Journal
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
Volume -, Issue -, Pages -Publisher
SPRINGER
DOI: 10.1007/s10586-023-04108-5
Keywords
Blockchain; Consensus; Cellular goore game; Learning automata; Cognitive
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A blockchain is a distributed general ledger that records cryptographic transactions after authentication using consensus algorithms. AI and blockchain have gained significant attention and growth in recent years, and applying AI to solve blockchain challenges can yield fascinating results. Cognitive blockchain utilizes AI to improve performance and overcome challenges.
A blockchain is a distributed general ledger that, after authentication, records cryptographic transactions. Consensus algorithms are used to record transactions in the general ledger. Consensus algorithms are designed to achieve reliability in a network involving untrusted nodes. Although several protocols have been in operation for several years, they still have drawbacks. Artificial intelligence (AI) and blockchain are two technologies that have received a lot of attention in the last decade and are rapidly growing. Fascinating results can be obtained by applying AI to solve existing blockchain challenges. Cognitive blockchain employs artificial intelligence to improve performance and solve its challenges. Cognitive blockchain can perceive network conditions, analyze gained knowledge, effectively decide, and adapt to improve network performance. CGG, which models distributed systems with many simple objects that interact with each other locally, could be a suitable learning model for the cognitive blockchain because of the distributed nature of the blockchain network. We presented a new consensus protocol based on the Cellular Goore Game (CGG) as a cognitive model for blockchain consensus that could be used as intelligence consensus in the cognitive blockchain. The proposed consensus protocol partitions the nodes that take part in the consensus, organizes the CGG model to verify a new block after publication, and finally, based on the CGG's result, confirms or rejects the block. A new intelligent consensus approach improves fault tolerance, scalability, and performance and reduces participation costs in consensus for private and consortium blockchains. We conduct a qualitative study of the proposed protocol and analyze its experimental performance. The results show that the proposed schema performs well in the presence of numerous faulty nodes, as well as in terms of scalability and throughput.
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