Akash Network：去中心化云如何挑战AWS影视渲染垄断

// SPDX-License-Identifier: MIT
pragma solidity ^0.8.20;

import "@openzeppelin/contracts/token/ERC20/ERC20.sol";
import "@openzeppelin/contracts/access/AccessControl.sol";
import "@openzeppelin/contracts/utils/ReentrancyGuard.sol";

contract AkashRenderMarket is ERC20, AccessControl, ReentrancyGuard {
    bytes32 public constant PROVIDER_ROLE = keccak256("PROVIDER_ROLE");
    bytes32 public constant RENDERER_ROLE = keccak256("RENDERER_ROLE");

    enum LeaseStatus { PENDING, ACTIVE, COMPLETED, CANCELLED, DISPUTED }

    struct ComputeProvider {
        address provider;
        string gpuModel;
        uint256 gpuCount;
        uint256 gpuMemory;    // MB per GPU
        uint256 cpuCores;
        uint256 ramMB;
        uint256 storageGB;
        uint256 pricePerHour; // AKT per hour
        uint256 reputation;   // 0-1000
        uint256 totalLeases;
        uint256 uptimeHours;
        bool isActive;
    }

    struct RenderLease {
        uint256 leaseId;
        address tenant;
        address provider;
        string containerImage;
        string sceneCID;
        uint256 durationHours;
        uint256 gpuCount;
        uint256 totalPrice;
        LeaseStatus status;
        uint256 startTime;
        uint256 endTime;
        bytes32 workHash;
    }

    uint256 private _leaseCounter;
    uint256 public constant MIN_REPUTATION = 100;
    uint256 public constant MAX_DURATION = 720; // 30 days max
    uint256 public constant DISPUTE_PERIOD = 86400; // 24 hours

    mapping(address => ComputeProvider) public providers;
    mapping(uint256 => RenderLease) public leases;
    mapping(address => uint256) public escrowBalances;
    mapping(uint256 => uint256) public disputeVotes;

    event ProviderRegistered(address indexed provider, string gpuModel, uint256 pricePerHour);
    event LeaseCreated(uint256 indexed leaseId, address indexed tenant, address indexed provider, uint256 totalPrice);
    event LeaseCompleted(uint256 indexed leaseId, bytes32 workHash);
    event LeaseDisputed(uint256 indexed leaseId, address indexed initiator);

    constructor() ERC20("Akash Token", "AKT") {
        _grantRole(DEFAULT_ADMIN_ROLE, msg.sender);
        _mint(msg.sender, 100000000 * 10**18); // 100M initial supply
    }

    function registerProvider(
        string memory _gpuModel,
        uint256 _gpuCount,
        uint256 _gpuMemory,
        uint256 _cpuCores,
        uint256 _ramMB,
        uint256 _storageGB,
        uint256 _pricePerHour
    ) external {
        require(providers[msg.sender].provider == address(0), "Already registered");

        providers[msg.sender] = ComputeProvider({
            provider: msg.sender,
            gpuModel: _gpuModel,
            gpuCount: _gpuCount,
            gpuMemory: _gpuMemory,
            cpuCores: _cpuCores,
            ramMB: _ramMB,
            storageGB: _storageGB,
            pricePerHour: _pricePerHour,
            reputation: 500,
            totalLeases: 0,
            uptimeHours: 0,
            isActive: true
        });

        _grantRole(PROVIDER_ROLE, msg.sender);
        emit ProviderRegistered(msg.sender, _gpuModel, _pricePerHour);
    }

    function createLease(
        address _provider,
        string memory _containerImage,
        string memory _sceneCID,
        uint256 _durationHours,
        uint256 _gpuCount
    ) external payable nonReentrant {
        require(providers[_provider].isActive, "Provider not active");
        require(providers[_provider].gpuCount >= _gpuCount, "Insufficient GPUs");
        require(_durationHours <= MAX_DURATION, "Duration too long");
        require(providers[_provider].reputation >= MIN_REPUTATION, "Low reputation");

        uint256 totalPrice = providers[_provider].pricePerHour * _durationHours * _gpuCount;
        require(balanceOf(msg.sender) >= totalPrice, "Insufficient AKT balance");

        _leaseCounter++;
        uint256 leaseId = _leaseCounter;

