nature and limited communication, range of vehicles causes breaking the link between them very frequently, which in turn causes failure in the data delivery. Therefore, a stable path should be established from the source to the destination node to deliver data packets at the intended destination node. Therefore, for a stable route from source to the destination node selection of the next hop should be appropriate. The proposed work in this paper has been made to discuss how the best next hop node can be selected to deliver data packet successfully at the destination node D. A mathematical model fuzzy logic-based directional location routing (FLDLR) has been proposed to select a remarkable next hop node in the VANET. To select next hop, FLDLR has considered fuzzy logic sets of the routing metrics, i.e., next hop distance, node speed, closeness, the data transmission rate of the node, and node movement direction. To investigate the performance of FLDLR, the simulation work has been done through network simulator-2 and compared with existing LAR and D-LAR protocols. 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| author |
Rana, Kamlesh Kumar |
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Rana, Kamlesh Kumar misc VANET misc FLDLR misc Next hop misc Fuzzy logic misc D-LAR misc LAR Fuzzy Logic-Based Directional Location Routing in Vehicular Ad Hoc Network |
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Fuzzy Logic-Based Directional Location Routing in Vehicular Ad Hoc Network VANET (dpeaa)DE-He213 FLDLR (dpeaa)DE-He213 Next hop (dpeaa)DE-He213 Fuzzy logic (dpeaa)DE-He213 D-LAR (dpeaa)DE-He213 LAR (dpeaa)DE-He213 |
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misc VANET misc FLDLR misc Next hop misc Fuzzy logic misc D-LAR misc LAR |
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Fuzzy Logic-Based Directional Location Routing in Vehicular Ad Hoc Network |
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fuzzy logic-based directional location routing in vehicular ad hoc network |
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Fuzzy Logic-Based Directional Location Routing in Vehicular Ad Hoc Network |
| abstract |
Abstract The vehicular ad hoc network (VANET) is an autonomous system of mobile vehicles where mobile vehicles can transmit or receive data packet over the wireless link. Due to the movable nature and limited communication, range of vehicles causes breaking the link between them very frequently, which in turn causes failure in the data delivery. Therefore, a stable path should be established from the source to the destination node to deliver data packets at the intended destination node. Therefore, for a stable route from source to the destination node selection of the next hop should be appropriate. The proposed work in this paper has been made to discuss how the best next hop node can be selected to deliver data packet successfully at the destination node D. A mathematical model fuzzy logic-based directional location routing (FLDLR) has been proposed to select a remarkable next hop node in the VANET. To select next hop, FLDLR has considered fuzzy logic sets of the routing metrics, i.e., next hop distance, node speed, closeness, the data transmission rate of the node, and node movement direction. To investigate the performance of FLDLR, the simulation work has been done through network simulator-2 and compared with existing LAR and D-LAR protocols. Through simulated results has shown that the FLDLR outperforms existing protocols from the standpoints routing overhead and packet delivery delay. |
| abstractGer |
Abstract The vehicular ad hoc network (VANET) is an autonomous system of mobile vehicles where mobile vehicles can transmit or receive data packet over the wireless link. Due to the movable nature and limited communication, range of vehicles causes breaking the link between them very frequently, which in turn causes failure in the data delivery. Therefore, a stable path should be established from the source to the destination node to deliver data packets at the intended destination node. Therefore, for a stable route from source to the destination node selection of the next hop should be appropriate. The proposed work in this paper has been made to discuss how the best next hop node can be selected to deliver data packet successfully at the destination node D. A mathematical model fuzzy logic-based directional location routing (FLDLR) has been proposed to select a remarkable next hop node in the VANET. To select next hop, FLDLR has considered fuzzy logic sets of the routing metrics, i.e., next hop distance, node speed, closeness, the data transmission rate of the node, and node movement direction. To investigate the performance of FLDLR, the simulation work has been done through network simulator-2 and compared with existing LAR and D-LAR protocols. Through simulated results has shown that the FLDLR outperforms existing protocols from the standpoints routing overhead and packet delivery delay. |
| abstract_unstemmed |
Abstract The vehicular ad hoc network (VANET) is an autonomous system of mobile vehicles where mobile vehicles can transmit or receive data packet over the wireless link. Due to the movable nature and limited communication, range of vehicles causes breaking the link between them very frequently, which in turn causes failure in the data delivery. Therefore, a stable path should be established from the source to the destination node to deliver data packets at the intended destination node. Therefore, for a stable route from source to the destination node selection of the next hop should be appropriate. The proposed work in this paper has been made to discuss how the best next hop node can be selected to deliver data packet successfully at the destination node D. A mathematical model fuzzy logic-based directional location routing (FLDLR) has been proposed to select a remarkable next hop node in the VANET. To select next hop, FLDLR has considered fuzzy logic sets of the routing metrics, i.e., next hop distance, node speed, closeness, the data transmission rate of the node, and node movement direction. To investigate the performance of FLDLR, the simulation work has been done through network simulator-2 and compared with existing LAR and D-LAR protocols. Through simulated results has shown that the FLDLR outperforms existing protocols from the standpoints routing overhead and packet delivery delay. |
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1 |
| title_short |
Fuzzy Logic-Based Directional Location Routing in Vehicular Ad Hoc Network |
| url |
https://dx.doi.org/10.1007/s40010-019-00641-4 |
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true |
| author2 |
Tripathi, Sachin Raw, Ram Shringar |
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Tripathi, Sachin Raw, Ram Shringar |
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| doi_str |
10.1007/s40010-019-00641-4 |
| up_date |
2024-07-03T18:07:14.927Z |
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| score |
7.3996553 |