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A Thin Client Error-Correcting Data Storage Framework Based on Blockchain

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Urban Intelligence and Applications

Part of the book series: Studies in Distributed Intelligence ((SDI))

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Abstract

Traditional centralized and distributed data storage systems are hard to achieve data integrity. A blockchain is more resistant to modification of the data than widely used technologies, such as digital signature and digital watermarking. Each node in a blockchain is required to store data so that all the nodes should have powerful computing and storage capacity. Centralized service points make a thin client possible at the cost of decreasing decentralization that a blockchain possesses. In addition, a wrong block breaks the data consistency in the system, and existing data dissemination protocol cannot solve the wrong block problem efficiently. This paper proposes a thin client error-correcting data storage framework based on blockchain. The data of the clients are stored as blocks in the system to achieve the data integrity. The data requests are handled by randomly selected blockchain nodes. We propose two error-correcting mechanisms to validate and correct the wrong data blocks. We also analyze the performance of the proposed framework with respect to data tamper proof, consensus, and thin client. The proposed framework has the characteristics of lightweight client, data tamper proof, and high resource utilization in the blockchain network.

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Acknowledgements

This work was partly supported by the National Natural Science Foundation of China (U1836102), the Anhui Provincial Natural Science Foundation (1608085MF142), the open project of State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System (CEMEE2018Z0102B), and the National Undergraduate Training Programs for Innovation and Entrepreneurship (201710359019).

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Correspondence to Yuqi Fan .

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Fan, Y., Zou, J., Liu, S., Yin, Q., Guan, X., Yuan, X. (2020). A Thin Client Error-Correcting Data Storage Framework Based on Blockchain. In: Yuan, X., Elhoseny, M. (eds) Urban Intelligence and Applications. Studies in Distributed Intelligence . Springer, Cham. https://doi.org/10.1007/978-3-030-45099-1_3

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  • DOI: https://doi.org/10.1007/978-3-030-45099-1_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-45098-4

  • Online ISBN: 978-3-030-45099-1

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