RhinoSpider | P2P resource-sharing network
  • Introduction
    • Our POV on Issues with AI Infrastructure
  • Getting Started
  • Core Components
  • Contribution Modes
  • Reward Mechanism
  • Security & Privacy
  • Multi-Token System
  • Data Marketplace Dynamics
  • Target Customers
  • Network Governance
  • Key Calculations
  • FAQs
  • P2P Resource-Sharing Network on ICP
  • Our Vision
  • AI-based Data Quality Enhancements
  • AI-based Node Performance Enhancements
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P2P Resource-Sharing Network on ICP

RhinoSpider is a peer-to-peer resource-sharing network that rewards users for contributing idle bandwidth and computational power to decentralized applications and AI.

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Last updated 3 months ago

The RhinoSpider Core Team has chosen the Internet Computer Protocol (ICP) as the native ecosystem of RhinoSpider. This page explains the intent behind the choice -- note that there may be additional factors not covered in this page, due to the focus of this page on covering only the most important aspects.

1. Decentralization

ICP enables true decentralization, hosting both frontend and backend of applications entirely on-chain. For RhinoSpider, this means:

  • Spider Nodes (Light and Full):

    • Hosted as canisters (ICP’s advanced smart contracts), ensuring decentralized and secure operation of bandwidth and computational contributions.

    • Light Nodes utilize ICP’s ultra-fast query calls, while Full Nodes handle heavy computational tasks via update calls without needing centralized intermediaries.

  • Data Marketplace:

    • Decentralized operations of RhinoSpider's marketplace can run seamlessly within ICP’s subnets, ensuring high availability and eliminating the risks associated with centralized systems.

2. Scalability for data aggregation

ICP's Chain Key Technology allows for horizontal scaling by distributing workloads across subnets. This scalability supports RhinoSpider’s Sovereign Data Rollup, ensuring the aggregation and structuring of large-scale data contributions for AI training.

3. High-speed real-time data retrieval

ICP delivers web-speed performance, essential for RhinoSpider’s Live Context Retrieval (LCR) engine:

  • Query response times average 100ms, enabling real-time access to data.

  • Update calls complete in approximately 2 seconds, ensuring that AI models and decentralized applications always receive fresh, accurate data streams.

This speed guarantees RhinoSpider can eventually meet the demands of AI systems and decentralized applications requiring live data.

4. Cost predictability

ICP’s reverse gas model offers RhinoSpider:

  • Predictable and reduced hosting costs, as canisters pay for computational resources using cycles.

  • Lower operational expenses compared to Ethereum’s gas fees or AWS infrastructure, allowing RhinoSpider to pass greater rewards to its contributors.

This cost efficiency ensures RhinoSpider remains competitive, both as a service provider and a decentralized data marketplace.

6. Decentralized AI

ICP’s support for on-chain AI inference and training aligns with RhinoSpider’s computational mining layer: ICP’s canisters can host and execute AI workloads, enabling RhinoSpider to allocate computational tasks efficiently across its nodes. Data stored and processed on-chain ensures long-term availability and verifiability, vital for AI training datasets.

7. Motoko-based smart contracts

  • Familiar Development: Motoko’s syntax is user-friendly and similar to JavaScript/TypeScript, which our team is already experienced with, allowing our developers to write smart contracts with relative ease.

  • State Persistence: Motoko’s ability to maintain stable variables ensures RhinoSpider’s canisters can store data across invocations, essential for managing bandwidth usage, computational contributions, and reward distribution.

  • Concurrency Handling: Motoko’s actor-based concurrency model is ideal for handling RhinoSpider’s real-time interactions, such as task allocation and data retrieval.

8. Transparent governance with the NNS

ICP’s Network Nervous System (NNS) empowers RhinoSpider with decentralized governance:

  • Stakeholders can vote on critical decisions, such as scaling operations or upgrading components.

  • The NNS ensures seamless implementation of updates without network disruptions, maintaining RhinoSpider’s reliability.

9. Proof of Hosting

RhinoSpider can leverage ICP’s infrastructure to showcase its capabilities through a proof-of-hosting page:

  • Real-time metrics of active users, resource usage, and hosting costs can be displayed. This data can even be fed to relevant dashboards such as the IoTEX DePIN Hub tracker.

  • These on-chain proofs validate RhinoSpider’s decentralization and operational transparency, reinforcing its position as a leader in Web3 infrastructure.

Tentative tech architecture diagram