000			04050nam a22005775i 4500
001			978-3-030-88991-3
003			DE-He213
005			20240423125509.0
007			cr nn 008mamaa
008			211118s2021 sz | s |||| 0|eng d
020			_a9783030889913 _9978-3-030-88991-3
024	7		_a10.1007/978-3-030-88991-3 _2doi
050		4	_aTK5105.5-5105.9
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072		7	_aCOM043000 _2bisacsh
072		7	_aUKN _2thema
082	0	4	_a004.6 _223
100	1		_aXu, Wenchao. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	1	0	_aInternet Access in Vehicular Networks _h[electronic resource] / _cby Wenchao Xu, Haibo Zhou, Xuemin (Sherman) Shen.
250			_a1st ed. 2021.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2021.
300			_aXII, 165 p. 76 illus., 67 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aOverview of Internet Access of Vehicular Networks -- Internet Access Modeling of Vehicular Internet Access -- V2X Interworking via Vehicular Internet Access -- Intelligent Link Management for Vehicular Internet Access -- Intelligent Networking enabled Vehicular Distributed Learning -- Conclusion and Future Works.
520			_aThis book introduces the Internet access for vehicles as well as novel communication and computing paradigms based on the Internet of vehicles. To enable efficient and reliable Internet connection for mobile vehicle users, this book first introduces analytical modelling methods for the practical vehicle-to-roadside (V2R) Internet access procedure, and employ the interworking of V2R and vehicle-to-vehicle (V2V) to improve the network performance for a variety of automotive applications. In addition, the wireless link performance between a vehicle and an Internet access station is investigated, and a machine learning based algorithm is proposed to improve the link throughout by selecting an efficient modulation and coding scheme. This book also investigates the distributed machine learning algorithms over the Internet access of vehicles. A novel broadcasting scheme is designed to intelligently adjust the training users that are involved in the iteration rounds for an asynchronous federated learning scheme, which is shown to greatly improve the training efficiency. This book conducts the fully asynchronous machine learning evaluations among vehicle users that can utilize the opportunistic V2R communication to train machine learning models. Researchers and advanced-level students who focus on vehicular networks, industrial entities for internet of vehicles providers, government agencies target on transportation system and road management will find this book useful as reference. Network device manufacturers and network operators will also want to purchase this book. .
650		0	_aComputer networks .
650		0	_aWireless communication systems.
650		0	_aMobile communication systems.
650		0	_aComputers, Special purpose.
650		0	_aAutomotive engineering.
650	1	4	_aComputer Communication Networks.
650	2	4	_aWireless and Mobile Communication.
650	2	4	_aSpecial Purpose and Application-Based Systems.
650	2	4	_aAutomotive Engineering.
700	1		_aZhou, Haibo. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aShen, Xuemin (Sherman). _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
710	2		_aSpringerLink (Online service)
773	0		_tSpringer Nature eBook
776	0	8	_iPrinted edition: _z9783030889906
776	0	8	_iPrinted edition: _z9783030889920
776	0	8	_iPrinted edition: _z9783030889937
856	4	0	_uhttps://doi.org/10.1007/978-3-030-88991-3
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912			_aZDB-2-SXCS
942			_cSPRINGER
999			_c178575 _d178575