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Aleo Privacy Blockchain Major Upgrade: Synthesis Puzzle Algorithm Analysis and Incentive Testnet Launch
Aleo: A New Breakthrough in Privacy-Protection Blockchain
Aleo is a blockchain project dedicated to privacy protection, achieving a higher level of privacy and scalability through zero-knowledge proof technology ( ZKP ). The core idea of the project is to allow users to verify their identity and process data while protecting personal data.
Project Overview
Privacy
The core of Aleo is zero-knowledge proofs ( ZKPs ) technology, which enables the execution of transactions and smart contracts while protecting privacy. Details of users' transactions, such as the sender and amount, are hidden by default. This design not only protects user privacy but also allows for selective disclosure when necessary, making it very suitable for the development of DeFi applications. The main components include:
Leo Programming Language: Adapted from Rust, specifically designed for developing zero-knowledge applications ( ZKApps ), reducing the requirements for developers' knowledge of cryptography.
snarkVM and snarkOS: snarkVM allows off-chain computation while only verifying the results on-chain, thereby improving efficiency. snarkOS ensures the security of data and computation, and supports permissionless functionality execution.
zkCloud: Provides a secure and private off-chain computing environment that supports programming interactions between users, organizations, and DAOs.
Aleo also provides an integrated development environment (IDE) and a software development kit (SDK), supporting developers to quickly write and publish applications. Developers can deploy applications in Aleo's program registry without relying on third parties, reducing platform risk.
Scalability
Aleo adopts an off-chain processing method, where transactions are first computed for proof on the user's device, and then only the verification results are uploaded to the Blockchain. This approach greatly enhances transaction processing speed and system scalability, avoiding issues like network congestion and high fees similar to Ethereum.
Consensus Mechanism
Aleo has introduced AleoBFT, a hybrid architecture consensus mechanism that combines the instant finality of validators with the computational power of provers. AleoBFT not only improves the decentralization of the network but also enhances its performance and security.
Block Quick Finality: AleoBFT ensures that each block is immediately confirmed after generation, enhancing node stability and user experience.
Decentralized Assurance: By separating block production from the generation of coinbase, validators are responsible for generating blocks, while provers perform proof calculations to prevent a minority of entities from monopolizing the network.
Incentive Mechanism: Validators and provers share Block rewards; encouraging provers to become validators by staking tokens, thereby enhancing the network's decentralization and computing power.
Aleo allows developers to create applications that are not restricted by gas, making it particularly suitable for long-running applications such as machine learning.
Latest Developments
Aleo plans to launch the incentive testnet on July 1st, here is some important latest information:
ARC-100 Proposal Passed: This proposal involves compliance aspects, locking funds on the network, and security measures such as delayed transactions. The team is currently making final adjustments.
Validator Incentive Program: It will launch on July 1st, aiming to validate the new puzzle mechanism. The program will run until July 15th, during which 1 million Aleo points will be allocated as rewards.
Token Supply: The initial supply is 1.5 billion tokens, with an initial circulating supply of about 10%( to be determined). These tokens mainly come from Coinbase tasks(7.5 million), which will be distributed within the first six months, including rewards for staking, running validators, and validating nodes.
Testnet Beta Reset: This is the last network reset, and after it is completed, no new features will be added. The network will be similar to the mainnet.
Code freeze: Completed a week ago.
Validator Node Expansion Plan: The initial number of validator nodes is 15, with a target to increase to 50 within the year, and ultimately reach 500. To become a delegator requires 10,000 tokens, while becoming a validator requires 10 million tokens, and these amounts will gradually decrease over time.
Synthesis Puzzle Algorithm Analysis
Aleo recently updated the puzzle algorithm, with the new algorithm no longer focusing on the generation of zk proof results, but rather on generating the intermediate data witness before the proof is created. Here is a brief introduction to the new algorithm:
Consensus Process
Prover calculates the puzzle constructs solutions and broadcasts them to the network.
Validator aggregates transactions and solutions for new blocks, ensuring that the number of solutions does not exceed the consensus limit.
The legitimacy of the Solution needs to verify whether its epoch_hash and proof_target meet the network requirements, and whether the number of solutions in the block is within the limits.
Effective solutions can earn consensus rewards.
Synthesis Puzzle core mechanism
Each epoch generates a fixed EpochProgram, which is used by all provers together.
Each puzzle calculation is called a nonce, composed of the address receiving the mining reward, epoch_hash, and the random number counter.
The EpochProgram generates a random number sampled from the instruction set based on the current epoch_hash.
Use nonce as a random seed to generate the input for EpochProgram.
Aggregate the R1CS and input corresponding to the EpochProgram to perform witness computation.
After calculating all the witnesses, convert them into a sequence of leaf nodes for the Merkle tree.
Calculate the merkle root and convert it to the solution's proof_target to determine if it meets the current epoch requirements.
If the requirements are met, submit the solution and broadcast.
This update changes puzzle from generating proof to generating witness. The solution calculation logic within each epoch is consistent, but there are significant differences between different epochs. The new algorithm discards the previous GPU optimizations for MSM and NTT calculations, and due to the serial execution dependencies in the witness generation process, achieving parallelization faces significant challenges.