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
Powered by GitBook
On this page
  1. WhitePaper of StratrosAI
  2. System Architecture and Technical Flow

Technical Workflow

PreviousSystem ArchitectureNextDA Service API

Last updated 4 months ago

The technical workflow of StratrosAI is structured in multiple steps to ensure data and operations are secure and consistent within a decentralized environment. The main workflow components include:

  1. Threshold Signature Confirmations: StratrosAI employs Merkle Trees, BLS confirmation nodes, Schnorr confirmation nodes, and Secp256 K1 confirmation nodes to verify data and transactions. Each confirmation node uses threshold signature confirmation technology to ensure data integrity and security, providing robust protection for data processing in on-chain AI projects.

  2. Canister Services: StratrosAI’s Canister services run on a multi-subnet architecture, supporting distributed deployment of multiple Canister nodes. This service structure ensures the efficient operation and scalability of AI applications, facilitating smooth data exchange and processing between different application modules.

  3. Boundary Nodes Dispersal: Boundary nodes are dispersed throughout the network, ensuring reliable data distribution and retrieval. Each boundary node works closely with the Canister services layer to enable fast and secure data transmission between the services and storage layers, enhancing system performance and scalability.

  4. Service Establishment: StratrosAI supports multiple services (e.g., Service 1, Service 2, etc.), with each service connecting to other layers via boundary nodes. This modular design provides a flexible environment for developing and deploying decentralized AI applications, allowing each module in the services layer to operate independently while maintaining connectivity with storage and confirmation functions.

  5. Staking Process: Users can stake assets like ckBTC, ckETH, etc., in the staking layer and earn additional rewards through StratrosAI’s restaking feature. Restaking allows users to allocate these assets to the DA layer and AVS ecosystem for security support, maximizing asset yield. Through restaking, users not only earn additional staking rewards but also support StratrosAI’s security and decentralization, strengthening network stability.