Paper Info
Title
Blockchain-Based Model for Nondeterministic Crowdsensing Strategy With Vehicular Team Cooperation
Abstract
Smart vehicles can cooperate in teams to perform crowdsensing tasks in smart cities. A critical challenge in this regard is to build a secure model for nondeterministic vehicle teams to achieve maximum social welfare. Although several crowdsensing models have been proposed, none of them has focused on real-time vehicle teamwork. In this article, to the best of our knowledge, we propose the first secure model, called blockchain-based nondeterministic teamwork cooperation (BNTC), for nondeterministic teamwork cooperation in a vehicular crowdsensing system. We model the system as a multiconditional NP-complete problem by explicitly considering the dynamic features of task issuers and workers. To solve the problem, we propose the winning teams selected (WTS) algorithm based on a reverse auction and utilize a knapsack-based method to solve the models. We consider the credit of teams for determining the payment. Thus, we propose a credit-based team payment (CTP) algorithm for BNTC to maximize the welfare of the system. We also propose a general blockchain-based framework to address trust issues and security challenges to make the method suitable for use in practical applications. Based on theoretical analyses and extensive simulations, we demonstrate that the proposed model performs better than the baselines and can achieve the maximum social welfare. Implementation with Ethereum suggests our model can operate within a reasonable cost.
Year
DOI
Venue
2020
10.1109/JIOT.2020.3000048
IEEE Internet of Things Journal
Keywords
DocType
Volume
Blockchain,mobile crowdsensing (MCS),smart cities,team perception
Journal
7
Issue
ISSN
Citations 
9
2327-4662
5
PageRank 
References 
Authors
0.39
0
5
Name
Order
Citations
PageRank
Jianrong Wang1175.69
Xinlei Feng250.39
Tianyi Xu36414.20
Huansheng Ning484783.48
Tie Qiu589580.18