A new energy‐aware method for load balance managing in the fog‐based vehicular ad hoc networks (VANET) using a hybrid optimization algorithm

Abstract Fog‐based VANETs (Vehicular Ad hoc NETworks) is a new model with vehicular cloud and fog computing benefits. Fog‐based VANETs consist of a series of mobile nodes that are fully dynamic without any central management. These networks have some limitations due to the use of the mobile power so...
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Autor*in:	Ren Qun [verfasserIn] Seyedeh Maryam Arefzadeh [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	Communication network design, planning and routing Computer communications Mobile radio systems Optimisation techniques Other computer networks

Übergeordnetes Werk:	In: IET Communications - Wiley, 2021, 15(2021), 13, Seite 1665-1676
Übergeordnetes Werk:	volume:15 ; year:2021 ; number:13 ; pages:1665-1676

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.1049/cmu2.12179

Katalog-ID:	DOAJ039615014

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520			\|a Abstract Fog‐based VANETs (Vehicular Ad hoc NETworks) is a new model with vehicular cloud and fog computing benefits. Fog‐based VANETs consist of a series of mobile nodes that are fully dynamic without any central management. These networks have some limitations due to the use of the mobile power source. There are many challenges in extending mobile‐based networks' life span. Many methods have been suggested to minimize the nodes' energy consumption and extend the network life. Also, some works have been developed for load‐balanced routing. Still, energy‐efficient routing and load balancing in VANETs are challenges. The purpose of this study is to present a suitable method based on energy awareness for load balancing in fog‐based VANETs using a hybrid optimization algorithm (employing ant colony optimization and artificial bee colony (ACO‐ABC)). The simulation results in the Network Simulator 2 (NS2) environment showed that as the number of nodes increased, the consumed amount of energy in the VANET is increased. Also, with the increasing number of tasks, load balancing by the proposed method has been improved. Finally, the simulation experiments showed that the proposed hybrid algorithm (ACO‐ABC) outperforms all other algorithms.
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allfields	10.1049/cmu2.12179 doi (DE-627)DOAJ039615014 (DE-599)DOAJccd31399139a4e4ab580d60749d90b0f DE-627 ger DE-627 rakwb eng TK5101-6720 Ren Qun verfasserin aut A new energy‐aware method for load balance managing in the fog‐based vehicular ad hoc networks (VANET) using a hybrid optimization algorithm 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Fog‐based VANETs (Vehicular Ad hoc NETworks) is a new model with vehicular cloud and fog computing benefits. Fog‐based VANETs consist of a series of mobile nodes that are fully dynamic without any central management. These networks have some limitations due to the use of the mobile power source. There are many challenges in extending mobile‐based networks' life span. Many methods have been suggested to minimize the nodes' energy consumption and extend the network life. Also, some works have been developed for load‐balanced routing. Still, energy‐efficient routing and load balancing in VANETs are challenges. The purpose of this study is to present a suitable method based on energy awareness for load balancing in fog‐based VANETs using a hybrid optimization algorithm (employing ant colony optimization and artificial bee colony (ACO‐ABC)). The simulation results in the Network Simulator 2 (NS2) environment showed that as the number of nodes increased, the consumed amount of energy in the VANET is increased. Also, with the increasing number of tasks, load balancing by the proposed method has been improved. Finally, the simulation experiments showed that the proposed hybrid algorithm (ACO‐ABC) outperforms all other algorithms. Communication network design, planning and routing Computer communications Mobile radio systems Optimisation techniques Other computer networks Telecommunication Seyedeh Maryam Arefzadeh verfasserin aut In IET Communications Wiley, 2021 15(2021), 13, Seite 1665-1676 (DE-627)521691621 (DE-600)2264240-7 17518636 nnns volume:15 year:2021 number:13 pages:1665-1676 https://doi.org/10.1049/cmu2.12179 kostenfrei https://doaj.org/article/ccd31399139a4e4ab580d60749d90b0f kostenfrei https://doi.org/10.1049/cmu2.12179 kostenfrei https://doaj.org/toc/1751-8628 Journal toc kostenfrei https://doaj.org/toc/1751-8636 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 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_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 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_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 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_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4367 GBV_ILN_4393 GBV_ILN_4700 AR 15 2021 13 1665-1676
