Crowd sensing data delivery based on tangle DAG network

doi:10.19682/j.cnki.1005-8885.2022.1016

The Journal of China Universities of Posts and Telecommunications ›› 2023, Vol. 30 ›› Issue (3): 88-98.doi: 10.19682/j.cnki.1005-8885.2022.1016

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Crowd sensing data delivery based on tangle DAG network

Chen Hui, Jiang Xiaoling, Wu Tianting, Mou Xingyu

1. Operation Monitoring Department, Jilin Province Meteorological Information Network Center, Changchun 130062, China 2. Appraisal Department, Jilin Province Meteorological Disaster Prevention Technology Center, Changchun 130062, China

Received:2021-09-01 Revised:2022-11-01 Online:2023-06-30 Published:2023-06-30
Contact: Wu Tianting E-mail:686982385@qq.com

Abstract

Abstract: In view of the fact that current data delivery methods are not enough to meet the security requirements of today's distributed crowd sensing, and the data delivery methods are not flexible enough, this paper proposes a crowd sensing data interaction method based on tangle directed acyclic graph (DAG) network. In this method, users and platforms are regarded as nodes of the network in the process of performing crowd sensing tasks. First, the heaviest chain is generated through the main chain strategy to ensure the stability of the network. Then, the hidden Markov model ( HMM ) prediction model is used to improve the correlation of the perceived data to improve the performance. Then, the confidential transaction and commitment algorithm is used to ensure the reliability of the transaction, overcome the security risks faced by the trusted third party, and simplify the group intelligence aware transaction mode. Finally, through simulation experiments, the security and feasibility of the group intelligence aware data delivery method based on tangle DAG network are verified.

Key words: data delivery, crowd sensing, tangle directed acyclic graph (DAG), confidential transactions

CLC Number:

TP393

Chen Hui, Jiang Xiaoling, Wu Tianting, Mou Xingyu. Crowd sensing data delivery based on tangle DAG network[J]. The Journal of China Universities of Posts and Telecommunications, 2023, 30(3): 88-98.

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Crowd sensing data delivery based on tangle DAG network

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