@clduab11/gemini-flow/src/protocols/a2a/tools/performance-optimization-layer.ts

Revolutionary AI agent swarm coordination platform with Google Services integration, multimedia processing, and production-ready monitoring. Features 8 Google AI services, quantum computing capabilities, and enterprise-grade security.

/**
 * Performance Optimization Layer
 *
 * Provides intelligent performance optimization for A2A tool invocations.
 * Includes predictive optimization, adaptive resource allocation, and
 * machine learning-based performance tuning.
 */

import { EventEmitter } from "events";
import { Logger } from "../../../utils/logger.js";
import { CacheManager } from "../../../core/cache-manager.js";
import { PerformanceMonitor } from "../../../monitoring/performance-monitor.js";
import {
  A2AToolInvocation,
  A2AToolResponse,
  A2AToolContext,
} from "./a2a-tool-wrapper.js";
import { MCPToolRegistry } from "./mcp-a2a-tool-registry.js";

export interface PerformanceProfile {
  toolId: string;
  averageLatency: number;
  p95Latency: number;
  p99Latency: number;
  successRate: number;
  errorRate: number;
  throughput: number;
  resourceUtilization: {
    cpu: number;
    memory: number;
    network: number;
    io: number;
  };
  contextMetrics: {
    trustLevelPerformance: Record<string, number>;
    parameterSizeImpact: number;
    timeOfDayVariance: number;
    loadFactorImpact: number;
  };
  lastUpdated: Date;
}

export interface OptimizationStrategy {
  id: string;
  name: string;
  description: string;
  conditions: OptimizationCondition[];
  actions: OptimizationAction[];
  priority: number;
  successRate: number;
  averageImprovement: number;
  enabled: boolean;
}

export interface OptimizationCondition {
  type:
    | "latency"
    | "error_rate"
    | "throughput"
    | "resource_usage"
    | "context"
    | "custom";
  operator: "gt" | "lt" | "eq" | "gte" | "lte" | "contains" | "matches";
  value: any;
  threshold?: number;
  customCheck?: (
    profile: PerformanceProfile,
    context: A2AToolContext,
  ) => boolean;
}

export interface OptimizationAction {
  type:
    | "cache"
    | "parallel"
    | "retry"
    | "circuit_breaker"
    | "load_balance"
    | "precompute"
    | "batch"
    | "custom";
  parameters: Record<string, any>;
  execute: (
    invocation: A2AToolInvocation,
    context: OptimizationContext,
  ) => Promise<OptimizationResult>;
}

export interface OptimizationContext {
  originalInvocation: A2AToolInvocation;
  performanceProfile: PerformanceProfile;
  systemLoad: SystemLoadMetrics;
  historicalData: HistoricalPerformanceData;
  constraints: PerformanceConstraints;
}

export interface OptimizationResult {
  success: boolean;
  optimizationApplied: string[];
  performanceImprovement: {
    latencyReduction: number;
    throughputIncrease: number;
    resourceSavings: Record<string, number>;
  };
  response?: A2AToolResponse;
  metadata: {
    executionTime: number;
    optimizationOverhead: number;
    cacheHit: boolean;
    fallbackUsed: boolean;
  };
}

export interface SystemLoadMetrics {
  cpuUsage: number;
  memoryUsage: number;
  networkLatency: number;
  diskIO: number;
  activeConnections: number;
  queueLength: number;
  timestamp: Date;
}

export interface HistoricalPerformanceData {
  timeWindow: string;
  invocations: number;
  patterns: {
    peakHours: number[];
    commonParameterSizes: number[];
    frequentErrors: string[];
    performanceTrends: Array<{
      timestamp: Date;
      metric: string;
      value: number;
    }>;
  };
}

export interface PerformanceConstraints {
  maxLatency?: number;
  maxResourceUsage?: number;
  minSuccessRate?: number;
  budget?: number;
  availabilityTarget?: number;
}

export interface PredictionModel {
  id: string;
  name: string;
  type: "linear" | "neural" | "ensemble" | "statistical";
  features: string[];
  accuracy: number;
  lastTrained: Date;
  predictions: Record<string, any>;
}