        // Transfer AKT to escrow
        _transfer(msg.sender, address(this), totalPrice);
        escrowBalances[leaseId] = totalPrice;

        leases[leaseId] = RenderLease({
            leaseId: leaseId,
            tenant: msg.sender,
            provider: _provider,
            containerImage: _containerImage,
            sceneCID: _sceneCID,
            durationHours: _durationHours,
            gpuCount: _gpuCount,
            totalPrice: totalPrice,
            status: LeaseStatus.ACTIVE,
            startTime: block.timestamp,
            endTime: block.timestamp + (_durationHours * 3600),
            workHash: bytes32(0)
        });

        providers[_provider].totalLeases++;

        emit LeaseCreated(leaseId, msg.sender, _provider, totalPrice);
    }

    function completeLease(uint256 _leaseId, bytes32 _workHash) external {
        RenderLease storage lease = leases[_leaseId];
        require(lease.provider == msg.sender, "Not provider");
        require(lease.status == LeaseStatus.ACTIVE, "Lease not active");

        lease.status = LeaseStatus.COMPLETED;
        lease.workHash = _workHash;
        lease.endTime = block.timestamp;

        // Release payment to provider
        uint256 payment = escrowBalances[_leaseId];
        _transfer(address(this), lease.provider, payment);
        escrowBalances[_leaseId] = 0;

        // Update reputation
        providers[lease.provider].reputation = 
            min(1000, providers[lease.provider].reputation + 5);

        emit LeaseCompleted(_leaseId, _workHash);
    }

    function disputeLease(uint256 _leaseId) external {
        RenderLease storage lease = leases[_leaseId];
        require(msg.sender == lease.tenant || msg.sender == lease.provider, "Not party");
        require(lease.status == LeaseStatus.ACTIVE, "Lease not active");
        require(block.timestamp <= lease.endTime + DISPUTE_PERIOD, "Dispute period expired");

        lease.status = LeaseStatus.DISPUTED;
        emit LeaseDisputed(_leaseId, msg.sender);
    }

    function resolveDispute(uint256 _leaseId, bool _favorTenant) 
        external onlyRole(DEFAULT_ADMIN_ROLE) {
        RenderLease storage lease = leases[_leaseId];
        require(lease.status == LeaseStatus.DISPUTED, "Not disputed");

        if (_favorTenant) {
            // Return funds to tenant
            _transfer(address(this), lease.tenant, escrowBalances[_leaseId]);
            providers[lease.provider].reputation = 
                max(0, providers[lease.provider].reputation - 100);
        } else {
            // Release to provider
            _transfer(address(this), lease.provider, escrowBalances[_leaseId]);
        }

        escrowBalances[_leaseId] = 0;
        lease.status = LeaseStatus.COMPLETED;
    }

    function getProvider(address _provider) 
        external view returns (ComputeProvider memory) {
        return providers[_provider];
    }

    function getLease(uint256 _leaseId) 
        external view returns (RenderLease memory) {
        return leases[_leaseId];
    }

    function getMarketPrice() 
        external view returns (uint256 avgPrice) {
        uint256 totalPrice = 0;
        uint256 count = 0;
        
        for (uint256 i = 1; i <= _leaseCounter; i++) {
            if (leases[i].status == LeaseStatus.ACTIVE) {
                totalPrice += leases[i].totalPrice;
                count++;
            }
        }
        
        return count > 0 ? totalPrice / count : 0;
    }

    function min(uint256 a, uint256 b) private pure returns (uint256) {
        return a < b ? a : b;
    }

    function max(uint256 a, uint256 b) private pure returns (uint256) {
        return a > b ? a : b;
    }
}

"""
Akash Network渲染任务调度器 - 去中心化云渲染模拟
模拟竞价、部署和渲染执行的全流程
"""

import asyncio
import random
import hashlib
import time
from typing import Dict, List, Optional, Tuple
from dataclasses import dataclass, field
from enum import Enum
import statistics

class GPUModel(Enum):
    RTX_4090 = ("NVIDIA RTX 4090", 1200, 24576, 2.5)
    RTX_4080 = ("NVIDIA RTX 4080", 850, 16384, 2.0)
    RTX_3090 = ("NVIDIA RTX 3090", 950, 24576, 1.8)
    A100 = ("NVIDIA A100", 1800, 81920, 5.0)
    A6000 = ("NVIDIA A6000", 1500, 49152, 4.0)
    RTX_4070 = ("NVIDIA RTX 4070", 650, 12288, 1.2)
    RX_7900XTX = ("AMD RX 7900 XTX", 880, 24576, 1.5)
    
    def __init__(self, name, benchmark, memory, base_price):
        self.model_name = name
        self.benchmark = benchmark
        self.memory = memory
        self.base_price = base_price

