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Ethereum: Pruning the branches in Merkle Tree
When Building Blockchain Networks on Top of Ethereum, Developers Often Want to Optimize Storage and Network Performance. One Common Technique Used to Achieve This Goal is Pruning the Branches in the Merkle Tree.
In Traditional Bitcoin, The Merkle Tree, A Complex Data Structure That Allows for Efficient Validation and Verification of Transactions Across The Network. However, as the size of the blockchain increases, so does the number of leaves (or transactions) in the Merkle Tree. This can lead to storage space inefficiencies and slower transaction processing times.
The Bitcoin Paper, which Satoshi Nakamoto Published in 2008, Highlights One Solution for Pruning branches in the Merkle Tree: by malfunction only the hash values of their children, rather than the actual transactions Themselves. This approach allows developers to reduce the amount of data that needs to be stored and transmitted across the network.
In Ethereum, This Technique is Known as « Leaf Pruning ». By Using Leaf-Level Hashing (I.E., malfunction only the hashes of the internal nodes), Ethereum Developers can Eliminate Redundant Data and Save Storage Space. However, this also mean that each transaction will have ferwer children in the Merkle Tree, which can Impact the Security and Efficiency of the Network.
For Example, Consider A Simple Example of Two Transactions: T1 andT2. In The Merkle Tree, Both T1 and T2 would be represented as Leaves (I.E., Hashes). However, Since T1 is only a child of t2, the brandele tree for t1 would not include its own hash value. This can make it more difficult to Verify Transactions on the Ethereum Network.
In practice, Leaf Pruning in Ethereum Has Been implemented through Various Means, Including the use of Specialized Hardware and Software Libraries. However, The Technique Still Requires Careful Consideration When Designing Large-Scale Blockchain Applications.
AS Developers Continue to Build and Expand Their Ethereum-Based Projects, The Importance of Efficient Storage and Data Management Will Only Grow. By Understanding How to Prune Branches in the Merkle Tree, We Can Optimize Our Network’s Performance, Reduce Costs, And Improve Overall User Experience.