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024 7 _a10.1007/978-981-99-6921-0
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100 1 _aLi, Youqi.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_996019
245 1 0 _aIncentive Mechanism for Mobile Crowdsensing
_h[electronic resource] :
_bA Game-theoretic Approach /
_cby Youqi Li, Fan Li, Song Yang, Chuan Zhang.
250 _a1st ed. 2024.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2024.
300 _aXI, 129 p. 1 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
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490 1 _aSpringerBriefs in Computer Science,
_x2191-5776
505 0 _aChapter 1: A Brief Introduction -- Chapter 2: Long-term Incentive Mechanism for Mobile Crowdsensing -- Chapter 3: Fair Incentive Mechanism for Mobile Crowdsensing -- Chapter 4: Collaborative Incentive Mechanism for Mobile Crowdsensing -- Chapter 5: Coopetition-aware Incentive Mechanism for Mobile Crowdsensing -- Chapter 6: Summary.
520 _aMobile crowdsensing (MCS) is emerging as a novel sensing paradigm in the Internet of Things (IoTs) due to the proliferation of smart devices (e.g., smartphones, wearable devices) in people's daily lives. These ubiquitous devices provide an opportunity to harness the wisdom of crowds by recruiting mobile users to collectively perform sensing tasks, which largely collect data about a wide range of human activities and the surrounding environment. However, users suffer from resource consumption such as battery, processing power, and storage, which discourages users' participation. To ensure the participation rate, it is necessary to employ an incentive mechanism to compensate users' costs such that users are willing to take part in crowdsensing. This book sheds light on the design of incentive mechanisms for MCS in the context of game theory. Particularly, this book presents several game-theoretic models for MCS in different scenarios. In Chapter 1, the authors present an overview of MCS and state the significance of incentive mechanism for MCS. Then, in Chapter 2, 3, 4, and 5, the authors propose a long-term incentive mechanism, a fair incentive mechanism, a collaborative incentive mechanism, and a coopetition-aware incentive mechanism for MCS, respectively. Finally, Chapter 6 summarizes this book and point out the future directions. This book is of particular interest to the readers and researchers in the field of IoT research, especially in the interdisciplinary field of network economics and IoT.
650 0 _aMobile computing.
_93438
650 0 _aCooperating objects (Computer systems).
_96195
650 0 _aData mining.
_93907
650 0 _aComputer science
_xMathematics.
_93866
650 0 _aMathematical statistics.
_99597
650 0 _aAlgorithms.
_93390
650 0 _aComputer science.
_99832
650 1 4 _aMobile Computing.
_93438
650 2 4 _aCyber-Physical Systems.
_932475
650 2 4 _aData Mining and Knowledge Discovery.
_996025
650 2 4 _aProbability and Statistics in Computer Science.
_931857
650 2 4 _aDesign and Analysis of Algorithms.
_931835
650 2 4 _aTheory and Algorithms for Application Domains.
_979177
700 1 _aLi, Fan.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_996027
700 1 _aYang, Song.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_996029
700 1 _aZhang, Chuan.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_996031
710 2 _aSpringerLink (Online service)
_996036
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789819969203
776 0 8 _iPrinted edition:
_z9789819969227
830 0 _aSpringerBriefs in Computer Science,
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856 4 0 _uhttps://doi.org/10.1007/978-981-99-6921-0
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