@dataclass
class ComputeProvider:
    provider_id: str
    gpu_model: GPUModel
    gpu_count: int
    cpu_cores: int
    ram_gb: int
    storage_gb: int
    price_per_hour: float
    reputation: float
    location: str
    uptime_percent: float
    is_available: bool
    current_load: float = 0.0
    total_earnings: float = 0.0
    leases_completed: int = 0

@dataclass
class RenderJob:
    job_id: str
    tenant: str
    scene_cid: str
    frame_count: int
    resolution: Tuple[int, int]
    samples_per_pixel: int
    gpu_memory_required: int
    estimated_hours: float
    max_budget: float
    priority: int  # 1-5
    status: str = "pending"
    created_at: float = 0.0
    assigned_providers: List[str] = field(default_factory=list)
    frames_completed: int = 0
    total_cost: float = 0.0

@dataclass
class BidProposal:
    provider_id: str
    job_id: str
    price_per_hour: float
    estimated_duration: float
    total_price: float
    score: float = 0.0

class AkashRenderScheduler:
    """
    Akash Network渲染任务调度器
    模拟去中心化云渲染的竞价、调度和执行
    """
    
    def __init__(self):
        self.providers: Dict[str, ComputeProvider] = {}
        self.jobs: Dict[str, RenderJob] = {}
        self.active_leases: Dict[str, str] = {}  # job_id -> provider_id
        self.completed_jobs: List[RenderJob] = []
        self.market_prices: List[float] = []
        
    def register_provider(
        self,
        gpu_model: GPUModel,
        gpu_count: int,
        cpu_cores: int,
        ram_gb: int,
        storage_gb: int,
        price_per_hour: float,
        location: str,
        uptime_percent: float
    ) -> str:
        """注册算力提供者"""
        provider_id = hashlib.sha256(
            f"provider_{len(self.providers)}_{time.time()}".encode()
        ).hexdigest()[:12]
        
        provider = ComputeProvider(
            provider_id=provider_id,
            gpu_model=gpu_model,
            gpu_count=gpu_count,
            cpu_cores=cpu_cores,
            ram_gb=ram_gb,
            storage_gb=storage_gb,
            price_per_hour=price_per_hour,
            reputation=500,
            location=location,
            uptime_percent=uptime_percent,
            is_available=True
        )
        
        self.providers[provider_id] = provider
        return provider_id
    
    def submit_job(
        self,
        tenant: str,
        scene_cid: str,
        frame_count: int,
        resolution: Tuple[int, int],
        samples_per_pixel: int,
        gpu_memory_required: int,
        max_budget: float,
        priority: int = 3
    ) -> str:
        """提交渲染任务"""
        job_id = hashlib.sha256(
            f"render_job_{len(self.jobs)}_{time.time()}".encode()
        ).hexdigest()[:16]
        
        # 预估渲染时间
        estimated_hours = (
            frame_count * resolution[0] * resolution[1] * samples_per_pixel
        ) / (1000000000 * 60 * 60)  # 简化的估算公式
        
        job = RenderJob(
            job_id=job_id,
            tenant=tenant,
            scene_cid=scene_cid,
            frame_count=frame_count,
            resolution=resolution,
            samples_per_pixel=samples_per_pixel,
            gpu_memory_required=gpu_memory_required,
            estimated_hours=estimated_hours,
            max_budget=max_budget,
            priority=priority,
            created_at=time.time()
        )
        
        self.jobs[job_id] = job
        return job_id
    
    async def run_auction(self, job_id: str) -> Optional[BidProposal]:
        """运行反向拍卖，选择最优提供者"""
        job = self.jobs[job_id]
        if not job:
            return None
        
        bids = []
        
        for provider_id, provider in self.providers.items():
            if not provider.is_available:
                continue
            if provider.current_load >= 0.9:
                continue
            if provider.gpu_model.memory < job.gpu_memory_required:
                continue
            
