A Reverse Auction-Based User Incentive Method in Mobile Crowdsensing Network

Abstract

The invention requests protection of a user incentive method in a mobile crowd sensing network based on reverse auction, which utilizes a reverse auction framework to encourage users to participate in location-related sensing activities, and considers the random exit situation in the user sensing process. The scheme aims at maximizing user utility under the premise of feasible budget to improve users' enthusiasm for participating in perception activities. First, a task-centric approach is adopted to select users as the winners of perception tasks to ensure high task coverage. Secondly, according to the completion of the task of the winner, the user is paid according to the time-proportion sharing rule to ensure the authenticity of the incentive. The user incentive method in the reverse auction-based mobile crowd sensing network proposed by the present invention has the characteristics of computational validity, individual rationality, budget balance and authenticity. The invention can enable the user to obtain the maximum utility, encourage the user to participate in the task, and improve the user's participation enthusiasm.

Description

technical field [0001] The invention belongs to the technical field of crowd sensing, and in particular relates to a user incentive method in a mobile crowd sensing network based on reverse auction. Background technique [0002] Currently, smartphones have integrated many sensors, such as GPS, accelerometer, gyroscope, microphone, camera, etc. These sensors can jointly monitor human activities and the surrounding environment, so that people can perceive and obtain information about the surrounding environment anytime, anywhere. Utilizing ubiquitous smartphone users to perceive and collect large-scale data has become a new type of perception. At present, some projects have realized different applications in the fields of environmental monitoring, intelligent transportation, behavior monitoring, and indoor positioning based on mobile crowd sensing. [0003] The data acquisition of mobile crowd sensing applications requires the use of a large number of mobile user terminals fo...

AI Technical Summary

Problems solved by technology

[0005] However, due to the selfishness and randomness of human beings, the design of the mobile crowd sensing incentive method based on the reverse auction model faces certain challenges.

[0006] Problems caused by selfishness: Most participants are motivated by payment incentives from the crowdsensing platform to participate in the sensing task. In the crowdsensing system, user income is a major factor affecting user participation, that is, the higher the user utility, the more motivated they are to participate in perception. higher

[0007] Problems caused by randomness: The random movement of people or unexpected situations make the user leave the perceived location during the execution of the task, resulting in the incomplete task

Zhang Xiang et al. proposed SS-Model (Single-requesterSingle-bid), SM-Model (Single-requester Multiple-bid) and MM-Model (Multiple-requester Multiple-bid) three incentive models, among which SM-Model is the general form of SS-Model, and MM-Model considers the competition between multiple crowd sensing platforms and the competition between multiple users. However, the three incentive models do not fully consider the problem that the winner quits perception with random probability in the process of performing the task. They all assume that the winner can complete the winning perception task. However, the above assumptions are not realistic.

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