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020			_a9783031228605
024	7		_a10.1007/978-3-031-22860-5 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTK5105.5 _b2023 EB
100	1		_aLi, Mushu _eautor _4http://id.loc.gov/vocabulary/relators/aut _9690204
245	1	0	_aIntelligent Computing and Communication for the Internet of Vehicles _cby Mushu Li, Jie Gao, Xuemin (Sherman) Shen, Lian Zhao
250			_a1st ed 2023
264		1	_aCham _bSpringer Nature Switzerland _c2023
300			_a1 recurso en línea
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	0		_aSpringerBriefs in Computer Science _x2191-5776
505	0		_a1 Introduction -- 1.1 Internet of Vehicles (IoV) -- 1.2 IoV Use Cases -- 1.3 Network Characteristics in IoV -- 1.4 Outline of the Monograph -- References -- 2 Overview of Communication and Computing in IoV -- 2.1 Communication and Computing in IoV -- 2.2 V2X Communication Protocols -- 2.3 Vehicular Computing Resource Scheduling -- References -- 3 Protocol Design for Safety Message Broadcast -- 3.1 Communication in Safety Message Broadcast -- 3.2 Network Scenario -- 3.2.1 Basic Settings -- 3.2.2 Features of Safety Message Broadcast -- 3.2.3 Assumptions -- 3.3 CIDC: A Distributed and Adaptive MAC Design -- 3.3.1 Messaging Mechanism Design -- 3.3.2 Contention Intensity Estimation Method -- 3.3.3 Channel Access Mechanism Design -- 3.4 CIDC: Network-Perspective Modeling -- 3.5 CIDC: Performance Analysis -- 3.5.1 Basic Features -- 3.5.2 Packet-to-Slot Ratio -- 3.5.3 Contention Intensity and Contention Delay -- 3.5.4 Collision Conditions and Probability -- 3.6 Performance Evaluation -- vii -- viii Contents -- 3.6.1 Performance with Accurate Contention Intensity -- Estimation -- 3.6.2 A Comparison of Analytical and Numerical Results -- 3.6.3 Performance under Contention Intensity Estimation -- Errors -- 3.7 Summary -- References -- 4 Computing Scheduling for Autonomous Driving -- 4.1 Computing in Autonomous Driving -- 4.2 System Model -- 4.2.1 Network Model -- 4.2.2 Computing Scheduling Scenarios -- 4.2.3 Age of Computing Results -- 4.3 Adaptive Computing Resource Scheduling -- 4.3.1 Restless Multi-armed Bandit Formulation -- 4.3.2 Indexability and Index Policy -- 4.4 Machine Learning-based Scheduling Policy -- 4.4.1 DRL-assisted Scheduling -- 4.4.2 Scheduling Scheme for Asynchronous Offloading -- 4.5 Performance Evaluation -- 4.5.1 Numerical Results -- 4.5.2 Simulation in a Real Dataset -- 4.6 Summary -- References -- 5 Conclusions -- 5.1 Conclusions on Intelligent Computing and Communication -- in IoV -- 5.2 Open Research Problems.
520			_aThis book investigates intelligent network resource management for IoV, with the objective of maximizing the communication and computing performance of vehicle users. Focusing on two representative use cases in IoV, i.e., safety message broadcast and autonomous driving, the authors propose link-layer protocol design and application-layer computing task scheduling to achieve the objective given the unique characteristics and requirements of IoV. In particular, this book illustrates the challenges of resource management for IoV due to network dynamics, such as time-varying traffic intensity and vehicle mobility, and presents intelligent resource management solutions to adapt to the network dynamics. The Internet of Vehicles (IoV) enables vehicle-to-everything connectivity and supports a variety of applications for vehicles on the road Intelligent resource management is critical for satisfying demanding communication and computing requirements on IoV, while the highly dynamic network environments pose challenges to the design of resource management schemes. This book provides insights into the significance of adaptive resource management in improving the performance of IoV. The customized communication protocol and computing scheduling scheme are designed accordingly by taking the network dynamics information as an integral design factor. Moreover, the decentralized designs of the proposed solutions guarantee low signaling overhead and high scalability. A comprehensive literature review summarizing recent resource management schemes in IoV, followed by the customized design of communication and computing solutions for the two IoV use cases is included which can serve as a useful reference for professionals from both academia and industry in the area of IoV and resource management. Researchers working within this field and computer science and electrical engineering students will find this book useful as well.
988			_aSpringer_Computer_2023
650		7	_2embne _9141354 _aRedes informáticas
700	1		_9685686 _aGao, Jie _eautor
700	1		_9686069 _aShen, X. _d1958- _eautor _q(Xuemin),
700	1		_9690205 _aZhao, Lian _d1969- _eautor
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-22860-5 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2024 _dz _ean _zSI