            # 计算出价
            price_per_hour = provider.price_per_hour
            
            # 根据GPU数量和任务复杂度调整
            effective_gpu_count = min(provider.gpu_count, 4)  # 最多使用4个GPU
            estimated_duration = job.estimated_hours / effective_gpu_count
            total_price = price_per_hour * estimated_duration
            
            if total_price > job.max_budget:
                continue
            
            # 计算综合评分
            score = (
                (1 / (total_price + 1)) * 30 +  # 价格得分
                (provider.reputation / 1000) * 25 +  # 信誉得分
                (provider.uptime_percent / 100) * 20 +  # 在线率得分
                (1 / (estimated_duration + 1)) * 15 +  # 速度得分
                (effective_gpu_count / 8) * 10  # 算力得分
            )
            
            bid = BidProposal(
                provider_id=provider_id,
                job_id=job_id,
                price_per_hour=price_per_hour,
                estimated_duration=estimated_duration,
                total_price=total_price,
                score=score
            )
            
            bids.append(bid)
        
        if not bids:
            return None
        
        # 选择最优出价
        bids.sort(key=lambda b: b.score, reverse=True)
        winner = bids[0]
        
        return winner
    
    async def deploy_and_render(
        self,
        job_id: str,
        winner: BidProposal
    ) -> bool:
        """部署并执行渲染任务"""
        job = self.jobs[job_id]
        provider = self.providers[winner.provider_id]
        
        # 更新状态
        job.status = "deploying"
        job.assigned_providers.append(winner.provider_id)
        provider.current_load += 0.5
        job.total_cost = winner.total_price
        
        # 模拟容器部署
        await asyncio.sleep(random.uniform(0.5, 2))
        job.status = "rendering"
        
        self.active_leases[job_id] = winner.provider_id
        
        # 模拟渲染进度
        frames_per_second = random.randint(1, 10)  # 模拟每秒渲染帧数
        total_frames = job.frame_count
        
        while job.frames_completed < total_frames:
            await asyncio.sleep(1)
            job.frames_completed += frames_per_second
            if job.frames_completed > total_frames:
                job.frames_completed = total_frames
            
            # 每10%报告一次进度
            if job.frames_completed % (total_frames // 10) < frames_per_second:
                progress = (job.frames_completed / total_frames) * 100
                print(f"  任务 {job_id[:8]}: {progress:.0f}% "
                      f"({job.frames_completed}/{total_frames} 帧)")
        
        # 完成
        job.status = "completed"
        provider.current_load -= 0.5
        provider.total_earnings += winner.total_price
        provider.leases_completed += 1
        provider.reputation = min(1000, provider.reputation + 10)
        
        self.completed_jobs.append(job)
        del self.active_leases[job_id]
        
        return True
    
    def get_market_stats(self) -> Dict:
        """获取市场统计"""
        active_jobs = sum(1 for j in self.jobs.values() if j.status == "rendering")
        pending_jobs = sum(1 for j in self.jobs.values() if j.status == "pending")
        completed = len(self.completed_jobs)
        
        total_gpu = sum(
            p.gpu_count for p in self.providers.values()
            if p.is_available
        )
        
        avg_price = statistics.mean(
            [p.price_per_hour for p in self.providers.values() if p.is_available]
        ) if self.providers else 0
        
        return {
            "providers": len(self.providers),
            "total_gpus": total_gpu,
            "active_jobs": active_jobs,
            "pending_jobs": pending_jobs,
            "completed_jobs": completed,
            "avg_price_akt": round(avg_price, 2),
            "total_earnings": round(
                sum(p.total_earnings for p in self.providers.values()), 2
            ),
            "avg_reputation": round(
                statistics.mean([p.reputation for p in self.providers.values()]), 1
            ) if self.providers else 0
        }

# 运行模拟
async def main():
    scheduler = AkashRenderScheduler()
    
    print("=== Akash Network 去中心化渲染模拟 ===\n")
    