spelling	10.1049/cmu2.12179 doi (DE-627)DOAJ039615014 (DE-599)DOAJccd31399139a4e4ab580d60749d90b0f DE-627 ger DE-627 rakwb eng TK5101-6720 Ren Qun verfasserin aut A new energy‐aware method for load balance managing in the fog‐based vehicular ad hoc networks (VANET) using a hybrid optimization algorithm 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Fog‐based VANETs (Vehicular Ad hoc NETworks) is a new model with vehicular cloud and fog computing benefits. Fog‐based VANETs consist of a series of mobile nodes that are fully dynamic without any central management. These networks have some limitations due to the use of the mobile power source. There are many challenges in extending mobile‐based networks' life span. Many methods have been suggested to minimize the nodes' energy consumption and extend the network life. Also, some works have been developed for load‐balanced routing. Still, energy‐efficient routing and load balancing in VANETs are challenges. The purpose of this study is to present a suitable method based on energy awareness for load balancing in fog‐based VANETs using a hybrid optimization algorithm (employing ant colony optimization and artificial bee colony (ACO‐ABC)). The simulation results in the Network Simulator 2 (NS2) environment showed that as the number of nodes increased, the consumed amount of energy in the VANET is increased. Also, with the increasing number of tasks, load balancing by the proposed method has been improved. Finally, the simulation experiments showed that the proposed hybrid algorithm (ACO‐ABC) outperforms all other algorithms. Communication network design, planning and routing Computer communications Mobile radio systems Optimisation techniques Other computer networks Telecommunication Seyedeh Maryam Arefzadeh verfasserin aut In IET Communications Wiley, 2021 15(2021), 13, Seite 1665-1676 (DE-627)521691621 (DE-600)2264240-7 17518636 nnns volume:15 year:2021 number:13 pages:1665-1676 https://doi.org/10.1049/cmu2.12179 kostenfrei https://doaj.org/article/ccd31399139a4e4ab580d60749d90b0f kostenfrei https://doi.org/10.1049/cmu2.12179 kostenfrei https://doaj.org/toc/1751-8628 Journal toc kostenfrei https://doaj.org/toc/1751-8636 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 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_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 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_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 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_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4367 GBV_ILN_4393 GBV_ILN_4700 AR 15 2021 13 1665-1676
allfields_unstemmed	10.1049/cmu2.12179 doi (DE-627)DOAJ039615014 (DE-599)DOAJccd31399139a4e4ab580d60749d90b0f DE-627 ger DE-627 rakwb eng TK5101-6720 Ren Qun verfasserin aut A new energy‐aware method for load balance managing in the fog‐based vehicular ad hoc networks (VANET) using a hybrid optimization algorithm 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Fog‐based VANETs (Vehicular Ad hoc NETworks) is a new model with vehicular cloud and fog computing benefits. Fog‐based VANETs consist of a series of mobile nodes that are fully dynamic without any central management. These networks have some limitations due to the use of the mobile power source. There are many challenges in extending mobile‐based networks' life span. Many methods have been suggested to minimize the nodes' energy consumption and extend the network life. Also, some works have been developed for load‐balanced routing. Still, energy‐efficient routing and load balancing in VANETs are challenges. The purpose of this study is to present a suitable method based on energy awareness for load balancing in fog‐based VANETs using a hybrid optimization algorithm (employing ant colony optimization and artificial bee colony (ACO‐ABC)). The simulation results in the Network Simulator 2 (NS2) environment showed that as the number of nodes increased, the consumed amount of energy in the VANET is increased. Also, with the increasing number of tasks, load balancing by the proposed method has been improved. Finally, the simulation experiments showed that the proposed hybrid algorithm (ACO‐ABC) outperforms all other algorithms. Communication network design, planning and routing Computer communications Mobile radio systems Optimisation techniques Other computer networks Telecommunication Seyedeh Maryam Arefzadeh verfasserin aut In IET Communications Wiley, 2021 15(2021), 13, Seite 1665-1676 (DE-627)521691621 (DE-600)2264240-7 17518636 nnns volume:15 year:2021 number:13 pages:1665-1676 https://doi.org/10.1049/cmu2.12179 kostenfrei https://doaj.org/article/ccd31399139a4e4ab580d60749d90b0f kostenfrei https://doi.org/10.1049/cmu2.12179 kostenfrei https://doaj.org/toc/1751-8628 Journal toc kostenfrei https://doaj.org/toc/1751-8636 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 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_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 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_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 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_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4367 GBV_ILN_4393 GBV_ILN_4700 AR 15 2021 13 1665-1676
