Incentive Mechanism for Mobile Crowdsensing
Incentive Mechanism for Mobile Crowdsensing

Author: Youqi Li

Publisher: Springer Nature

Published: 2024-01-03

Total Pages: 137

ISBN-13: 9819969212

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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 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.

Mobile Crowd Sensing: Incentive Mechanism Design
Mobile Crowd Sensing: Incentive Mechanism Design

Author: Fen Hou

Publisher: Springer

Published: 2018-10-24

Total Pages: 59

ISBN-13: 3030010244

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This SpringerBrief investigates and reviews the development and various applications of mobile crowd sensing (MCS). With the miniaturization of sensors and the popularity of smart mobile devices, MCS becomes a promising solution to efficiently collect different types of information, such as traffic conditions, air quality, temperature and more, which is covered in this brief. The features, novelty, and applications of MCS are elaborated in detail in this brief. In addition, the basic knowledge about auction theory and incentive mechanism design is introduced. Incentive mechanism design plays a key role in the success of MCS. With an efficient incentive mechanism, it is possible to attract enough mobile users to participate in a MCS system, thus enough high quality sensing data can be collected. Two types of incentive mechanisms with different system models are introduced in this brief. One is the reputation-aware incentive mechanism, and another is the social-aware incentive mechanism. This SpringerBrief covers the significance and the impacts of both reputation and social relationship of smartphone users (SUs) in MCS and presents extensive simulation results to demonstrate the good performance of the proposed incentive mechanisms compared with some existing counterparts. The target audience for this SpringerBrief is researchers and engineers in the area of wireless communication and networking, especially those who are interested in the mobile crowd sensing or incentive mechanism design. Meanwhile, it is also intended as a reference guide for advanced level students in the area of wireless communications and computer networks.

Web, Artificial Intelligence and Network Applications
Web, Artificial Intelligence and Network Applications

Author: Leonard Barolli

Publisher: Springer Nature

Published: 2020-03-30

Total Pages: 1487

ISBN-13: 3030440389

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This proceedings book presents the latest research findings, and theoretical and practical perspectives on innovative methods and development techniques related to the emerging areas of Web computing, intelligent systems and Internet computing. The Web has become an important source of information, and techniques and methodologies that extract quality information are of paramount importance for many Web and Internet applications. Data mining and knowledge discovery play a key role in many of today's major Web applications, such as e-commerce and computer security. Moreover, Web services provide a new platform for enabling service-oriented systems. The emergence of large-scale distributed computing paradigms, such as cloud computing and mobile computing systems, has opened many opportunities for collaboration services, which are at the core of any information system. Artificial intelligence (AI) is an area of computer science that builds intelligent systems and algorithms that work and react like humans. AI techniques and computational intelligence are powerful tools for learning, adaptation, reasoning and planning, and they have the potential to become enabling technologies for future intelligent networks. Research in the field of intelligent systems, robotics, neuroscience, artificial intelligence and cognitive sciences is vital for the future development and innovation of Web and Internet applications. Chapter "An Event-Driven Multi Agent System for Scalable Traffic Optimization" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Task Allocation and Incentive Mechanism Design for Mobile Crowdsensing
Task Allocation and Incentive Mechanism Design for Mobile Crowdsensing

Author: Tao, Xi

Publisher:

Published: 2020

Total Pages: 0

ISBN-13:

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Mobile crowdsensing (MCS) is a new paradigm of data collection with large-scale sensing. A group of users with mobile devices (e.g., smartphones, tablet computers, and wearables) are recruited as workers to move around in a specific region and carry out sensing tasks. There are two key problems in MCS, i.e., task allocation problem and incentive mechanism design. In this thesis, we build a MCS framework and provide solutions to its two key problems. Specifically, we focus on (1) the task allocation problem in the static scenarios, in which the information of tasks and workers are known at the beginning of sensing activities; (2) the task allocation problem in the dynamic scenarios when the platform cannot obtain the information of workers before their arrivals; and (3) the incentive mechanism design that motivates workers to participate in the sensing activities. Our proposed MCS framework is associated with two important components to deal with the task allocation problem and incentive mechanism design, respectively. The task allocation problem is considered and formulated as a path planning problem since the tasks in the MCS framework are generally location-dependent. We first plan paths for workers in the static scenarios. Meanwhile, we take two different modes of path planning into account, i.e., the platform-centric mode and workercentric mode. To solve the path planning problem in these two modes, we propose an evolutionary algorithm and a heuristic algorithm, respectively. Second, we investigate the dynamic task allocation problem. Although the platform has incomplete information of workers, we explore several online algorithms to achieve the satisfactory performance. Third, we design a location-protected and truthful incentive mechanism to motivate workers to move around and accomplish sensing tasks. Based on the results of path planning, we use the auction theory to ensure workers to provide their true private information including costs and task sets. The overall performance of our proposed framework is extensively evaluated through simulations and the simulation results illustrate the effectiveness and efficiency of our solutions in the proposed framework.

Mobile Computing, Applications, and Services
Mobile Computing, Applications, and Services

Author: Yuyu Yin

Publisher: Springer Nature

Published: 2019-09-24

Total Pages: 245

ISBN-13: 3030284689

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This book constitutes the thoroughly refereed post-conference proceedings of the 10th International Conference on Mobile Computing, Applications, and Services, MobiCASE 2019, held in Hangzhou, China, in June 2019. The 17 full papers were carefully reviewed and selected from 48 submissions. The papers are organized in topical sections on mobile application with data analysis, mobile application with AI, edge computing, energy optimization and application

Green, Pervasive, and Cloud Computing
Green, Pervasive, and Cloud Computing

Author: Shijian Li

Publisher: Springer

Published: 2019-03-14

Total Pages: 526

ISBN-13: 3030150933

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This book constitutes the proceedings of the 13th International Conference on Green, Pervasive, and Cloud Computing, GPC 2018, held in Hangzhou, China, in May 2018. The 35 full papers included in this volume were carefully reviewed and selected from 101 initial submissions. They are organized in the following topical sections: network security, and privacy-preserving; pervasive sensing and analysis; cloud computing, mobile computing, and crowd sensing; social and urban computing; parallel and distributed systems, optimization; pervasive applications; and data mining and knowledge mining.

Mobile Multimedia Communications
Mobile Multimedia Communications

Author: Jinbo Xiong

Publisher: Springer Nature

Published: 2021-11-02

Total Pages: 899

ISBN-13: 3030898148

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This book constitutes the thoroughly refereed post-conference proceedings of the 14th International Conference on Mobile Multimedia Communications, Mobimedia 2021, held in July 2021. Due to COVID-19 pandemic the conference was held virtually. The 66 revised full papers presented were carefully selected from 166 submissions. The papers are organized in topical sections as follows: Internet of Things and Wireless Communications Communication; Strategy Optimization and Task Scheduling Oral Presentations; Privacy Computing Technology; Cyberspace Security and Access control; Neural Networks and Feature Learning Task Classification and Prediction; Object Recognition and Detection.

Mobile Crowdsensing
Mobile Crowdsensing

Author: Cristian Borcea

Publisher: CRC Press

Published: 2016-12-01

Total Pages: 207

ISBN-13: 1315352419

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Mobile crowdsensing is a technology that allows large scale, cost-effective sensing of the physical world. In mobile crowdsensing, mobile personal devices such as smart phones or smart watches come equipped with a variety of sensors that can be leveraged to collect data related to environment, transportation, healthcare, safety and so on. This book presents the first extensive coverage of mobile crowdsensing, with examples and insights drawn from the authors’ extensive research on this topic as well as from the research and development of a growing community of researchers and practitioners working in this emerging field. Throughout the text, the authors provide the reader with various examples of crowdsensing applications and the building blocks to creating the necessary infrastructure, explore the related concepts of mobile sensing and crowdsourcing, and examine security and privacy issues introduced by mobile crowdsensing platforms. Provides a comprehensive description of mobile crowdsensing, a one-stop shop for all relevant issues pertaining to mobile crowdsensing, including motivation, applications, design and implementation, incentive mechanisms, and reliability and privacy. Describes the design and implementations of mobile crowdsensing platforms of great interest for the readers working in research and industry to quickly implement and test their systems. Identifies potential issues in building such mobile crowdsensing applications to ensure their usability in real life and presents future directions in mobile crowdsensing by emphasizing the open problems that have to be addressed.