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Performance analysis of PoUW consensus mechanism: Fork probability and throughput

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Abstract

Proof of work (PoW) is a popular consensus mechanism for blockchain. However, it, consuming huge computing resources, does not serve useful purpose beyond reaching a consensus. Recently, proof of useful work (PoUW) has been proposed to overcome the drawback of PoW. With PoUW, each miner spends almost all the time in doing useful work (e.g., data classification), and then competes for the winner by the number of its consumed CPU instructions. Therefore, the time of doing useful work is a salient factor which is newly introduced to PoUW. In this paper, focusing on the new factor, we first model the fork probability of PoUW and then quantify its system throughput. Our model takes into account various design parameters (including the time of doing useful work) and produces a closed-form expression of the system throughput. We then run extensive simulations that verify the accuracy and effectiveness of our theoretical model. This study is very helpful for providing theoretically-guided parameter configurations for PoUW.

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Acknowledgements

This work was supported in part by the National Nature Science Foundation of China under Grants 61872451, 61872452 and 61702365, in part by the Macao FDCT under Grants 0098/2018/A3, 0076/2019/A2 and 0062/2020/A2, and in part by the Strategic Priority Research Program of the Chinese Academy of Sciences, Grant No. XDA19080203.

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Authors and Affiliations

  1. Faculty of Information Technology, Macau University of Science and Technology, Taipa, Macau, 00853, China

    Qinglin Zhao, Jianwen Yuan & Li Feng

  2. Suzhou Research Institute, Aerospace Information Research Institute, Chinese Academy of Sciences, Suzhou, 215000, China

    Xianqing Tai

  3. Guangdong Key Laboratory of IoT Information Technology, 111 Center for Intelligent Bath Manufacturing Based On IoT Technology, Guangdong University of Technology, Guangzhou, 510006, Guangdong, China

    Jie Xu

  4. Institute of Microelectronics of the Chinese Academy of Science, Beijing, 100000, China

    Zhijie Ma

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  1. Qinglin Zhao
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  2. Xianqing Tai
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  5. Li Feng
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Correspondence to Li Feng.

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Zhao, Q., Tai, X., Yuan, J. et al. Performance analysis of PoUW consensus mechanism: Fork probability and throughput. Peer-to-Peer Netw. Appl. 15, 1126–1138 (2022). https://doi.org/10.1007/s12083-021-01237-9

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  • DOI: https://doi.org/10.1007/s12083-021-01237-9

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