allfieldsGer	10.1049/cmu2.12179 doi (DE-627)DOAJ039615014 (DE-599)DOAJccd31399139a4e4ab580d60749d90b0f DE-627 ger DE-627 rakwb eng TK5101-6720 Ren Qun verfasserin aut A new energy‐aware method for load balance managing in the fog‐based vehicular ad hoc networks (VANET) using a hybrid optimization algorithm 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Fog‐based VANETs (Vehicular Ad hoc NETworks) is a new model with vehicular cloud and fog computing benefits. Fog‐based VANETs consist of a series of mobile nodes that are fully dynamic without any central management. These networks have some limitations due to the use of the mobile power source. There are many challenges in extending mobile‐based networks' life span. Many methods have been suggested to minimize the nodes' energy consumption and extend the network life. Also, some works have been developed for load‐balanced routing. Still, energy‐efficient routing and load balancing in VANETs are challenges. The purpose of this study is to present a suitable method based on energy awareness for load balancing in fog‐based VANETs using a hybrid optimization algorithm (employing ant colony optimization and artificial bee colony (ACO‐ABC)). The simulation results in the Network Simulator 2 (NS2) environment showed that as the number of nodes increased, the consumed amount of energy in the VANET is increased. Also, with the increasing number of tasks, load balancing by the proposed method has been improved. Finally, the simulation experiments showed that the proposed hybrid algorithm (ACO‐ABC) outperforms all other algorithms. Communication network design, planning and routing Computer communications Mobile radio systems Optimisation techniques Other computer networks Telecommunication Seyedeh Maryam Arefzadeh verfasserin aut In IET Communications Wiley, 2021 15(2021), 13, Seite 1665-1676 (DE-627)521691621 (DE-600)2264240-7 17518636 nnns volume:15 year:2021 number:13 pages:1665-1676 https://doi.org/10.1049/cmu2.12179 kostenfrei https://doaj.org/article/ccd31399139a4e4ab580d60749d90b0f kostenfrei https://doi.org/10.1049/cmu2.12179 kostenfrei https://doaj.org/toc/1751-8628 Journal toc kostenfrei https://doaj.org/toc/1751-8636 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 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_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 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_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 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_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4367 GBV_ILN_4393 GBV_ILN_4700 AR 15 2021 13 1665-1676
allfieldsSound	10.1049/cmu2.12179 doi (DE-627)DOAJ039615014 (DE-599)DOAJccd31399139a4e4ab580d60749d90b0f DE-627 ger DE-627 rakwb eng TK5101-6720 Ren Qun verfasserin aut A new energy‐aware method for load balance managing in the fog‐based vehicular ad hoc networks (VANET) using a hybrid optimization algorithm 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Fog‐based VANETs (Vehicular Ad hoc NETworks) is a new model with vehicular cloud and fog computing benefits. Fog‐based VANETs consist of a series of mobile nodes that are fully dynamic without any central management. These networks have some limitations due to the use of the mobile power source. There are many challenges in extending mobile‐based networks' life span. Many methods have been suggested to minimize the nodes' energy consumption and extend the network life. Also, some works have been developed for load‐balanced routing. Still, energy‐efficient routing and load balancing in VANETs are challenges. The purpose of this study is to present a suitable method based on energy awareness for load balancing in fog‐based VANETs using a hybrid optimization algorithm (employing ant colony optimization and artificial bee colony (ACO‐ABC)). The simulation results in the Network Simulator 2 (NS2) environment showed that as the number of nodes increased, the consumed amount of energy in the VANET is increased. Also, with the increasing number of tasks, load balancing by the proposed method has been improved. Finally, the simulation experiments showed that the proposed hybrid algorithm (ACO‐ABC) outperforms all other algorithms. Communication network design, planning and routing Computer communications Mobile radio systems Optimisation techniques Other computer networks Telecommunication Seyedeh Maryam Arefzadeh verfasserin aut In IET Communications Wiley, 2021 15(2021), 13, Seite 1665-1676 (DE-627)521691621 (DE-600)2264240-7 17518636 nnns volume:15 year:2021 number:13 pages:1665-1676 https://doi.org/10.1049/cmu2.12179 kostenfrei https://doaj.org/article/ccd31399139a4e4ab580d60749d90b0f kostenfrei https://doi.org/10.1049/cmu2.12179 kostenfrei https://doaj.org/toc/1751-8628 Journal toc kostenfrei https://doaj.org/toc/1751-8636 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 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_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 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_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 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_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4367 GBV_ILN_4393 GBV_ILN_4700 AR 15 2021 13 1665-1676
