基于BLS聚合签名技术的平行链共识算法优化方案

Parallel chain consensus algorithm optimization scheme based on Boneh-Lynn-Shacham aggregate signature technology

目前,平行链的每个共识节点均需发送各自的共识交易到主链上以参与共识,这导致大量的共识交易严重占用主链的区块容量,并且浪费手续费。针对上述问题,利用平行链上的共识交易具有共识数据相同签名不同的特点,结合双线性映射技术,提出一种基于BLS聚合签名技术的平行链共识算法优化方案。首先,用共识节点对交易数据进行签名;然后,用平行链各节点通过点对点(P2P)网络在内部广播共识交易并同步消息;最后,由Leader节点统计共识交易,且当共识交易的数量大于2/3时,将对应的BLS签名数据聚合并发送交易聚合签名到主链上进行验证。实验结果表明,所提方案与原始平行链共识算法相比能够有效解决平行链上共识节点重复发送共识交易到主链的问题,在减少对主链存储空间的占用的同时节省交易手续费,只占用主链存储空间4 KB并且只产生一笔0.01比特元(BTY)的交易手续费。

At present,each consensus node of the parallel chain needs to send its own consensus transaction to the main chain to participate in the consensus.As a result,a large number of consensus transactions occupy the block capacity of the main chain seriously and waste transaction fees.In order to solve the above problems,an optimization scheme of parallel chain consensus algorithm based on BLS(Boneh-Lynn-Shacham)aggregate signature technology was proposed by combining bilinear map technology with the characteristics of the same consensus data and different signatures of consensus trades on parallel chain.Firstly,the transaction data was signed by the consensus node.Then,the consensus transaction was broadcasted by each node of the parallel chain and the message was synchronized internally through P2P(Peer-to-Peer)network.Finally,the consensus transactions were counted by Leader node.When the number of consensus transactions was greater than 2/3,the corresponding BLS signature data was aggregated and the transaction aggregate signature was sent to the main chain for verification.Experimental results show that compared with the original parallel chain consensus algorithm,the proposed scheme can effectively solve the problem of consensus nodes on the parallel chain repeatedly sending consensus transactions to the main chain,save transaction fees with reducing the occupancy of the storage space of the main chain,only occupy 4 KB of the storage space of the main chain and only generate a transaction fee of 0.01 BiT Yuan(BTY).