@inproceedings{f75d48af671f4c6cb04caed17e9e90c0,
title = "SOBC: A Smart Ocean Oriented Blockchain System for Cross-organizational Data Sharing",
abstract = "The refinement of the division of labor among organizations in the field of ocean exploration has made the cross-organizational data sharing a common phenomenon. Although the blockchain system can solve the trust problem among organizations, the unstable Underwater Wireless Sensor Network (UWSN) and high network traffic costs of satellite network hindered the application of blockchain in the smart ocean. In this paper, we propose the smart ocean blockchain architecture (SOBC) that supports high transaction concurrency and saves network traffic to achieve trusted cross-organizational data sharing in the ocean exploration field. First, we design the SOBC architecture and use channels to isolate different businesses to ensure data privacy and high transaction concurrency. Second, we design blockchain smart contracts to implement data transmission rules among regulatory agencies, data providers and data demanders to achieve trusted data sharing. Finally, we design a channel-based consistency protocol to reduce the network traffic consumption when nodes reconnect to the core network. We use data collected from the spectrum detection platform to verify the effect of SOBC by simulating the ocean exploration network conditions. The experimental results show that the SOBC is superior to the Ethereum-based blockchain architecture in transactions concurrency supporting. Besides, compared with Ethereum, the SOBC reduces network traffic consumption by 70\% under unstable network conditions.",
keywords = "Blockchain, Cross-organizational data sharing, Internet of underwater things, Ocean exploration, Smart ocean, Underwater wireless sensor network",
author = "Yuchen Tian and Yansong Wang and Weiguo Tian and Haiwen Du and Xiaofang Li and Dongjie Zhu",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Singapore Pte Ltd.; 6th International Conference on Data Mining and Big Data, DMBD 2021 ; Conference date: 20-10-2021 Through 22-10-2021",
year = "2021",
doi = "10.1007/978-981-16-7502-7\_27",
language = "英语",
isbn = "9789811675010",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "250--262",
editor = "Ying Tan and Yuhui Shi and Albert Zomaya and Hongyang Yan and Jun Cai",
booktitle = "Data Mining and Big Data - 6th International Conference, DMBD 2021, Proceedings",
address = "德国",
}