StratrosAI
  • WhitePaper of StratrosAI
    • Background
      • Introduction
      • Problem Statement
      • Industry Analysis
    • StratrosAI Introduction and Core Features
      • What is StratrosAI?
      • StratrosAI Solution
    • System Architecture and Technical Flow
      • System Architecture
      • Technical Workflow
    • DA Service API
      • gRPC Interfaces
      • ICDA Storage Canister and Confirmation Canister
        • Storage Canister
        • Confirmation Canister
    • Application and Mechanism of the Restaking Feature
      • Advantages of Restaking
      • Working Principle of Restaking
      • Infrastructure
    • Market Potential and Use Cases
      • Market Potential
      • Market Size
      • Use Cases
    • Business Model and Target Users
      • Business Model
      • Target Users
    • Costs, Challenges and Validation
      • Costs and Challenges
      • Validation
      • Open Source
    • Future Development and Competitive Comparison
      • Roadmap
      • Competitive Comparison
    • Conclusion
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  1. WhitePaper of StratrosAI
  2. System Architecture and Technical Flow

System Architecture

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Last updated 4 months ago

StratrosAI’s architecture is designed to offer a secure, efficient operational environment for decentralized AI applications, supporting large-scale data storage, computation, and cross-chain interaction. Its core architecture includes the following key layers:

  1. Staking Layer: This layer comprises ckBTC, ckETH, and other ck-Tokens, which users can stake to support ecosystem security and decentralization while earning yields. StratrosAI integrates a restaking feature, allowing users to maximize asset returns by restaking ckBTC and ckETH. Through restaking, users can earn additional staking rewards and provide security and stability support for DA and AVS AI projects.

  2. Storage Layer: Comprising multiple storage Canisters, this layer provides decentralized data storage support. It ensures secure storage and efficient access to large-scale AI datasets, offering a low-cost, scalable storage environment for AI projects within the AVS ecosystem.

  3. Confirmation Layer: This layer is responsible for transaction and interaction security and integrity within the system. It supports various signature algorithms, including Secp256 K1, Schnorr, and BLS, ensuring secure validation during data transmission and storage.

  4. Boundary Nodes: These nodes serve as intermediaries, connecting the Storage and Confirmation Layers to the Services Layer. Acting as gateways for data flow and verification, boundary nodes facilitate secure and efficient data transfer across different layers, providing access for all services and applications and enabling seamless module interactions within the system.

  5. Services Layer: This layer hosts multiple services to provide foundational support for decentralized applications. Each service module accesses Storage and Confirmation Layer data and functions through boundary nodes, enabling the development of data-driven AI applications.