LEADER 04607nam 22007695 450 001 9910799237003321 005 20240103220134.0 010 $a981-9969-21-2 024 7 $a10.1007/978-981-99-6921-0 035 $a(CKB)29526911900041 035 $a(DE-He213)978-981-99-6921-0 035 $a(MiAaPQ)EBC31094198 035 $a(Au-PeEL)EBL31094198 035 $a(EXLCZ)9929526911900041 100 $a20240103d2024 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aIncentive Mechanism for Mobile Crowdsensing$b[electronic resource] $eA Game-theoretic Approach /$fby Youqi Li, Fan Li, Song Yang, Chuan Zhang 205 $a1st ed. 2024. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2024. 215 $a1 online resource (XI, 129 p. 1 illus.) 225 1 $aSpringerBriefs in Computer Science,$x2191-5776 311 08$a9789819969203 327 $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. 330 $aMobile crowdsensing (MCS) is emerging as a novel sensing paradigm in the Internet of Things (IoTs) due to the proliferation of smart devices (e.g., smartphones, wearable devices) in people?s daily lives. These ubiquitous devices provide an opportunity to harness the wisdom of crowds by recruiting mobile users to collectively perform sensing tasks, which largely collect data about a wide range of human activities and the surrounding environment. However, users suffer from resource consumption such as battery, processing power, and storage, which discourages users? participation. To ensure the participation rate, it is necessary to employ an incentive mechanism to compensate users? costs such that users are willing to take part in crowdsensing. This book sheds light on the design of incentive mechanisms for MCS in the context of game theory. Particularly, this book presents several game-theoretic models for MCS in different scenarios. In Chapter 1, the authors present an overview of MCS and state the significance of incentive mechanism for MCS. Then, in Chapter 2, 3, 4, and 5, the authors propose a long-term incentive mechanism, a fair incentive mechanism, a collaborative incentive mechanism, and a coopetition-aware incentive mechanism for MCS, respectively. Finally, Chapter 6 summarizes this book and point out the future directions. This book is of particular interest to the readers and researchers in the field of IoT research, especially in the interdisciplinary field of network economics and IoT. 410 0$aSpringerBriefs in Computer Science,$x2191-5776 606 $aMobile computing 606 $aCooperating objects (Computer systems) 606 $aData mining 606 $aComputer science$xMathematics 606 $aMathematical statistics 606 $aAlgorithms 606 $aComputer science 606 $aMobile Computing 606 $aCyber-Physical Systems 606 $aData Mining and Knowledge Discovery 606 $aProbability and Statistics in Computer Science 606 $aDesign and Analysis of Algorithms 606 $aTheory and Algorithms for Application Domains 615 0$aMobile computing. 615 0$aCooperating objects (Computer systems). 615 0$aData mining. 615 0$aComputer science$xMathematics. 615 0$aMathematical statistics. 615 0$aAlgorithms. 615 0$aComputer science. 615 14$aMobile Computing. 615 24$aCyber-Physical Systems. 615 24$aData Mining and Knowledge Discovery. 615 24$aProbability and Statistics in Computer Science. 615 24$aDesign and Analysis of Algorithms. 615 24$aTheory and Algorithms for Application Domains. 676 $a004.167 700 $aLi$b Youqi$4aut$4http://id.loc.gov/vocabulary/relators/aut$01587638 702 $aLi$b Fan$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aYang$b Song$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aZhang$b Chuan$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910799237003321 996 $aIncentive Mechanism for Mobile Crowdsensing$93875877 997 $aUNINA