Quantitative Cooperation Analysis among Cross-chain Smart Contracts
- Hong Su
Abstract
In cross-chain scenarios, there are different blockchains, which need to
cooperate. Cooperation among different blockchains is done by smart
contracts that work together to complete cross-chain tasks. When
numerous cooperative smart contracts are involved, smart contracts form
a complex interaction network, which makes it difficult to evaluate the
cooperation. It needs a common model to quantitatively analyze the
cross-chain cooperation of associated smart contracts. In this paper, we
model the cooperation among smart contracts as conditions and their
corresponding actions, the condition-trigger model. Then we propose the
method to calculate the cooperation probabilities by the graph weight.
As the edge weight lacks the information of interaction probabilities,
we introduce the dimension of the edge weight to calculate the
probabilities. Finally, we verify the proposed condition-trigger model
and its different types. It demonstrates that our proposed methods can
effectively analyze the cross-chain cooperation among smart contracts.