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001 978-3-031-32138-2
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005 20240423130246.0
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008 230725s2023 sz | s |||| 0|eng d
020 _a9783031321382
_9978-3-031-32138-2
024 7 _a10.1007/978-3-031-32138-2
_2doi
050 4 _aTK5105.5-5105.9
072 7 _aUKN
_2bicssc
072 7 _aCOM043000
_2bisacsh
072 7 _aUKN
_2thema
082 0 4 _a004.6
_223
100 1 _aXiao, Liang.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aReinforcement Learning for Maritime Communications
_h[electronic resource] /
_cby Liang Xiao, Helin Yang, Weihua Zhuang, Minghui Min.
250 _a1st ed. 2023.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2023.
300 _aIX, 146 p. 50 illus., 49 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aWireless Networks,
_x2366-1445
505 0 _aIntroduction -- Intelligent Internet of Things Networking Architecture -- Intelligent IoT Network Awareness -- Intelligent Traffic Control -- Intelligent Resource Scheduling -- Mobile Edge Computing Enabled Intelligent IoT -- Blockchain Enabled Intelligent IoT -- Conclusions and Future Challenges.
520 _aThis book demonstrates that the reliable and secure communication performance of maritime communications can be significantly improved by using intelligent reflecting surface (IRS) aided communication, privacy-aware Internet of Things (IoT) communications, intelligent resource management and location privacy protection. In the IRS aided maritime communication system, the reflecting elements of IRS can be intelligently controlled to change the phase of signal, and finally enhance the received signal strength of maritime ships (or sensors) or jam maritime eavesdroppers illustrated in this book. The power and spectrum resource in maritime communications can be jointly optimized to guarantee the quality of service (i.e., security and reliability requirements), and reinforcement leaning is adopted to smartly choose the resource allocation strategy. Moreover, learning based privacy-aware offloading and location privacy protection are proposed to intelligently guarantee the privacy-preserving requirements of maritime ships or (sensors). Therefore, these communication schemes based on reinforcement learning algorithms can help maritime communication systems to improve the information security, especially in dynamic and complex maritime environments. This timely book also provides broad coverage of the maritime wireless communication issues, such as reliability, security, resource management, and privacy protection. Reinforcement learning based methods are applied to solve these issues. This book includes four rigorously refereed chapters from prominent international researchers working in this subject area. The material serves as a useful reference for researchers, graduate students. Practitioners seeking solutions to maritime wireless communication and security related issues will benefit from this book as well.
650 0 _aComputer networks .
650 0 _aWireless communication systems.
650 0 _aMobile communication systems.
650 0 _aMachine learning.
650 1 4 _aComputer Communication Networks.
650 2 4 _aWireless and Mobile Communication.
650 2 4 _aMachine Learning.
700 1 _aYang, Helin.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aZhuang, Weihua.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aMin, Minghui.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031321375
776 0 8 _iPrinted edition:
_z9783031321399
776 0 8 _iPrinted edition:
_z9783031321405
830 0 _aWireless Networks,
_x2366-1445
856 4 0 _uhttps://doi.org/10.1007/978-3-031-32138-2
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
999 _c186719
_d186719