language	English
source	In IET Communications 15(2021), 13, Seite 1665-1676 volume:15 year:2021 number:13 pages:1665-1676
sourceStr	In IET Communications 15(2021), 13, Seite 1665-1676 volume:15 year:2021 number:13 pages:1665-1676
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Communication network design, planning and routing Computer communications Mobile radio systems Optimisation techniques Other computer networks Telecommunication
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container_title	IET Communications
authorswithroles_txt_mv	Ren Qun @@aut@@ Seyedeh Maryam Arefzadeh @@aut@@
publishDateDaySort_date	2021-01-01T00:00:00Z
hierarchy_top_id	521691621
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callnumber-first	T - Technology
author	Ren Qun
spellingShingle	Ren Qun misc TK5101-6720 misc Communication network design, planning and routing misc Computer communications misc Mobile radio systems misc Optimisation techniques misc Other computer networks misc Telecommunication A new energy‐aware method for load balance managing in the fog‐based vehicular ad hoc networks (VANET) using a hybrid optimization algorithm
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topic_title	TK5101-6720 A new energy‐aware method for load balance managing in the fog‐based vehicular ad hoc networks (VANET) using a hybrid optimization algorithm Communication network design, planning and routing Computer communications Mobile radio systems Optimisation techniques Other computer networks
topic	misc TK5101-6720 misc Communication network design, planning and routing misc Computer communications misc Mobile radio systems misc Optimisation techniques misc Other computer networks misc Telecommunication
topic_unstemmed	misc TK5101-6720 misc Communication network design, planning and routing misc Computer communications misc Mobile radio systems misc Optimisation techniques misc Other computer networks misc Telecommunication
topic_browse	misc TK5101-6720 misc Communication network design, planning and routing misc Computer communications misc Mobile radio systems misc Optimisation techniques misc Other computer networks misc Telecommunication
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title	A new energy‐aware method for load balance managing in the fog‐based vehicular ad hoc networks (VANET) using a hybrid optimization algorithm
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title_full	A new energy‐aware method for load balance managing in the fog‐based vehicular ad hoc networks (VANET) using a hybrid optimization algorithm
author_sort	Ren Qun
journal	IET Communications
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author_browse	Ren Qun Seyedeh Maryam Arefzadeh
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title_sort	new energy‐aware method for load balance managing in the fog‐based vehicular ad hoc networks (vanet) using a hybrid optimization algorithm
callnumber	TK5101-6720
title_auth	A new energy‐aware method for load balance managing in the fog‐based vehicular ad hoc networks (VANET) using a hybrid optimization algorithm
abstract	Abstract Fog‐based VANETs (Vehicular Ad hoc NETworks) is a new model with vehicular cloud and fog computing benefits. Fog‐based VANETs consist of a series of mobile nodes that are fully dynamic without any central management. These networks have some limitations due to the use of the mobile power source. There are many challenges in extending mobile‐based networks' life span. Many methods have been suggested to minimize the nodes' energy consumption and extend the network life. Also, some works have been developed for load‐balanced routing. Still, energy‐efficient routing and load balancing in VANETs are challenges. The purpose of this study is to present a suitable method based on energy awareness for load balancing in fog‐based VANETs using a hybrid optimization algorithm (employing ant colony optimization and artificial bee colony (ACO‐ABC)). The simulation results in the Network Simulator 2 (NS2) environment showed that as the number of nodes increased, the consumed amount of energy in the VANET is increased. Also, with the increasing number of tasks, load balancing by the proposed method has been improved. Finally, the simulation experiments showed that the proposed hybrid algorithm (ACO‐ABC) outperforms all other algorithms.