    # 注册算力提供者
    print("注册算力提供者...")
    providers_data = [
        (GPUModel.RTX_4090, 4, 16, 64, 2000, 1.5, "US-West", 99.5),
        (GPUModel.RTX_4090, 2, 8, 32, 1000, 1.2, "US-East", 98.0),
        (GPUModel.A100, 8, 64, 256, 8000, 5.0, "US-West", 99.9),
        (GPUModel.RTX_4080, 4, 16, 64, 2000, 0.8, "EU-West", 97.5),
        (GPUModel.RTX_3090, 6, 24, 96, 4000, 0.6, "Asia-East", 95.0),
        (GPUModel.RTX_4070, 2, 8, 32, 1000, 0.4, "Asia-South", 90.0),
        (GPUModel.A6000, 4, 32, 128, 4000, 3.5, "EU-North", 99.0),
        (GPUModel.RX_7900XTX, 2, 16, 64, 2000, 0.7, "Australia", 93.0),
        (GPUModel.RTX_4090, 8, 32, 128, 8000, 2.0, "US-West", 99.8),
        (GPUModel.RTX_3090, 4, 16, 64, 2000, 0.5, "EU-West", 96.0),
    ]
    
    for gpu, count, cpu, ram, storage, price, loc, uptime in providers_data:
        pid = scheduler.register_provider(gpu, count, cpu, ram, storage, price, loc, uptime)
        print(f"  {pid[:8]}: {gpu.model_name} x{count}, "
              f"{price}AKT/h, {loc}")
    
    # 提交渲染任务
    print("\n提交渲染任务...")
    jobs_data = [
        ("QmSceneA", 2400, (3840, 2160), 1024, 8192, 500, 5),  # 高优先级
        ("QmSceneB", 1200, (1920, 1080), 256, 4096, 100, 3),   # 中等优先级
        ("QmSceneC", 4800, (4096, 2160), 2048, 16384, 2000, 4), # 高优先级大项目
        ("QmSceneD", 600, (1920, 1080), 128, 2048, 50, 2),     # 低优先级
        ("QmSceneE", 1800, (3840, 2160), 512, 8192, 300, 3),   # 中等优先级
    ]
    
    job_ids = []
    for scene, frames, res, samples, gpu_mem, budget, priority in jobs_data:
        jid = scheduler.submit_job(
            "0xCreator", scene, frames, res, samples, gpu_mem, budget, priority
        )
        job_ids.append(jid)
        print(f"  任务 {jid[:8]}: {frames}帧, {res[0]}x{res[1]}, "
              f"预算{budget}AKT, 优先级{priority}")
    
    # 运行拍卖和部署
    print("\n=== 运行竞价和部署 ===\n")
    
    for jid in job_ids:
        job = scheduler.jobs[jid]
        print(f"处理任务 {jid[:8]}...")
        
        # 运行拍卖
        winner = await scheduler.run_auction(jid)
        if not winner:
            print(f"  任务 {jid[:8]}: 没有可用提供者")
            continue
        
        print(f"  中标: {winner.provider_id[:8]}, "
              f"价格: {winner.price_per_hour}AKT/h, "
              f"总价: {winner.total_price:.2f}AKT, "
              f"评分: {winner.score:.1f}")
        
        # 部署渲染
        success = await scheduler.deploy_and_render(jid, winner)
        if success:
            print(f"  任务 {jid[:8]}: 渲染完成 ✓\n")
    
    # 市场统计
    print("\n=== 市场统计 ===")
    stats = scheduler.get_market_stats()
    for key, value in stats.items():
        print(f"  {key}: {value}")
    
    # 成本对比
    print("\n=== 成本对比（vs AWS） ===")
    total_akash_cost = sum(j.total_cost for j in scheduler.completed_jobs)
    total_aws_cost = total_akash_cost * 8  # AWS约8倍价格
    savings = total_aws_cost - total_akash_cost
    
    print(f"  Akash总成本: {total_akash_cost:.2f} AKT")
    print(f"  AWS等效成本: {total_aws_cost:.2f} USD")
    print(f"  节省: {savings:.2f} USD ({(savings/total_aws_cost*100):.0f}%)")

if __name__ == "__main__":
    asyncio.run(main())

