MicroAlgo Inc. Develops a Blockchain Storage Optimization Solution Based on the Archimes Optimization Algorithm
MLGO
Published on 05/08/2025 at 08:30, updated on 05/08/2025 at 11:38
MicroAlgo Inc. announced a focus on addressing the efficiency bottlenecks in blockchain storage by introducing the Archimedes Optimization Al algorithm (AOA) into distributed storage architecture. Through intelligent algorithmic restructuring of data storage and node collaboration mechanisms, they aim to provide an innovative solution for large-scale blockchain applications. The Archimedes Optimization Algorithm (AOA) is a metaheuristic algorithm that simulates the force-driven motion of objects in a fluid.
Its core concept is derived from the principle of Archimedean buoyancy: the buoyant force exerted on an object immersed in a fluid equals the weight of the fluid displaced. By dynamically adjusting parameters such as density, volume, and acceleration, the algorithm models the iterative motion of an object from a random initial position toward an optimal "equilibrium point." In zero-knowledge proof contexts, AOA enhances efficiency by optimizing randomness selection and constraint composition in proof generation, minimizing on-chain storage demands. To mitigate risks of data tampering and node failure, AOA monitors anomalies in on-chain data hash values in real time, and uses cross-verification across multiple node replicas to quickly identify compromised nodes and trigger recovery workflows.
During recovery, the algorithm selects the optimal replica node for synchronization based on node trust level and network connectivity, ensuring rapid system consistency restoration. Compared to traditional approaches, MicroAlgo's AOA-based blockchain storage optimization solution offers significant advantages. Conventional storage strategies often rely on fixed rules--such as uniform sharding or round-robin allocation--which are prone to falling into the pitfalls of local optima.
In contrast, AOA leverages a global search mechanism inspired by fluid dynamics, enabling it to rapidly explore over a million sharding combinations within a complex network of tens of millions of nodes. Its solution efficiency surpasses that of Genetic Algorithms (GA) by 40%, and reduces the number of iterations needed by 25% compared to Particle Swarm Optimization (PSO), effectively avoiding the blindness of static strategies. The node status and data characteristics of blockchain networks are in constant flux.
The AOA transfer factor mechanism dynamically switches search modes based on real-time load data: during network congestion, it enhances local exploitation to quickly stabilize system performance; during low load, it activates global exploration to discover optimal resource allocation solutions. Emirical data shows this approach controls the standardiation of node storage utilization within 15%, reducing load imbalance by 60% compared to traditional methods. As blockchain penetrates deeper into Web3.0, the metaverse, and other fields, on-chain data volume will experience explosive growth.
MicroAlgo's AOA technology will continue to evolve in the following directions: at the algorithmic level, it plans to introduce quantum computing acceleration to boost AOA's iteration speed by over 100 times, addressing optimization needs for exabyte-scale data; at the architectural level, it will explore "algorithm-hardware" co-design, developing dedicated ASIC chips for AOA hardware acceleration to reduce energy costs of blockchain nodes; at the ecosystem level, it will promote deep integration of AOA with cross-chain protocols (e.g., Polkadot, Cosmos) to build a cross-chain storage resource scheduling network, achieving the ultimate goal of "one-point on-chain, network-wide intelligent storage." In the future, AOA is poised to become the "intelligent hub of blockchain storage, driving distributed storage from " rule-driven" to "algorithmic autonomy," laying the technical foundation for unlocking data value in the digital economy era.