Dynamic Evolutionary Game-based Modeling, Analysis and Performance Enhancement of Blockchain Channels

Pei Yun Zhang, Meng Chu Zhou, Chen Xi Li, Abdullah Abusorrah

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

The recent development of channel technology has promised to reduce the transaction verification time in blockchain operations. When transactions are transmitted through the channels created by nodes, the nodes need to cooperate with each other. If one party refuses to do so, the channel is unstable. A stable channel is thus required. Because nodes may show uncooperative behavior, they may have a negative impact on the stability of such channels. In order to address this issue, this work proposes a dynamic evolutionary game model based on node behavior. This model considers various defense strategies' cost and attack success ratio under them. Nodes can dynamically adjust their strategies according to the behavior of attackers to achieve their effective defense. The equilibrium stability of the proposed model can be achieved. The proposed model can be applied to general channel networks. It is compared with two state-of-the-art blockchain channels: Lightning network and Spirit channels. The experimental results show that the proposed model can be used to improve a channel's stability and keep it in a good cooperative stable state. Thus its use enables a blockchain to enjoy higher transaction success ratio and lower transaction transmission delay than the use of its two peers.

Original languageEnglish (US)
Pages (from-to)188-202
Number of pages15
JournalIEEE/CAA Journal of Automatica Sinica
Volume10
Issue number1
DOIs
StatePublished - Jan 1 2023

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Information Systems
  • Control and Optimization
  • Artificial Intelligence

Keywords

  • Blockchain
  • channel network
  • evolutionary game
  • malicious behavior
  • secure computing
  • stability analysis

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