Journal of Korean Society of Industrial and Systems Engineering (산업경영시스템학회지)

Society of Korea Industrial and System Engineering (한국산업경영시스템학회)
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Decentralization Analysis and Control Model Design for PoN Distributed Consensus Algorithm

PoN 분산합의 알고리즘 탈중앙화 분석 및 제어 모델 설계

  • Choi, Jin Young (Department of Industrial Engineering, Ajou University) ;
  • Kim, Young Chang (Electronics and Telecommunications Research Institute) ;
  • Oh, Jintae (Electronics and Telecommunications Research Institute) ;
  • Kim, Kiyoung (Electronics and Telecommunications Research Institute)
  • Received : 2021.12.15
  • Accepted : 2022.01.19
  • Published : 2022.03.31
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Abstract

The PoN (Proof of Nonce) distributed consensus algorithm basically uses a non-competitive consensus method that can guarantee an equal opportunity for all nodes to participate in the block generation process, and this method was expected to resolve the first trilemma of the blockchain, called the decentralization problem. However, the decentralization performance of the PoN distributed consensus algorithm can be greatly affected by the network transaction transmission delay characteristics of the nodes composing the block chain system. In particular, in the consensus process, differences in network node performance may significantly affect the composition of the congress and committee on a first-come, first-served basis. Therefore, in this paper, we presented a problem by analyzing the decentralization performance of the PoN distributed consensus algorithm, and suggested a fairness control algorithm using a learning-based probabilistic acceptance rule to improve it. In addition, we verified the superiority of the proposed algorithm by conducting a numerical experiment, while considering the block chain systems composed of various heterogeneous characteristic systems with different network transmission delay.

Keywords

Acknowledgement

This work was supported by the Institute of Information & communications Technology Planning & Evaluation(IITP) grant funded by the Korea government(MSIT) (No. 2021-0-00118, Development of decentralized consensus composition technology for large-scale nodes)

References

  1. Gochhayat, S., Shetty, S., Mukkamala, R., Foytik, P., Kamhoua, G. and Njilla, L. Measuring Decentrality in Blockchain Based Systems, IEEE Access, 2020, Vol.8, 10.1109/ACCESS.2020.3026577.
  2. Kim, Y.C., Kim, K.Y., Oh, J.T., Kim, D.G. and Choi, J.Y., Simulator design and performance analysis of BADA distributed consensus algorithm, Journal of Society of Korea Industrial and Systems Engineering, 2020, Vol.43, No.4, 168-177. https://doi.org/10.11627/jkise.2020.43.4.168
  3. Kimani, D., Adams, K., Attah-Boakye, R., Ullah, S., Frecknall-Hughes, J. and Kim, J., Blockchain, business and the fourth industrial revolution: Whence, whither, wherefore and how?, Technol Forecast Soc Change, 2020, Vol. 161, pp. 143-174.
  4. Kwon, Y., Liu, J., Kim, M., Song, D. and Kim, Y., Impossibility of full decentralization in permissionless blockchains, Proc. 1st ACM Conference on Advances in Financial Technologies, Zurich, Switzerland, 2019.
  5. Oh, J.T., Park, J.Y., Kim, Y.C., and Kim K.Y., Algorithm based on Byzantine agreement among decentralized agents (BADA), ETRI Journal, 2020, pp. 1-14.
  6. Viswanathan, S. and Shah, A. The Scalability Trilemma in Blockchain, https://medium.com/@aakash_13214/thescalability-trilemma-in-blockchain-75fb57f646df, 2018.
  7. Yoo, S. M., 4th industrial revolution and blockchain: Focusing on data economics, The Journal of The Korean Institute of Communication Sciences, 2020, Vol. 37, No. 2, pp. 23-30.
  8. Zheng, Z., Xie, S., Dai H., and Wang, H., An overview of blockchain technology: Architecture consensus and future trends, Proc. IEEE Int. Congr. Big Data (BigData Congr.), Honolulu, USA, 2017, pp. 557-564.