abstractGer	Abstract Fog‐based VANETs (Vehicular Ad hoc NETworks) is a new model with vehicular cloud and fog computing benefits. Fog‐based VANETs consist of a series of mobile nodes that are fully dynamic without any central management. These networks have some limitations due to the use of the mobile power source. There are many challenges in extending mobile‐based networks' life span. Many methods have been suggested to minimize the nodes' energy consumption and extend the network life. Also, some works have been developed for load‐balanced routing. Still, energy‐efficient routing and load balancing in VANETs are challenges. The purpose of this study is to present a suitable method based on energy awareness for load balancing in fog‐based VANETs using a hybrid optimization algorithm (employing ant colony optimization and artificial bee colony (ACO‐ABC)). The simulation results in the Network Simulator 2 (NS2) environment showed that as the number of nodes increased, the consumed amount of energy in the VANET is increased. Also, with the increasing number of tasks, load balancing by the proposed method has been improved. Finally, the simulation experiments showed that the proposed hybrid algorithm (ACO‐ABC) outperforms all other algorithms.
abstract_unstemmed	Abstract Fog‐based VANETs (Vehicular Ad hoc NETworks) is a new model with vehicular cloud and fog computing benefits. Fog‐based VANETs consist of a series of mobile nodes that are fully dynamic without any central management. These networks have some limitations due to the use of the mobile power source. There are many challenges in extending mobile‐based networks' life span. Many methods have been suggested to minimize the nodes' energy consumption and extend the network life. Also, some works have been developed for load‐balanced routing. Still, energy‐efficient routing and load balancing in VANETs are challenges. The purpose of this study is to present a suitable method based on energy awareness for load balancing in fog‐based VANETs using a hybrid optimization algorithm (employing ant colony optimization and artificial bee colony (ACO‐ABC)). The simulation results in the Network Simulator 2 (NS2) environment showed that as the number of nodes increased, the consumed amount of energy in the VANET is increased. Also, with the increasing number of tasks, load balancing by the proposed method has been improved. Finally, the simulation experiments showed that the proposed hybrid algorithm (ACO‐ABC) outperforms all other algorithms.
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title_short	A new energy‐aware method for load balance managing in the fog‐based vehicular ad hoc networks (VANET) using a hybrid optimization algorithm
url	https://doi.org/10.1049/cmu2.12179 https://doaj.org/article/ccd31399139a4e4ab580d60749d90b0f https://doaj.org/toc/1751-8628 https://doaj.org/toc/1751-8636
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doi_str	10.1049/cmu2.12179
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up_date	2024-07-04T00:04:45.199Z
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fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ039615014</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230308031936.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230227s2021 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1049/cmu2.12179</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ039615014</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJccd31399139a4e4ab580d60749d90b0f</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="050" ind1=" " ind2="0"><subfield code="a">TK5101-6720</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Ren Qun</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="2"><subfield code="a">A new energy‐aware method for load balance managing in the fog‐based vehicular ad hoc networks (VANET) using a hybrid optimization algorithm</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2021</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 Fog‐based VANETs (Vehicular Ad hoc NETworks) is a new model with vehicular cloud and fog computing benefits. Fog‐based VANETs consist of a series of mobile nodes that are fully dynamic without any central management. These networks have some limitations due to the use of the mobile power source. There are many challenges in extending mobile‐based networks' life span. Many methods have been suggested to minimize the nodes' energy consumption and extend the network life. Also, some works have been developed for load‐balanced routing. Still, energy‐efficient routing and load balancing in VANETs are challenges. The purpose of this study is to present a suitable method based on energy awareness for load balancing in fog‐based VANETs using a hybrid optimization algorithm (employing ant colony optimization and artificial bee colony (ACO‐ABC)). The simulation results in the Network Simulator 2 (NS2) environment showed that as the number of nodes increased, the consumed amount of energy in the VANET is increased. Also, with the increasing number of tasks, load balancing by the proposed method has been improved. Finally, the simulation experiments showed that the proposed hybrid algorithm (ACO‐ABC) outperforms all other algorithms.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Communication network design, planning and routing</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Computer communications</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mobile radio systems</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Optimisation techniques</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Other computer networks</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Telecommunication</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Seyedeh Maryam Arefzadeh</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" 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A new energy‐aware method for load balance managing in the fog‐based vehicular ad hoc networks (VANET) using a hybrid optimization algorithm

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