A Double-Auction-Based Mechanism to Stimulate Secondary Users for Cooperative Sensing in Cognitive Radio Networks

Zhu, Yuqing; Wu, Weili; Li, Deying; Ding, Ling

doi:10.1109/tvt.2014.2360840

Cited by 5 publications

(2 citation statements)

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“…The auction mechanism, as a technique of game theory, has been used to solve the allocation and pricing problems in a variety of applications, such as mobile crowdsensing [20] [21], edge computing [22] [23], and spectrum trading [24] [25]. Zhang et al [20] surveyed the diverse incentive strategies that encouraged users to take part in mobile crowdsourcing.…”

Section: Related Workmentioning

confidence: 99%

“…Jiao et al [23] proposed an auction-based market model for computing resource allocation between the edge server and miners. Zhu et al [24] devised a truthful double auction mechanism for cooperative sensing in radio networks. Zheng et al [25] achieved a social welfare maximization problem by re-distributing wireless channels, while they took the strategy-proof into consideration as well.…”

Section: Related Workmentioning

confidence: 99%

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Reliable Traffic Monitoring Mechanisms Based on Blockchain in Vehicular Networks

Guo,

Ding,

2020

Preprint

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The real-time traffic monitoring is a fundamental mission in a smart city to understand traffic conditions and avoid dangerous incidents. In this paper, we propose a reliable and efficient traffic monitoring system that integrates blockchain and the Internet of vehicles technologies effectively. It can crowdsource its tasks of traffic information collection to vehicles that run on the road instead of installing cameras in every corner. First, we design a lightweight blockchain-based information trading framework to model the interactions between traffic administration and vehicles. It guarantees reliability, efficiency, and security during executing trading. Second, we define the utility functions for the entities in this system and come up with a budgeted auction mechanism that motivates vehicles to undertake the collection tasks actively. In our algorithm, it not only ensures that the total payment to the selected vehicles does not exceed a given budget, but also maintains the truthfulness of auction process that avoids some vehicles to offer unreal bids for getting greater utilities. Finally, we conduct a group of numerical simulations to evaluate the reliability of our trading framework and performance of our algorithms, whose results demonstrate their correctness and efficiency perfectly.

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