Quantitative cooperation analysis among cross-chain smart contracts

In cross-chain scenarios, there are different blockchains that need cooperation. The cooperation between different blockchains is completed through smart contracts, which jointly complete cross-chain tasks. When numerous cooperative smart contracts are involved, smart contracts form a complex interactive network, which makes it difficult to evaluate the cooperation. A general model is needed 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 quantitative condition-trigger model. Then, a method of calculating trigger probability by using graph weight is proposed. As the edge weight lacks the information of interaction probability, we introduce the dimension of the edge weight to calculate the interaction probability. The results show that the proposed method can effectively analyze the cross-chain cooperation between smart contracts.