AI Resource Layer

The AI Resource Layer manages the registration, listing, and allocation of AI infrastructure resources such as network bandwidth, GPUs, CPUs, storage, and computing power. This layer ensures efficient resource utilization and availability for AI model training and execution. This includes:

• Resource Registration: Allows users to register their AI resources.

• Resource Discovery: Identifies available computing resources, such as GPUs, CPUs, and storage, from various providers.

• Resource Listing: Displays available resources for lease or purchase.

• Resource Allocation: Dynamically allocates these resources based on demand and availability to ensure efficient utilization.

• Resource Monitoring: Continuously monitors resource usage to optimize performance and ensure reliability.

Code for Resource Management (Node.js with Express)

const express = require('express');
const router = express.Router();

// Sample data
let resources = [
    { id: 1, type: 'GPU', owner: '0xOwnerAddress1', price: 10, available: true },
    { id: 2, type: 'CPU', owner: '0xOwnerAddress2', price: 5, available: true }
];

// Register a new resource
router.post('/register', (req, res) => {
    const { id, type, owner, price } = req.body;
    resources.push({ id, type, owner, price, available: true });
    res.status(201).send('Resource registered');
});

// List all resources
router.get('/list', (req, res) => {
    res.json(resources);
});

// Allocate resource
router.post('/allocate/:id', (req, res) => {
    const resourceId = parseInt(req.params.id);
    const resource = resources.find(r => r.id === resourceId);

    if (resource && resource.available) {
        resource.available = false;
        res.send('Resource allocated');
    } else {
        res.status(404).send('Resource not available');
    }
});

module.exports = router;