// Akash Network渲染任务管理SDK
const { ethers } = require('ethers');
const axios = require('axios');
const crypto = require('crypto');

class AkashRenderSDK {
  constructor(akashRpcUrl, contractAddress) {
    this.provider = new ethers.JsonRpcProvider(akashRpcUrl);
    this.contract = new ethers.Contract(
      contractAddress,
      [
        'function createLease(address provider, string containerImage, string sceneCID, uint256 durationHours, uint256 gpuCount) payable',
        'function completeLease(uint256 leaseId, bytes32 workHash)',
        'function getLease(uint256 leaseId) view returns (tuple(uint256 leaseId, address tenant, address provider, string containerImage, string sceneCID, uint256 durationHours, uint256 gpuCount, uint256 totalPrice, uint8 status, uint256 startTime, uint256 endTime, bytes32 workHash))',
        'function getProvider(address provider) view returns (tuple(address provider, string gpuModel, uint256 gpuCount, uint256 gpuMemory, uint256 cpuCores, uint256 ramMB, uint256 storageGB, uint256 pricePerHour, uint256 reputation, uint256 totalLeases, uint256 uptimeHours, bool isActive))'
      ],
      this.provider
    );
    
    this.jobCache = new Map();
  }

  /**
   * 搜索可用算力提供者
   */
  async searchProviders(filters = {}) {
    const {
      minGpuMemory = 4096,
      maxPrice = 10,
      minReputation = 100,
      location = null
    } = filters;
    
    // 模拟搜索提供者
    const providers = [];
    for (let i = 0; i < 20; i++) {
      const gpuModels = [
        { name: 'RTX 4090', memory: 24576, price: 1.5 },
        { name: 'A100', memory: 81920, price: 5.0 },
        { name: 'RTX 4080', memory: 16384, price: 0.8 },
        { name: 'RTX 3090', memory: 24576, price: 0.6 },
        { name: 'RTX 4070', memory: 12288, price: 0.4 }
      ];
      
      const gpu = gpuModels[i % gpuModels.length];
      if (gpu.memory >= minGpuMemory && gpu.price <= maxPrice) {
        providers.push({
          address: `0x${crypto.randomBytes(20).toString('hex')}`,
          gpuModel: gpu.name,
          gpuMemory: gpu.memory,
          pricePerHour: gpu.price,
          reputation: Math.floor(Math.random() * 500 + 500),
          location: ['US-West', 'US-East', 'EU-West', 'Asia-East', 'Australia'][i % 5],
          gpuCount: Math.floor(Math.random() * 4) + 1
        });
      }
    }
    
    return providers.sort((a, b) => a.pricePerHour - b.pricePerHour);
  }

  /**
   * 部署渲染任务
   */
  async deployRenderJob(
    jobConfig,
    provider,
    signer
  ) {
    const {
      sceneCID,
      frameCount,
      resolution,
      renderEngine = 'blender',
      priority = 'normal'
    } = jobConfig;
    
    const contract = this.contract.connect(signer);
    
    // 创建容器镜像描述
    const containerImage = `${renderEngine}:latest`;
    
    // 估算时长和成本
    const estimatedHours = this.estimateRenderTime(
      frameCount, resolution, priority
    );
    
    const gpuCount = Math.min(
      provider.gpuCount,
      Math.ceil(frameCount / 100) // 每100帧至少1个GPU
    );
    
    const totalCost = provider.pricePerHour * estimatedHours * gpuCount;
    
    console.log(`部署渲染任务:`);
    console.log(`  场景: ${sceneCID}`);
    console.log(`  帧数: ${frameCount}`);
    console.log(`  分辨率: ${resolution.width}x${resolution.height}`);
    console.log(`  提供者: ${provider.gpuModel} x${gpuCount}`);
    console.log(`  预估时长: ${estimatedHours}小时`);
    console.log(`  预估成本: ${totalCost} AKT`);
    
    // 创建链上租约
    const tx = await contract.createLease(
      provider.address,
      containerImage,
      sceneCID,
      Math.ceil(estimatedHours),
      gpuCount,
      { value: ethers.parseEther(totalCost.toString()) }
    );
    
    const receipt = await tx.wait();
    
    // 解析租约ID
    const event = receipt.logs.find(
      log => log.fragment && log.fragment.name === 'LeaseCreated'
    );
    
    const leaseId = event ? event.args[0].toString() : null;
    
    const job = {
      leaseId,
      provider: provider.address,
      sceneCID,
      frameCount,
      resolution,
      estimatedHours,
      totalCost,
      gpuCount,
      status: 'deploying',
      createdAt: Date.now(),
      receipt
    };
    
    this.jobCache.set(leaseId, job);
    
    return job;
  }

  /**
   * 预估渲染时间
   */
  estimateRenderTime(frameCount, resolution, priority) {
    const pixelCount = resolution.width * resolution.height;
    const baseTime = (frameCount * pixelCount) / (1000000000/3600);
    
    const priorityMultiplier = {
      'low': 2.0,
      'normal': 1.0,
      'high': 0.5,
      'urgent': 0.25
    };
    
    return baseTime * (priorityMultiplier[priority] || 1.0);
  }

  /**
   * 监控渲染进度
   */
  async monitorJob(leaseId) {
    const job = this.jobCache.get(leaseId);
    if (!job) {
      throw new Error('任务不存在');
    }
    
    // 模拟进度监控
    const totalFrames = job.frameCount;
    const progress = {
      leaseId,
      framesCompleted: 0,
      totalFrames,
      percentage: 0,
      status: 'rendering',
      estimatedRemaining: job.estimatedHours
    };
    
    // 模拟进度更新
    for (let i = 0; i <= 10; i++) {
      await new Promise(resolve => setTimeout(resolve, 1000));
      progress.framesCompleted = Math.floor(totalFrames * (i / 10));
      progress.percentage = i * 10;
      progress.estimatedRemaining = job.estimatedHours * (1 - i / 10);
      
      console.log(`  进度: ${progress.percentage}% ` +
        `(${progress.framesCompleted}/${totalFrames}) ` +
        `剩余: ${progress.estimatedRemaining.toFixed(1)}小时`);
    }
    
    progress.status = 'completed';
    return progress;
  }

  /**
   * 验证渲染结果
   */
  async verifyRenderResult(leaseId, expectedHash) {
    const job = this.jobCache.get(leaseId);
    if (!job) {
      throw new Error('任务不存在');
    }
    
    // 模拟获取渲染结果哈希
    const resultHash = crypto
      .createHash('sha256')
      .update(`${leaseId}:${job.sceneCID}:${Date.now()}`)
      .digest('hex');
    
    const isMatch = resultHash === expectedHash;
    
    return {
      leaseId,
      expectedHash,
      actualHash: resultHash,
      isMatch,
      verified: isMatch,
      timestamp: new Date().toISOString()
    };
  }

  /**
   * 完成租约并释放支付
   */
  async completeLease(leaseId, workHash, signer) {
    const contract = this.contract.connect(signer);
    
    const tx = await contract.completeLease(
      leaseId,
      ethers.keccak256(ethers.toUtf8Bytes(workHash))
    );
    
    const receipt = await tx.wait();
    
    console.log(`租约 ${leaseId} 完成, 支付已释放`);
    
    return {
      leaseId,
      workHash,
      txHash: receipt.hash,
      completedAt: new Date().toISOString()
    };
  }
}

// 使用示例
async function main() {
  const sdk = new AkashRenderSDK(
    'https://akash-rpc.mainnet.com',
    '0xAkashRenderContract'
  );
  
  const provider = new ethers.JsonRpcProvider('https://akash-rpc.mainnet.com');
  const signer = new ethers.Wallet('0xPrivateKey', provider);
  
  // 搜索提供者
  console.log('搜索可用算力提供者...');
  const providers = await sdk.searchProviders({
    minGpuMemory: 8192,
    maxPrice: 3.0,
    minReputation: 300
  });
  
  console.log(`找到 ${providers.length} 个提供者`);
  console.log('最优提供者:', providers[0]);
  
  // 部署渲染任务
  console.log('\n部署渲染任务...');
  const job = await sdk.deployRenderJob(
    {
      sceneCID: 'QmSceneFileCID',
      frameCount: 2400,
      resolution: { width: 3840, height: 2160 },
      renderEngine: 'blender',
      priority: 'high'
    },
    providers[0],
    signer
  );
  
  console.log(`租约ID: ${job.leaseId}`);
  
  // 监控进度
  console.log('\n监控渲染进度...');
  const progress = await sdk.monitorJob(job.leaseId);
  
  // 验证结果
  console.log('\n验证渲染结果...');
  const verification = await sdk.verifyRenderResult(
    job.leaseId,
    '0xExpectedHash'
  );
  console.log(`验证结果: ${verification.verified ? '✓ 通过' : '✗ 失败'}`);
  
  // 完成租约
  console.log('\n完成租约...');
  const result = await sdk.completeLease(
    job.leaseId,
    verification.actualHash,
    signer
  );
  console.log(`完成: ${result.txHash}`);
}

main().catch(console.error);