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Overview: Mobile 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 enable the possibility of harnessing the wisdom of crowds by recruiting mobile users to collectively perform sensing tasks that largely collect data about a diverse range of human activities and the surrounding environment. However, users suffer from resource consumption like battery, computing power, and storage, which discourage users’ participation. To ensure a participation rate, it is necessary to employ an incentive mechanism to compensate users’ costs such that users are willing to take part in crowdsensing. Designing an appropriate incentive mechanism is nontrivial due to different practical challenges like modeling and computational hardness. Capturing the different roles’ utility maximization, game theory is widely used to address incentive mechanism design problems. While many existing papers study incentive mechanism in MCS, to the best of our knowledge, there is few books giving a comprehensive review of the incentive mechanism for MCS, especially from the game-theoretic perspective. This book aims to fill this void. The prerequisite for reading this book is a basic understanding of the mobile crowdsensing infrastructure, game theory, equilibrium analysis, and convex optimization.
Genre: Non-Fiction > Tech & Devices
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