MicroAlgo Inc. Develops a Blockchain Storage Optimization Solution Based on the Archimedes Optimization Algorithm (AOA)
MicroAlgo Inc. (NASDAQ: MLGO) has announced the development of a blockchain storage optimization solution leveraging the Archimedes Optimization Algorithm (AOA). The solution addresses efficiency bottlenecks in blockchain storage through intelligent algorithmic restructuring of data storage and node collaboration mechanisms.
The system operates across five key stages: data preprocessing, sharding strategy optimization, node resource allocation, consensus mechanism enhancement, and security strategy tuning. The AOA-based solution outperforms traditional approaches, showing 40% better efficiency than Genetic Algorithms and requiring 25% fewer iterations compared to Particle Swarm Optimization. The technology maintains node storage utilization deviation within 15% and reduces load imbalance by 60% compared to conventional methods.
MicroAlgo Inc. (NASDAQ: MLGO) ha annunciato lo sviluppo di una soluzione per l'ottimizzazione dello storage blockchain basata sull'Algoritmo di Ottimizzazione di Archimede (AOA). Questa soluzione affronta i colli di bottiglia nell'efficienza dello storage blockchain tramite una ristrutturazione algoritmica intelligente della memorizzazione dei dati e dei meccanismi di collaborazione tra nodi.
Il sistema opera attraverso cinque fasi principali: pre-elaborazione dei dati, ottimizzazione della strategia di sharding, allocazione delle risorse dei nodi, miglioramento del meccanismo di consenso e regolazione della strategia di sicurezza. La soluzione basata su AOA supera le metodologie tradizionali, mostrando un'efficienza superiore del 40% rispetto agli Algoritmi Genetici e richiedendo un 25% in meno di iterazioni rispetto all'Ottimizzazione a Sciame di Particelle. La tecnologia mantiene la deviazione nell'utilizzo dello storage dei nodi entro il 15% e riduce lo squilibrio del carico del 60% rispetto ai metodi convenzionali.
MicroAlgo Inc. (NASDAQ: MLGO) ha anunciado el desarrollo de una solución de optimización del almacenamiento en blockchain que utiliza el Algoritmo de Optimización de Arquímedes (AOA). La solución aborda los cuellos de botella en la eficiencia del almacenamiento blockchain mediante una reestructuración algorítmica inteligente del almacenamiento de datos y los mecanismos de colaboración entre nodos.
El sistema opera en cinco etapas clave: preprocesamiento de datos, optimización de la estrategia de fragmentación (sharding), asignación de recursos de nodos, mejora del mecanismo de consenso y ajuste de la estrategia de seguridad. La solución basada en AOA supera los enfoques tradicionales, mostrando una eficiencia un 40% mejor que los Algoritmos Genéticos y requiriendo un 25% menos de iteraciones en comparación con la Optimización por Enjambre de Partículas. La tecnología mantiene la desviación en la utilización de almacenamiento de nodos dentro del 15% y reduce el desequilibrio de carga en un 60% respecto a los métodos convencionales.
MicroAlgo Inc. (NASDAQ: MLGO)는 아르키메데스 최적화 알고리즘(AOA)을 활용한 블록체인 저장소 최적화 솔루션 개발을 발표했습니다. 이 솔루션은 데이터 저장 및 노드 협력 메커니즘의 지능형 알고리즘 재구성을 통해 블록체인 저장소의 효율성 병목 현상을 해결합니다.
시스템은 데이터 전처리, 샤딩 전략 최적화, 노드 자원 할당, 합의 메커니즘 향상, 보안 전략 조정의 다섯 가지 주요 단계로 운영됩니다. AOA 기반 솔루션은 기존 방법보다 뛰어나 유전 알고리즘보다 40% 더 높은 효율성을 보이며 입자 군집 최적화에 비해 25% 적은 반복 횟수를 필요로 합니다. 이 기술은 노드 저장소 사용 편차를 15% 이내로 유지하고 기존 방법 대비 부하 불균형을 60% 감소시킵니다.
MicroAlgo Inc. (NASDAQ : MLGO) a annoncé le développement d'une solution d'optimisation du stockage blockchain utilisant l'algorithme d'optimisation d'Archimède (AOA). Cette solution résout les goulets d'étranglement en efficacité du stockage blockchain grâce à une restructuration algorithmique intelligente du stockage des données et des mécanismes de collaboration entre nœuds.
Le système fonctionne en cinq étapes clés : prétraitement des données, optimisation de la stratégie de sharding, allocation des ressources des nœuds, amélioration du mécanisme de consensus et ajustement de la stratégie de sécurité. La solution basée sur l'AOA surpasse les approches traditionnelles, affichant une efficacité supérieure de 40 % par rapport aux algorithmes génétiques et nécessitant 25 % d'itérations en moins comparé à l'optimisation par essaim de particules. La technologie maintient la déviation de l'utilisation du stockage des nœuds dans une limite de 15 % et réduit le déséquilibre de charge de 60 % par rapport aux méthodes conventionnelles.
MicroAlgo Inc. (NASDAQ: MLGO) hat die Entwicklung einer Blockchain-Speicheroptimierungslösung bekannt gegeben, die den Archimedes-Optimierungsalgorithmus (AOA) nutzt. Die Lösung behebt Effizienzengpässe im Blockchain-Speicher durch intelligente algorithmische Umstrukturierung der Datenspeicherung und der Mechanismen zur Zusammenarbeit der Knoten.
Das System arbeitet in fünf Schlüsselphasen: Datenvorverarbeitung, Optimierung der Sharding-Strategie, Ressourcenzuweisung der Knoten, Verbesserung des Konsensmechanismus und Anpassung der Sicherheitsstrategie. Die auf AOA basierende Lösung übertrifft traditionelle Ansätze und zeigt eine 40% bessere Effizienz als genetische Algorithmen und benötigt 25% weniger Iterationen im Vergleich zur Partikelschwarmoptimierung. Die Technologie hält die Abweichung der Knotenspeicherauslastung innerhalb von 15% und reduziert die Lastungleichheit um 60% gegenüber herkömmlichen Methoden.
- Developed innovative blockchain storage optimization solution showing significant performance improvements
- Solution demonstrates 40% better efficiency than Genetic Algorithms
- Reduces iterations by 25% compared to Particle Swarm Optimization
- Achieves 60% reduction in load imbalance compared to traditional methods
- Controls node storage utilization deviation within 15%
- Technology is still in development phase with unproven real-world implementation
- Significant investment may be required for quantum computing acceleration and ASIC chip development
- Complex integration requirements with existing blockchain systems
Insights
MicroAlgo announces innovative blockchain storage optimization technology with promising technical architecture but lacks evidence of market readiness or commercial impact.
MicroAlgo's new blockchain storage solution leverages the Archimedes Optimization Algorithm (AOA), applying fluid dynamics principles to solve distributed storage challenges. The approach models storage nodes as objects with properties like density (storage cost), volume (available space), and buoyancy (transmission efficiency) to dynamically optimize data placement and node collaboration.
The five-stage technical workflow represents a comprehensive approach to blockchain data management: preprocessing with differentiated strategies for various data types, dynamic sharding optimization based on data characteristics, adaptive node load balancing, consensus mechanism enhancement, and security strategy tuning. This holistic architecture addresses the core inefficiencies that typically plague blockchain storage systems.
The company claims performance advantages over traditional approaches, including
The future roadmap outlines ambitious plans including quantum computing acceleration, dedicated ASIC chips, and cross-chain protocol integration. While technically intriguing, these represent significant engineering challenges requiring substantial resources to implement.
Missing from this announcement is evidence of implementation maturity, market validation, or commercialization timeline. The press release doesn't mention beta testing, deployment metrics, customer feedback, or how this technology fits within MicroAlgo's business model. The highly technical nature of the announcement suggests this may be more of a research initiative than a market-ready product.
For blockchain infrastructure, innovative optimization approaches offer significant value proposition as networks scale, but commercial success requires translating technical capabilities into solutions for specific industry pain points—a connection not established in this announcement.
SHENZHEN, May 08, 2025 (GLOBE NEWSWIRE) -- MicroAlgo Inc. Develops a Blockchain Storage Optimization Solution Based on the Archimedes Optimization Algorithm (AOA)
Shenzhen, May. 08, 2025/––MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), announced a focus on addressing the efficiency bottlenecks in blockchain storage by introducing the Archimedes Optimization 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." MicroAlgo has deeply integrated this algorithm into blockchain storage scenarios. By targeting core issues such as data sharding strategies, node resource allocation, and consensus efficiency optimization, the company has constructed a multi-objective optimization model. AOA adaptively switches between global search and local exploitation to solve for optimal storage solutions under complex constraints, achieving multiple goals including reduced data redundancy, balanced node load, and enhanced storage performance. This injects intelligent and dynamic adjusting ability into blockchain storage systems.
MicroAlgo’s blockchain storage optimization solution uses AOA as its core engine and spans the entire data-on-chain lifecycle. The technical workflow is divided into five key stages:data Preprocessing, sharding Strategy Optimization, node Resource Allocation, consensus Mechanism Enhancement and security Strategy Tuning.
Data Feature Analysis and Preprocessing: Multi-dimensional feature extraction is performed on data destined for the blockchain. Depending on the characteristics of different data units, differentiated preprocessing strategies are applied: lightweight serialized encoding for structured transaction data; chunk-based hashing for unstructured file data; and homomorphic encryption or zero-knowledge proof preprocessing for privacy-sensitive data. The feature vectors generated during preprocessing, along with storage constraints (such as maximum node storage capacity, network latency thresholds, and data redundancy safety margins), collectively form the input parameter space for AOA.
Dynamic Sharding Strategy Optimization: AOA models the data sharding problem as an optimal partitioning task in multi-dimensional space. During initialization, storage nodes in the blockchain network are abstracted as "virtual objects," where each object's "density" corresponds to the node's storage cost coefficient, "volume" to its remaining available storage space, and "buoyancy" to its network transmission efficiency. In the iterative process, AOA performs a global exploration phase simulating the random movement of objects in fluid, traversing various shard combinations and employing collision detection to avoid local optima. In the local exploitation phase, the algorithm converges toward the current optimal sharding plan based on gradient information and dynamically adjusts the storage node allocation for each data block. For example, frequently accessed "hot data" is preferentially stored with multiple replicas on nodes with low latency and strong computational performance to ensure fast response, while infrequently accessed "cold data" is stored using erasure coding on nodes with lower cost and larger capacity, thereby reducing redundancy while ensuring availability. Through adjustment of the adaptive Transfer Factor, the algorithm dynamically balances exploration and exploitation, ultimately producing a sharding strategy that optimizes both storage efficiency and access performance.
Node Load Balancing and Resource Scheduling: At the node level, AOA builds a real-time load monitoring model, collecting dynamic status data such as storage utilization, CPU usage, and network bandwidth consumption, which serve as input for the algorithm’s "force analysis." When node load exceeds a threshold (e.g., storage utilization surpasses
Consensus Efficiency Enhancement and Block Optimization: At the consensus layer, AOA is deeply integrated with blockchain consensus mechanisms to optimize block generation and validation. Taking PBFT-like consensus as an example, the algorithm reformulates block packaging as a multi-objective optimization problem: it seeks balance between block size limits (e.g., 1MB maximum) and transaction throughput by analyzing transaction type (transfer vs. smart contract), priority (urgent vs. regular), and correlation (cross-contract vs. independent transactions). Based on this analysis, it dynamically adjusts transaction sorting and grouping within blocks. During node election, AOA calculates each node's "trust density" in real time, based on historical performance (e.g., participation in consensus, data validation accuracy, and network stability), and prioritizes high-trust nodes to participate in consensus, reducing the risk of malicious interference. For PoW-based consensus, AOA predicts hash power distribution and network load to dynamically adjust mining difficulty targets, thereby shortening block intervals and reducing energy waste while maintaining decentralization.
Adaptive Security Strategy Optimization: To meet blockchain storage demands for privacy protection and data security, AOA builds an encryption parameter optimization model. In homomorphic encryption scenarios, the algorithm automatically selects optimal parameters (e.g., modulus size, key length) based on data sensitivity and computational complexity, reducing overhead while maintaining cryptographic strength. 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
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. Empirical data shows this approach controls the standard deviation of node storage utilization within
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.
About MicroAlgo Inc.
MicroAlgo Inc. (the “MicroAlgo”), a Cayman Islands exempted company, is dedicated to the development and application of bespoke central processing algorithms. MicroAlgo provides comprehensive solutions to customers by integrating central processing algorithms with software or hardware, or both, thereby helping them to increase the number of customers, improve end-user satisfaction, achieve direct cost savings, reduce power consumption, and achieve technical goals. The range of MicroAlgo's services includes algorithm optimization, accelerating computing power without the need for hardware upgrades, lightweight data processing, and data intelligence services. MicroAlgo's ability to efficiently deliver software and hardware optimization to customers through bespoke central processing algorithms serves as a driving force for MicroAlgo's long-term development.
Forward-Looking Statements
This press release contains statements that may constitute "forward-looking statements." Forward-looking statements are subject to numerous conditions, many of which are beyond the control of MicroAlgo, including those set forth in the Risk Factors section of MicroAlgo's periodic reports on Forms 10-K and 8-K filed with the SEC. Copies are available on the SEC's website, www.sec.gov. Words such as "expect," "estimate," "project," "budget," "forecast," "anticipate," "intend," "plan," "may," "will," "could," "should," "believes," "predicts," "potential," "continue," and similar expressions are intended to identify such forward-looking statements. These forward-looking statements include, without limitation, MicroAlgo's expectations with respect to future performance and anticipated financial impacts of the business transaction.
MicroAlgo undertakes no obligation to update these statements for revisions or changes after the date of this release, except as may be required by law.
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MicroAlgo Inc.
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Email: ir@microalgor.com
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