3.Technical Architecture

3.1 System Architecture

VPZONE adopts a microservices architecture and distributed deployment to ensure scalability and high availability:

1. Blockchain infrastructure:

   • Based on Distributed Ledger Technology (DLT), supporting immutable and transparent records.

   • Employs a hybrid model of consortium and public blockchains to meet diverse use case requirements.

2. Layered design:

   • Separates front-end, business logic, and data layers, enabling secure and efficient API gateway management.

   • Data transmission uses TLS encryption protocols to ensure communication security.

3. Modular design:

   • Modular functionality development supports plugin-style extensions, ensuring system flexibility.

   • Optimizes microservices communication efficiency through Service Mesh technologies.

4. Scalability support:

   • Implements sharding techniques for efficient scalability and dynamic resource allocation.

   • Leverages containerization technologies (Docker, Kubernetes) for automated deployment and elastic scaling.

3.2 Data Layer Design

1. Data storage:

   • Combines relational databases (PostgreSQL) and distributed storage (IPFS) to accommodate diverse data requirements.

   • Implements hierarchical encryption for data storage, enhancing privacy protection.

2. Secure backup:

   • Provides automated daily backups with cross-regional storage to prevent regional failures.

   • Uses blockchain technology to record backup logs, ensuring transparent and credible data recovery processes.

3. Data analysis engine:

   • Integrates real-time streaming frameworks (e.g., Apache Flink) for anomaly detection and trading pattern analysis.

   • Offers user profiling tools to enhance personalized services.

4. On-chain notarization:

   • Ensures data integrity through Merkle trees and zero-knowledge proof technologies.

   • Provides auditing and traceability tools to support regulatory compliance needs.

3.3 Matching Engine

1. High-performance algorithms:

   • Optimizes matching efficiency using dynamic data partitioning techniques.

   • Incorporates multi-threaded processing mechanisms to support high-frequency trading needs.

2. Low-latency processing:

   • Introduces lightweight message queues (e.g., Kafka) to enhance order transmission speed.

   • Reduces latency using shared memory models to minimize system calls.

3. Flexible design:

   • Supports multiple order types, including limit orders, market orders, and stop-loss orders.

   • Seamlessly integrates cross-chain trading matching, enabling multi-asset swaps.

3.4 Smart Contract Integration

1. Smart contract platform compatibility:

   • Compatible with Ethereum EVM, Solana, and Polkadot ecosystems, supporting multi-language smart contract development (Solidity, Rust, etc.).

   • Offers one-click contract deployment tools to reduce development barriers.

2. Contract security:

   • Integrates static analysis tools and dynamic runtime monitoring to prevent potential vulnerabilities.

   • Employs off-chain simulation techniques to validate contract logic correctness.

3. Automated trading management:

   • Supports automated settlement and revenue distribution through smart contracts, improving trading efficiency.

   • Provides modular contract templates for developers to quickly deploy complex logic.