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Title TRUTH DISCOVERY FOR MOBILE WORKERS IN EDGE-ASSISTED MOBILE CROWDSENSING

Author(s) Amir Ali shah

Abstract The proliferation of mobile phones has led to the rise of mobile crowdsensing systems. However, many of these systems rely on the deep cloud, which can be complex and challenging to scale. To improve the performance of crowdsensing at the edge cloud, truth-discovery methods are commonly employed. These methods typically involve updating either the truth or the weight associated with a user's task. While some edge cloud-based crowdsensing systems exist, they do not provide incentives to users based on their experience. In this report, we present a new approach to truth discovery and incentive-giving that considers both the user's experience and the accuracy of their submitted data. Our modified truth-discovery algorithm updates both the weight and truth concurrently, with greater incentives offered to users who have completed more tasks and whose submitted data is close to the estimated truth. We have conducted simulations to demonstrate the effectiveness of our proposed solution in improving the incentive mechanism for experienced users.

Type Thesis/Dissertation MS

Faculty Engineering and Computer Science

Department Computer Science

Language English

Publication Date 2023-02-15

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