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Title: Quality-aware incentivisation for mobile crowd services
Author: Shi, Fengrui
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2019
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With the proliferation of mobile devices, mobile crowd participants have become one of the important providers for data and services. For example, mobile crowd sensing systems are designed to perform various tasks from environmental monitoring to traffic management by using the data collected through consumer mobile devices. In addition, the recent development of device to device (D2D) communications enables another kind of mobile crowd systems that offer data and computation offloading services in mobile peer to peer (P2P) networks. To provide mobile crowd services (MCS), mobile crowd participants may have to contribute their personal mobile resources, such as data, communication and computation resources. This could result in excessive resource consumption on their mobile devices and cause potential privacy issues. As a result, incentive mechanisms must be carefully designed into MCS systems in order to encourage the participation of mobile users despite these negative factors. Besides, quality of service (QoS) is also an essential driver to the practical and sustainable deployment and operation of MCS and building QoS awareness into the incentive mechanisms ensures that the limited monetary resources could be used to elicit the best QoS from mobile crowd participants. Therefore, in this thesis, we approach the incentivisation problems for MCS from a quality-aware perspective. We focus on two typical MCS systems - mobile crowd sensing services (MCSS) and mobile P2P crowd services (MPCS). Although heterogeneous services are offered through these MCS systems, their incentive mechanisms can be built systematically since they all pose similar challenges in terms of quality model design, economic activity modelling, and system deployment. For MCSS, the focus of this thesis is on data quality issues and we propose incentive mechanisms that incorporate data quality models into cooperative game theoretical frameworks. As for MPCS, communication and execution quality are modeled and built into specially structured data trading and offloading incentive mechanisms. This thesis emphasises both theoretical and practical aspects of MCS systems. From the theoretical point of view, the incentive mechanisms proposed in this thesis are designed based on various game theoretical and economic models. From the practical point of view, system prototypes are deployed to evaluate the performance of MCS and corresponding incentive mechanisms based on both QoS and economic impact.
Supervisor: McCann, Julie Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral