Performance Optimization

Performance Optimization

Overview

INTUE's performance optimization framework enables maximum computational efficiency, reduced latency, and optimal resource utilization. These optimization techniques ensure high-throughput signal processing and fast trade execution across distributed systems.

Latency Reduction Techniques

Signal Propagation Optimization

// Optimize signal propagation across microservices
function optimizeSignalPath(signal, destination) {
  // Map signal chain services
  const signalChain = buildSignalServiceChain(signal, destination);
  
  // Identify critical path
  const criticalPath = analyzeCriticalPath(signalChain);
  
  // Optimize signal transmission
  const optimizedChain = criticalPath.map(serviceNode => {
    if (serviceNode.isHighLatency) {
      // Apply specialized optimizations for high-latency nodes
      return optimizeHighLatencyNode(serviceNode);
    }
    return serviceNode;
  });
  
  // Create optimized signal envelope
  return {
    payload: signal,
    routingMetadata: {
      critical: true,
      priorityLevel: determinePriorityLevel(signal),
      preferredRoute: optimizedChain.map(node => node.id),
      latencyBudget: calculateLatencyBudget(signal)
    },
    compression: shouldCompressSignal(signal) ? 'enabled' : 'disabled',
    batching: shouldBatchSignal(signal) ? 'enabled' : 'disabled'
  };
}

// Determine if signal should use compression
function shouldCompressSignal(signal) {
  // Use compression for large payloads or non-critical paths
  return signal.data.size > 10000 || !signal.metadata.timeCritical;
}

// Determine if signal should be batched
function shouldBatchSignal(signal) {
  // Only batch non-urgent signals
  return !signal.metadata.urgent && signal.batchCompatible;
}

// Calculate latency budget for signal
function calculateLatencyBudget(signal) {
  if (signal.metadata.urgent) {
    return 50;  // 50ms for urgent signals
  } else if (signal.metadata.timeCritical) {
    return 200;  // 200ms for time-critical signals
  } else {
    return 1000;  // 1000ms for regular signals
  }
}

Execution Path Optimization

// Optimize trade execution path
async function optimizeExecutionPath(trade, exchangeAdapter) {
  // Capture execution start time
  const startTime = performance.now();
  
  // Generate execution plan
  const executionPlan = await planExecution(trade, exchangeAdapter);
  
  // Parallelize pre-execution validations
  const [
    balanceCheck,
    marketConditionCheck,
    riskCheck
  ] = await Promise.all([
    checkSufficientBalance(trade),
    checkMarketConditions(trade),
    performRiskValidation(trade)
  ]);
  
  // Validate all pre-execution checks
  const validationResult = validatePreExecutionChecks([
    balanceCheck,
    marketConditionCheck,
    riskCheck
  ]);
  
  if (!validationResult.valid) {
    return {
      success: false,
      reason: validationResult.reason,
      latency: performance.now() - startTime
    };
  }
  
  // Select optimal execution strategy based on order type and market conditions
  const executionStrategy = selectExecutionStrategy(
    trade,
    executionPlan.marketConditions
  );
  
  // Execute trade with optimized settings
  const result = await executeWithStrategy(
    trade,
    exchangeAdapter,
    executionStrategy
  );
  
  // Calculate total execution latency
  result.latency = performance.now() - startTime;
  
  // Log latency metrics
  logLatencyMetrics('trade_execution', result.latency, {
    asset: trade.asset,
    orderType: trade.type,
    strategy: executionStrategy.name
  });
  
  return result;
}

// Select optimal execution strategy
function selectExecutionStrategy(trade, marketConditions) {
  const strategies = {
    // Standard market order
    standard: {
      name: 'standard',
      maxSlippage: 0.001,  // 0.1%
      urgency: 'normal'
    },
    
    // Aggressive market order for urgent execution
    aggressive: {
      name: 'aggressive',
      maxSlippage: 0.003,  // 0.3%
      urgency: 'high'
    },
    
    // Smart order routing for optimal execution
    smart: {
      name: 'smart',
      maxSlippage: 0.001,  // 0.1%
      urgency: 'normal',
      dynamicRouting: true
    },
    
    // TWAP for large orders
    twap: {
      name: 'twap',
      maxSlippage: 0.001,  // 0.1%
      urgency: 'low',
      timeWindow: 10 * 60 * 1000,  // 10 minutes
      intervals: 5
    }
  };
  
  // Select strategy based on order size and market conditions
  if (isLargeOrder(trade)) {
    return strategies.twap;
  } else if (marketConditions.volatility > 0.05) {
    return strategies.aggressive;
  } else if (marketConditions.liquidity > 0.8) {
    return strategies.standard;
  } else {
    return strategies.smart;
  }
}

Computing Resource Management

Adaptive Resource Allocation

// Adaptive resource allocation for compute-intensive tasks
class AdaptiveResourceManager {
  constructor(config) {
    this.maxWorkers = config.maxWorkers || 8;
    this.minWorkers = config.minWorkers || 1;
    this.currentWorkers = this.minWorkers;
    this.taskQueue = [];
    this.workers = [];
    this.metrics = {
      taskLatencies: [],
      resourceUtilization: [],
      queueLength: []
    };
    
    // Initialize worker pool
    this.initializeWorkers(this.currentWorkers);
    
    // Start monitoring
    this.startMonitoring();
  }
  
  // Initialize worker pool
  initializeWorkers(count) {
    // Ensure we don't exceed max workers
    const targetCount = Math.min(count, this.maxWorkers);
    
    // Add new workers if needed
    while (this.workers.length < targetCount) {
      const worker = new ComputeWorker();
      this.workers.push(worker);
    }
    
    // Remove workers if we have too many
    while (this.workers.length > targetCount) {
      const worker = this.workers.pop();
      worker.terminate();
    }
    
    this.currentWorkers = this.workers.length;
    console.log(`Worker pool adjusted to ${this.currentWorkers} workers`);
  }
  
  // Submit task to the pool
  async submitTask(task) {
    return new Promise((resolve, reject) => {
      const wrappedTask = {
        ...task,
        startTime: Date.now(),
        resolve,
        reject
      };
      
      this.taskQueue.push(wrappedTask);
      this.processQueue();
    });
  }
  
  // Process tasks in the queue
  processQueue() {
    // Find idle workers
    const idleWorkers = this.workers.filter(worker => !worker.busy);
    
    // Assign tasks to idle workers
    while (idleWorkers.length > 0 && this.taskQueue.length > 0) {
      const worker = idleWorkers.shift();
      const task = this.taskQueue.shift();
      
      worker.busy = true;
      
      worker.execute(task).then(result => {
        // Record metrics
        const latency = Date.now() - task.startTime;
        this.metrics.taskLatencies.push(latency);
        
        // Resolve the task promise
        task.resolve(result);
        
        // Mark worker as idle
        worker.busy = false;
        
        // Continue processing queue
        this.processQueue();
      }).catch(error => {
        task.reject(error);
        worker.busy = false;
        this.processQueue();
      });
    }
    
    // Check if we need to adjust the worker pool
    this.adjustWorkerPool();
  }
  
  // Adjust worker pool based on load
  adjustWorkerPool() {
    const queueLength = this.taskQueue.length;
    const activeWorkers = this.workers.filter(worker => worker.busy).length;
    const utilization = activeWorkers / this.currentWorkers;
    
    // Record metrics
    this.metrics.resourceUtilization.push(utilization);
    this.metrics.queueLength.push(queueLength);
    
    // Keep metrics arrays bounded
    if (this.metrics.taskLatencies.length > 100) {
      this.metrics.taskLatencies.shift();
    }
    if (this.metrics.resourceUtilization.length > 100) {
      this.metrics.resourceUtilization.shift();
    }
    if (this.metrics.queueLength.length > 100) {
      this.metrics.queueLength.shift();
    }
    
    // Calculate average utilization
    const avgUtilization = this.metrics.resourceUtilization
      .slice(-10)
      .reduce((sum, val) => sum + val, 0) / 10;
    
    // Adjust worker count based on utilization and queue length
    if (avgUtilization > 0.8 && queueLength > 0) {
      // High utilization and tasks waiting, add workers
      const newWorkerCount = Math.min(
        this.currentWorkers + 1,
        this.maxWorkers
      );
      if (newWorkerCount > this.currentWorkers) {
        this.initializeWorkers(newWorkerCount);
      }
    } else if (avgUtilization < 0.3 && queueLength === 0) {
      // Low utilization and no waiting tasks, remove workers
      const newWorkerCount = Math.max(
        this.currentWorkers - 1,
        this.minWorkers
      );
      if (newWorkerCount < this.currentWorkers) {
        this.initializeWorkers(newWorkerCount);
      }
    }
  }
  
  // Start monitoring resource usage
  startMonitoring() {
    setInterval(() => {
      const metrics = this.getMetrics();
      
      // Log resource usage
      console.log(`Resource utilization: ${metrics.utilization.toFixed(2)}`);
      console.log(`Average task latency: ${metrics.avgLatency.toFixed(2)}ms`);
      console.log(`Queue length: ${metrics.queueLength}`);
      console.log(`Active workers: ${metrics.activeWorkers}/${this.currentWorkers}`);
    }, 30000); // Every 30 seconds
  }
  
  // Get current metrics
  getMetrics() {
    const activeWorkers = this.workers.filter(worker => worker.busy).length;
    
    return {
      utilization: activeWorkers / this.currentWorkers,
      avgLatency: this.metrics.taskLatencies.length > 0 ?
        this.metrics.taskLatencies.reduce((sum, val) => sum + val, 0) / 
        this.metrics.taskLatencies.length : 0,
      queueLength: this.taskQueue.length,
      activeWorkers
    };
  }
}

// Example usage
const resourceManager = new AdaptiveResourceManager({
  maxWorkers: 16,
  minWorkers: 2
});

// Submit compute-intensive tasks
async function processSignalAnalysis(marketData) {
  return resourceManager.submitTask({
    type: 'signal_analysis',
    data: marketData,
    priority: 'high'
  });
}

async function performBacktest(strategy, parameters) {
  return resourceManager.submitTask({
    type: 'backtest',
    data: { strategy, parameters },
    priority: 'medium'
  });
}

Memory Optimization

// Memory optimization for large datasets
class OptimizedDataStore {
  constructor(config) {
    this.maxCacheSize = config.maxCacheSize || 500 * 1024 * 1024; // 500MB
    this.currentCacheSize = 0;
    this.cache = new Map();
    this.accessCounts = new Map();
    this.lastAccessed = new Map();
    this.persistence = new PersistenceLayer(config.persistencePath);
  }
  
  // Store data with intelligent memory management
  async store(key, data) {
    // Calculate data size
    const dataSize = this._calculateSize(data);
    
    // Check if we need to evict items from cache
    if (this.currentCacheSize + dataSize > this.maxCacheSize) {
      await this._evictItems(dataSize);
    }
    
    // Store data in cache
    this.cache.set(key, data);
    this.accessCounts.set(key, 0);
    this.lastAccessed.set(key, Date.now());
    this.currentCacheSize += dataSize;
    
    // Also persist to storage
    await this.persistence.write(key, data);
    
    return {
      key,
      size: dataSize,
      cached: true
    };
  }
  
  // Retrieve data with access tracking
  async retrieve(key) {
    // Check if in memory cache
    if (this.cache.has(key)) {
      // Update access metrics
      this.accessCounts.set(key, (this.accessCounts.get(key) || 0) + 1);
      this.lastAccessed.set(key, Date.now());
      
      return this.cache.get(key);
    }
    
    // Not in cache, try to load from persistence
    try {
      const data = await this.persistence.read(key);
      
      // If data exists and we have space, add to cache
      if (data) {
        const dataSize = this._calculateSize(data);
        
        if (this.currentCacheSize + dataSize <= this.maxCacheSize) {
          this.cache.set(key, data);
          this.accessCounts.set(key, 1);
          this.lastAccessed.set(key, Date.now());
          this.currentCacheSize += dataSize;
        }
        
        return data;
      }
    } catch (error) {
      console.error(`Error retrieving data for ${key}:`, error);
    }
    
    return null;
  }
  
  // Calculate approximate size of data in bytes
  _calculateSize(data) {
    if (typeof data === 'string') {
      return data.length * 2; // UTF-16 characters
    } else if (data instanceof ArrayBuffer) {
      return data.byteLength;
    } else if (Array.isArray(data)) {
      return data.reduce((size, item) => size + this._calculateSize(item), 0);
    } else if (typeof data === 'object' && data !== null) {
      return Object.entries(data).reduce(
        (size, [key, value]) => 
          size + (key.length * 2) + this._calculateSize(value),
        0
      );
    } else {
      return 8; // Default size for numbers, booleans, etc.
    }
  }
  
  // Evict items to make room for new data
  async _evictItems(requiredSpace) {
    // If nothing to evict or more space needed than total cache, clear all
    if (this.cache.size === 0 || requiredSpace > this.maxCacheSize) {
      this.cache.clear();
      this.accessCounts.clear();
      this.lastAccessed.clear();
      this.currentCacheSize = 0;
      return;
    }
    
    // Calculate score for each item (combination of access frequency and recency)
    const scores = new Map();
    
    for (const key of this.cache.keys()) {
      const accessCount = this.accessCounts.get(key) || 0;
      const lastAccess = this.lastAccessed.get(key) || 0;
      const age = (Date.now() - lastAccess) / (1000 * 60); // Age in minutes
      
      // Score is higher for frequently and recently accessed items
      const score = (accessCount + 1) / (age + 1);
      scores.set(key, score);
    }
    
    // Sort items by score (ascending, so lowest scores first)
    const sortedItems = [...scores.entries()]
      .sort((a, b) => a[1] - b[1])
      .map(([key]) => key);
    
    // Evict items until we have enough space
    let freedSpace = 0;
    
    for (const key of sortedItems) {
      const data = this.cache.get(key);
      const dataSize = this._calculateSize(data);
      
      // Remove from cache
      this.cache.delete(key);
      this.accessCounts.delete(key);
      this.lastAccessed.delete(key);
      this.currentCacheSize -= dataSize;
      freedSpace += dataSize;
      
      // Check if we've freed enough space
      if (freedSpace >= requiredSpace) {
        break;
      }
    }
  }
  
  // Get cache statistics
  getStats() {
    return {
      itemCount: this.cache.size,
      currentCacheSize: this.currentCacheSize,
      maxCacheSize: this.maxCacheSize,
      utilization: this.currentCacheSize / this.maxCacheSize,
      persistedItems: this.persistence.getItemCount()
    };
  }
}

// Example usage
const dataStore = new OptimizedDataStore({
  maxCacheSize: 1024 * 1024 * 1024, // 1GB
  persistencePath: './data/cache'
});

// Store market data efficiently
async function storeMarketData(asset, timeframe, data) {
  const key = `market_data_${asset}_${timeframe}_${data.timestamp}`;
  return dataStore.store(key, data);
}

// Retrieve market data efficiently
async function getMarketData(asset, timeframe, timestamp) {
  const key = `market_data_${asset}_${timeframe}_${timestamp}`;
  return dataStore.retrieve(key);
}

Parallel Processing Strategies

Multi-threaded Analysis

// Multi-threaded market analysis
class ParallelAnalysisEngine {
  constructor(config) {
    this.workerCount = config.workerCount || Math.max(2, navigator.hardwareConcurrency - 1);
    this.workers = [];
    this.taskQueue = [];
    
    // Initialize worker threads
    this._initializeWorkers();
  }
  
  // Initialize worker threads
  _initializeWorkers() {
    for (let i = 0; i < this.workerCount; i++) {
      const worker = new Worker('./analysis-worker.js');
      
      worker.onmessage = (event) => {
        const { taskId, result, error } = event.data;
        
        // Find task in queue
        const taskIndex = this.taskQueue.findIndex(task => task.id === taskId);
        
        if (taskIndex !== -1) {
          const task = this.taskQueue[taskIndex];
          
          // Remove task from queue
          this.taskQueue.splice(taskIndex, 1);
          
          // Resolve or reject task promise
          if (error) {
            task.reject(new Error(error));
          } else {
            task.resolve(result);
          }
        }
        
        // Process next task if available
        this._processNextTask(worker);
      };
      
      worker.onerror = (error) => {
        console.error('Worker error:', error);
      };
      
      // Add to worker pool
      this.workers.push({
        worker,
        busy: false
      });
    }
  }
  
  // Process next task from queue
  _processNextTask(worker) {
    // Find an idle worker and available task
    const workerInfo = this.workers.find(w => w.worker === worker);
    
    if (!workerInfo || this.taskQueue.length === 0) {
      return;
    }
    
    // Find tasks that aren't in progress
    const pendingTasks = this.taskQueue.filter(task => !task.inProgress);
    
    if (pendingTasks.length === 0) {
      return;
    }
    
    // Get next task
    const task = pendingTasks[0];
    task.inProgress = true;
    workerInfo.busy = true;
    
    // Send task to worker
    worker.postMessage({
      taskId: task.id,
      type: task.type,
      payload: task.payload
    });
  }
  
  // Submit analysis task
  async analyzeData(type, payload) {
    return new Promise((resolve, reject) => {
      const taskId = `task${Date.now()}_${Math.random().toString(36).substr(2, 9)}`;
      
      // Add task to queue
      this.taskQueue.push({
        id: taskId,
        type,
        payload,
        inProgress: false,
        resolve,
        reject
      });
      
      // Find an idle worker
      const idleWorker = this.workers.find(w => !w.busy);
      
      if (idleWorker) {
        this._processNextTask(idleWorker.worker);
      }
    });
  }
  
  // Perform technical analysis in parallel
  async analyzeTechnicalIndicators(asset, data, indicators) {
    return this.analyzeData('technical', {
      asset,
      data,
      indicators
    });
  }
  
  // Analyze multiple assets in parallel
  async analyzeMultipleAssets(assets, timeframe) {
    // Create analysis tasks for each asset
    const analysisPromises = assets.map(asset => 
      this.analyzeData('asset_analysis', {
        asset,
        timeframe
      })
    );
    
    // Wait for all analyses to complete
    return Promise.all(analysisPromises);
  }
  
  // Shutdown worker threads
  shutdown() {
    this.workers.forEach(workerInfo => {
      workerInfo.worker.terminate();
    });
    
    this.workers = [];
    console.log('Analysis engine workers terminated');
  }
}

// Example usage
const analysisEngine = new ParallelAnalysisEngine({
  workerCount: 8
});

// Analyze multiple assets in parallel
async function analyzeMarket() {
  const assets = ['BTC', 'ETH', 'SOL', 'AVAX', 'MATIC', 'LINK', 'UNI', 'AAVE'];
  
  console.time('marketAnalysis');
  const results = await analysisEngine.analyzeMultipleAssets(assets, '1h');
  console.timeEnd('marketAnalysis');
  
  return results;
}

Distributed Processing

// Distributed processing manager
class DistributedProcessingManager {
  constructor(config) {
    this.nodeRegistry = new Map();
    this.serviceDiscovery = new ServiceDiscovery(config.discoveryEndpoint);
    this.taskDistributor = new TaskDistributor();
    this.resultCollector = new ResultCollector();
    
    // Initialize system
    this._initialize();
  }
  
  // Initialize distributed processing
  async _initialize() {
    // Discover available processing nodes
    const nodes = await this.serviceDiscovery.discoverNodes();
    
    for (const node of nodes) {
      this.registerNode(node);
    }
    
    // Set up service discovery events
    this.serviceDiscovery.on('nodeAdded', node => {
      this.registerNode(node);
    });
    
    this.serviceDiscovery.on('nodeRemoved', nodeId => {
      this.unregisterNode(nodeId);
    });
    
    console.log(`Distributed processing initialized with ${this.nodeRegistry.size} nodes`);
  }
  
  // Register processing node
  registerNode(node) {
    this.nodeRegistry.set(node.id, {
      ...node,
      status: 'available',
      capabilities: node.capabilities || [],
      performance: node.performance || {
         cpu: 1,
         memory: 1,
         network: 1
       },
      lastHeartbeat: Date.now()
    });
    
    console.log(`Node registered: ${node.id} (${node.hostname})`);
  }
  
  // Unregister processing node
  unregisterNode(nodeId) {
    this.nodeRegistry.delete(nodeId);
    console.log(`Node unregistered: ${nodeId}`);
  }
  
  // Find suitable nodes for task
  _findSuitableNodes(task, count = 1) {
    const candidates = [];
    
    for (const [nodeId, node] of this.nodeRegistry.entries()) {
      // Skip unavailable nodes
      if (node.status !== 'available') {
        continue;
      }
      
      // Check if node has required capabilities
      if (task.requiredCapabilities) {
        const hasCapabilities = task.requiredCapabilities.every(
          cap => node.capabilities.includes(cap)
        );
        
        if (!hasCapabilities) {
          continue;
        }
      }
      
      // Calculate node score based on performance metrics and load
      const score = this._calculateNodeScore(node, task);
      
      candidates.push({
        nodeId,
        node,
        score
      });
    }
    
    // Sort by score (descending)
    candidates.sort((a, b) => b.score - a.score);
    
    // Return the top N candidates
    return candidates.slice(0, count).map(c => c.nodeId);
  }
  
  // Calculate node score for task assignment
  _calculateNodeScore(node, task) {
    // Base score from performance metrics
    let score = (
      node.performance.cpu * 0.4 +
      node.performance.memory * 0.3 +
      node.performance.network * 0.3
    );
    
    // Adjust for task type if node has specialty
    if (task.type && node.specialties && node.specialties.includes(task.type)) {
      score *= 1.5;
    }
    
    // Adjust for current load
    if (node.currentLoad) {
      score *= (1 - (node.currentLoad / 100));
    }
    
    return score;
  }
  
  // Distribute task to processing nodes
  async distributeTask(task) {
    // For tasks that can be parallelized
    if (task.parallelizable) {
      return this._distributeParallelTask(task);
    }
    
    // For single-node tasks
    return this._distributeSingleNodeTask(task);
  }
  
  // Distribute task to a single node
  async _distributeSingleNodeTask(task) {
    const nodeIds = this._findSuitableNodes(task, 1);
    
    if (nodeIds.length === 0) {
      throw new Error('No suitable nodes available for task');
    }
    
    const nodeId = nodeIds[0];
    const node = this.nodeRegistry.get(nodeId);
    
    // Update node status
    node.status = 'busy';
    
    try {
      // Send task to node
      const result = await this.taskDistributor.sendTask(nodeId, task);
      
      // Update node status
      node.status = 'available';
      node.lastTask = {
        id: task.id,
        type: task.type,
        completedAt: Date.now()
      };
      
      return result;
    } catch (error) {
      // Handle node failure
      console.error(`Node ${nodeId} failed executing task ${task.id}:`, error);
      
      // Mark node as potentially problematic
      node.status = 'error';
      node.lastError = {
        task: task.id,
        error: error.message,
        time: Date.now()
      };
      
      // Retry on another node
      return this._distributeSingleNodeTask(task);
    }
  }
  
  // Distribute task to multiple nodes in parallel
  async _distributeParallelTask(task) {
    // Determine number of nodes to use
    const nodeCount = Math.min(
      task.optimalParallelism || 3,
      this.nodeRegistry.size
    );
    
    const nodeIds = this._findSuitableNodes(task, nodeCount);
    
    if (nodeIds.length === 0) {
      throw new Error('No suitable nodes available for parallel task');
    }
    
    // Split task into sub-tasks
    const subTasks = this._splitTask(task, nodeIds.length);
    
    // Distribute sub-tasks to nodes
    const subTaskPromises = subTasks.map((subTask, index) => {
      const nodeId = nodeIds[index];
      const node = this.nodeRegistry.get(nodeId);
      
      // Update node status
      node.status = 'busy';
      
      return this.taskDistributor.sendTask(nodeId, subTask)
        .then(result => {
          // Update node status
          node.status = 'available';
          node.lastTask = {
            id: subTask.id,
            type: subTask.type,
            completedAt: Date.now()
          };
          
          return result;
        })
        .catch(error => {
          // Handle node failure
          console.error(`Node ${nodeId} failed executing sub-task ${subTask.id}:`, error);
          
          // Mark node as potentially problematic
          node.status = 'error';
          node.lastError = {
            task: subTask.id,
            error: error.message,
            time: Date.now()
          };
          
          throw error;
        });
    });
    
    // Wait for all sub-tasks to complete or implement partial failure handling
    try {
      const subResults = await Promise.all(subTaskPromises);
      
      // Combine sub-results
      return this._combineResults(task, subResults);
    } catch (error) {
      // Handle partial failures by redistributing failed sub-tasks
      // This is a simplified implementation
      console.error('Partial failure in distributed task:', error);
      throw new Error('Distributed task execution failed');
    }
  }
  
  // Split task into sub-tasks for parallel processing
  _splitTask(task, count) {
    // This would be implemented based on the specific task type
    // Here's a generic implementation for demonstration
    
    const subTasks = [];
    
    for (let i = 0; i < count; i++) {
      subTasks.push({
        id: `${task.id}_part${i}`,
        type: task.type,
        parentTask: task.id,
        partIndex: i,
        partCount: count,
        payload: {
          ...task.payload,
          partitionKey: i,
          partitionCount: count
        }
      });
    }
    
    return subTasks;
  }
  
  // Combine results from sub-tasks
  _combineResults(originalTask, subResults) {
    // This would be implemented based on the specific task type
    // Here's a generic implementation for demonstration
    
    if (originalTask.type === 'marketAnalysis') {
      // For market analysis, combine asset results
      const combinedResults = {
        assets: {},
        timestamp: Date.now(),
        analysisTime: 0
      };
      
      // Combine all asset results
      for (const result of subResults) {
        // Combine asset data
        Object.assign(combinedResults.assets, result.assets);
        
        // Track longest analysis time
        combinedResults.analysisTime = Math.max(
          combinedResults.analysisTime,
          result.analysisTime || 0
        );
      }
      
      return combinedResults;
    } else if (originalTask.type === 'backtest') {
      // For backtests, combine performance metrics
      return {
        results: subResults.map(r => r.results).flat(),
        performance: {
          totalTrades: subResults.reduce((sum, r) => sum + r.performance.trades, 0),
          winRate: subResults.reduce((sum, r) => sum + r.performance.winRate, 0) / subResults.length,
          profitLoss: subResults.reduce((sum, r) => sum + r.performance.profitLoss, 0),
          maxDrawdown: Math.max(...subResults.map(r => r.performance.maxDrawdown))
        }
      };
    } else {
      // Generic combination
      return {
        combinedResult: subResults,
        count: subResults.length
      };
    }
  }
}

// Example usage
const distributedManager = new DistributedProcessingManager({
  discoveryEndpoint: 'https://discovery.intue.io'
});

// Perform distributed market analysis
async function performDistributedAnalysis() {
  const task = {
    id: `analysis_${Date.now()}`,
    type: 'marketAnalysis',
    parallelizable: true,
    optimalParallelism: 5,
    requiredCapabilities: ['market-data-processing'],
    payload: {
      assets: ['BTC', 'ETH', 'SOL', 'AVAX', 'DOT', 'LINK', 'UNI', 'AAVE', 'MKR', 'SNX'],
      timeframes: ['1h', '4h', '1d'],
      indicators: ['rsi', 'macd', 'bollinger', 'volume_profile']
    }
  };
  
  console.time('distributedAnalysis');
  const result = await distributedManager.distributeTask(task);
  console.timeEnd('distributedAnalysis');
  
  return result;
}

Database Optimization

// Optimize database queries for time series data
class TimeSeriesOptimizer {
  constructor(dbClient) {
    this.db = dbClient;
    this.cacheManager = new CacheManager({
      maxSize: 1000,
      ttl: 5 * 60 * 1000  // 5 minutes
    });
    this.queryStats = {
      total: 0,
      cached: 0,
      dbQueries: 0
    };
  }
  
  // Optimized query for time series data
  async queryTimeSeries({
    asset,
    metric,
    timeframe,
    startTime,
    endTime,
    aggregation = 'none'
  }) {
    this.queryStats.total++;
    
    // Generate cache key
    const cacheKey = this._generateCacheKey({
      asset,
      metric,
      timeframe,
      startTime,
      endTime,
      aggregation
    });
    
    // Check cache first
    const cachedResult = this.cacheManager.get(cacheKey);
    if (cachedResult) {
      this.queryStats.cached++;
      return cachedResult;
    }
    
    this.queryStats.dbQueries++;
    
    // Determine optimal query strategy
    const queryStrategy = this._determineQueryStrategy({
      timeframe,
      startTime,
      endTime
    });
    
    // Execute query with appropriate strategy
    let result;
    switch (queryStrategy) {
      case 'directQuery':
        result = await this._executeDirectQuery({
          asset,
          metric,
          timeframe,
          startTime,
          endTime,
          aggregation
        });
        break;
      case 'aggregationPipeline':
        result = await this._executeAggregationPipeline({
          asset,
          metric,
          timeframe,
          startTime,
          endTime,
          aggregation
        });
        break;
      case 'downsampledQuery':
        result = await this._executeDownsampledQuery({
          asset,
          metric,
          timeframe,
          startTime,
          endTime,
          aggregation
        });
        break;
      default:
        throw new Error(`Unknown query strategy: ${queryStrategy}`);
    }
    
    // Cache the result
    this.cacheManager.set(cacheKey, result);
    return result;
  }
  
  // Generate cache key
  _generateCacheKey(params) {
    return `${params.asset}_${params.metric}_${params.timeframe}_${params.startTime}_${params.endTime}_${params.aggregation}`;
  }
  
  // Determine optimal query strategy
  _determineQueryStrategy({
    timeframe,
    startTime,
    endTime
  }) {
    // Calculate time range in milliseconds
    const rangeMs = endTime - startTime;
    
    // Convert timeframe to milliseconds
    const timeframeMs = this._timeframeToMs(timeframe);
    
    // Calculate number of data points
    const dataPoints = rangeMs / timeframeMs;
    
    if (dataPoints <= 1000) {
      // For small queries, direct query is fastest
      return 'directQuery';
    } else if (dataPoints <= 10000) {
      // For medium queries, use aggregation pipeline
      return 'aggregationPipeline';
    } else {
      // For large queries, use downsampled data
      return 'downsampledQuery';
    }
  }
  
  // Convert timeframe string to milliseconds
  _timeframeToMs(timeframe) {
    const unit = timeframe.slice(-1);
    const value = parseInt(timeframe.slice(0, -1));
    
    switch (unit) {
      case 'm':
        return value * 60 * 1000;
      case 'h':
        return value * 60 * 60 * 1000;
      case 'd':
        return value * 24 * 60 * 60 * 1000;
      case 'w':
        return value * 7 * 24 * 60 * 60 * 1000;
      default:
        throw new Error(`Unknown timeframe unit: ${unit}`);
    }
  }
  
  // Execute direct database query
  async _executeDirectQuery({
    asset,
    metric,
    timeframe,
    startTime,
    endTime,
    aggregation
  }) {
    // Direct query implementation for small datasets
    const collection = this.db.collection(`${asset}_${timeframe}`);
    
    const query = {
      timestamp: {
        $gte: startTime,
        $lte: endTime
      }
    };
    
    const projection = {
      _id: 0,
      timestamp: 1
    };
    
