DAG structure On TFSCC (2)

DAG in blockchain

After having an intuitive understanding of the DAG structure, let's take a look at why blockchain is regarded as a special DAG structure?

According to the article "From Blockchain to DAG (I) - The Ledger Structure and Consensus Mechanism of Blockchain", whether the blockchain forks or not is related to the speed of generating blocks and broadcast speed. When the block generationspeed exceeds the broadcast speed, multiple blocks will be broadcast simultaneously, resulting in forks.

The more forks there are, the lower the security is.In order to reduce forking,Bitcoin found a balance between performance and security by generating a block every ten minutes to reduce forks.Now let's assume that the block generation time is long enough to prevent a new block from being generated before the previous block has finished broadcasting.Then the structure of this blockchain is a single chain.

In fact, due to network latency and other reasons, forking is inevitable in blockchain, so the actual blockchain structure will be as shown in the figure, and only one valid main chain (yellow) will be selected through ledger consensus, and the transaction information in the remaining block (red) is invalid and will not be adopted.

Transformers uses DAG structure to avoid the inability to concurrently execute block packaging in traditional blockchains. If you change the chained storage structure of blocks into a DAG mesh topology, you can achieve concurrent writing.

In the case where the block packaging time remains unchanged, N blocks can be concurrently packaged in the network, and the transactions in the network can be increased by N times. The combination of DAG and blockchain is to solve the efficiency problem. After the transaction is initiated, the network confirmation is broadcast directly.

From the perspective of the topology model above, the evolution from single chain to tree and mesh, from the granularity of blocks to the granularity of transactions, and from single point transitions to concurrent writing all enable transformers to make a qualitative leap in efficiency.

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