    // Add requested metric to projection
    projection[metric] = 1;
    
    // Execute query
    const results = await collection.find(query).project(projection).sort({ timestamp: 1 }).toArray();
    
    // Apply any additional aggregation if needed
    if (aggregation !== 'none') {
      return this._applyAggregation(results, metric, aggregation);
    }
    
    return results;
  }
  
  // Execute aggregation pipeline for medium-sized queries
  async _executeAggregationPipeline({
    asset,
    metric,
    timeframe,
    startTime,
    endTime,
    aggregation
  }) {
    const collection = this.db.collection(`${asset}_${timeframe}`);
    
    // Build aggregation pipeline
    const pipeline = [
      {
        $match: {
          timestamp: {
            $gte: startTime,
            $lte: endTime
          }
        }
      },
      {
        $sort: {
          timestamp: 1
        }
      },
      {
        $project: {
          _id: 0,
          timestamp: 1,
          [metric]: 1
        }
      }
    ];
    
    // Add aggregation stage if needed
    if (aggregation !== 'none') {
      pipeline.push(this._getAggregationStage(metric, aggregation));
    }
    
    // Execute aggregation pipeline
    return collection.aggregate(pipeline).toArray();
  }
  
  // Execute query against downsampled data for large queries
  async _executeDownsampledQuery({
    asset,
    metric,
    timeframe,
    startTime,
    endTime,
    aggregation
  }) {
    // Determine appropriate downsampled collection
    const downsampledTimeframe = this._getDownsampledTimeframe(timeframe);
    const collection = this.db.collection(`${asset}_${downsampledTimeframe}_downsampled`);
    
    // Build query
    const query = {
      timestamp: {
        $gte: startTime,
        $lte: endTime
      }
    };
    
    // Execute query
    const results = await collection.find(query).sort({ timestamp: 1 }).toArray();
    
    // Apply any additional processing
    return this._processDownsampledResults(results, metric, aggregation);
  }
  
  // Get appropriate downsampled timeframe
  _getDownsampledTimeframe(timeframe) {
    // Logic to determine appropriate downsampled timeframe
    const unit = timeframe.slice(-1);
    const value = parseInt(timeframe.slice(0, -1));
    
    if (unit === 'm' && value < 60) {
      return '1h';
    } else if (unit === 'h' && value < 24) {
      return '1d';
    } else {
      return '1w';
    }
  }
  
  // Apply aggregation to results
  _applyAggregation(results, metric, aggregation) {
    // Implementation of client-side aggregation
    switch (aggregation) {
      case 'avg':
        return this._calculateAverage(results, metric);
      case 'max':
        return this._calculateMax(results, metric);
      case 'min':
        return this._calculateMin(results, metric);
      case 'sum':
        return this._calculateSum(results, metric);
      default:
        return results;
    }
  }
  
  // Get aggregation stage for pipeline
  _getAggregationStage(metric, aggregation) {
    // Return appropriate aggregation stage
    switch (aggregation) {
      case 'avg':
        return {
          $group: {
            _id: null,
            result: { $avg: `$${metric}` },
            timestamp: { $first: '$timestamp' }
          }
        };
      case 'max':
        return {
          $group: {
            _id: null,
            result: { $max: `$${metric}` },
            timestamp: { $first: '$timestamp' }
          }
        };
      case 'min':
        return {
          $group: {
            _id: null,
            result: { $min: `$${metric}` },
            timestamp: { $first: '$timestamp' }
          }
        };
      case 'sum':
        return {
          $group: {
            _id: null,
            result: { $sum: `$${metric}` },
            timestamp: { $first: '$timestamp' }
          }
        };
      default:
        return {};
    }
  }
  
  // Process downsampled results
  _processDownsampledResults(results, metric, aggregation) {
    // Process downsampled data and apply aggregation if needed
    if (aggregation !== 'none') {
      return this._applyAggregation(results, metric, aggregation);
    }
    
    return results;
  }
  
  // Get query statistics
  getQueryStats() {
    return {
      ...this.queryStats,
      cacheHitRate: this.queryStats.total > 0 
        ? (this.queryStats.cached / this.queryStats.total) * 100 
        : 0
    };
  }
}

// Example usage
const timeSeriesOptimizer = new TimeSeriesOptimizer(dbClient);

// Query time series data efficiently
async function queryMarketData(asset, metric, timeframe, startDate, endDate) {
  return timeSeriesOptimizer.queryTimeSeries({
    asset,
    metric,
    timeframe,
    startTime: startDate.getTime(),
    endTime: endDate.getTime(),
    aggregation: 'none'
  });
}