/**
 * Main performance optimization layer
 */
export class PerformanceOptimizationLayer extends EventEmitter {
  private logger: Logger;
  private cache: CacheManager;
  private performanceMonitor: PerformanceMonitor;
  private toolRegistry: MCPToolRegistry;

  private performanceProfiles = new Map<string, PerformanceProfile>();
  private optimizationStrategies = new Map<string, OptimizationStrategy>();
  private systemLoadHistory: SystemLoadMetrics[] = [];
  private predictionModels = new Map<string, PredictionModel>();

  private circuitBreakers = new Map<string, CircuitBreaker>();
  private loadBalancers = new Map<string, LoadBalancer>();
  private batchProcessors = new Map<string, BatchProcessor>();

  constructor(
    toolRegistry: MCPToolRegistry,
    performanceMonitor: PerformanceMonitor,
  ) {
    super();
    this.logger = new Logger("PerformanceOptimizationLayer");
    this.cache = new CacheManager();
    this.performanceMonitor = performanceMonitor;
    this.toolRegistry = toolRegistry;

    this.initializeOptimizationStrategies();
    this.startPerformanceMonitoring();

    this.logger.info("Performance Optimization Layer initialized");
  }

  /**
   * Optimize tool invocation with intelligent strategies
   */
  async optimizeInvocation(
    invocation: A2AToolInvocation,
  ): Promise<OptimizationResult> {
    const startTime = Date.now();

    try {
      // Get performance profile for the tool
      const profile = await this.getPerformanceProfile(invocation.toolId);

      // Collect current system metrics
      const systemLoad = await this.getCurrentSystemLoad();

      // Get historical data
      const historicalData = await this.getHistoricalData(invocation.toolId);

      // Create optimization context
      const context: OptimizationContext = {
        originalInvocation: invocation,
        performanceProfile: profile,
        systemLoad,
        historicalData,
        constraints: this.extractConstraints(invocation),
      };

      // Select and apply optimization strategies
      const applicableStrategies =
        await this.selectOptimizationStrategies(context);

      if (applicableStrategies.length === 0) {
        // No optimization needed, execute normally
        return await this.executeWithoutOptimization(
          invocation,
          context,
          startTime,
        );
      }

      // Apply optimizations in priority order
      let result: OptimizationResult | null = null;
      const appliedOptimizations: string[] = [];

      for (const strategy of applicableStrategies) {
        try {
          const strategyResult = await this.applyOptimizationStrategy(
            strategy,
            context,
          );

          if (strategyResult.success) {
            result = strategyResult;
            appliedOptimizations.push(strategy.name);

            // Update strategy success metrics
            await this.updateStrategyMetrics(
              strategy.id,
              true,
              strategyResult.performanceImprovement,
            );

            break; // Use first successful optimization
          }
        } catch (error: any) {
          this.logger.warn("Optimization strategy failed", {
            strategy: strategy.name,
            error: error.message,
          });

          await this.updateStrategyMetrics(strategy.id, false);
        }
      }

      // If no optimization succeeded, fall back to normal execution
      if (!result) {
        result = await this.executeWithoutOptimization(
          invocation,
          context,
          startTime,
        );
        result.metadata.fallbackUsed = true;
      }

      // Update performance profile
      await this.updatePerformanceProfile(invocation.toolId, result);

      // Log optimization results
      this.logger.info("Invocation optimization completed", {
        toolId: invocation.toolId,
        appliedOptimizations,
        latencyReduction: result.performanceImprovement.latencyReduction,
        executionTime: Date.now() - startTime,
      });

      this.emit("optimization_applied", {
        invocation,
        result,
        appliedOptimizations,
      });

      return result;
    } catch (error: any) {
      this.logger.error("Optimization failed", {
        toolId: invocation.toolId,
        error: error.message,
      });

      // Fall back to unoptimized execution
      return await this.executeWithoutOptimization(
        invocation,
        {
          originalInvocation: invocation,
          performanceProfile: await this.getPerformanceProfile(
            invocation.toolId,
          ),
          systemLoad: await this.getCurrentSystemLoad(),
          historicalData: await this.getHistoricalData(invocation.toolId),
          constraints: this.extractConstraints(invocation),
        },
        startTime,
      );
    }
  }

  /**
   * Get or create performance profile for a tool
   */
  async getPerformanceProfile(toolId: string): Promise<PerformanceProfile> {
    let profile = this.performanceProfiles.get(toolId);

    if (!profile) {
      // Create initial profile from tool registration
      const registration = this.toolRegistry.getToolRegistration(toolId as any);

      profile = {
        toolId,
        averageLatency: registration?.metadata.averageLatency || 1000,
        p95Latency: (registration?.metadata.averageLatency || 1000) * 2,
        p99Latency: (registration?.metadata.averageLatency || 1000) * 3,
        successRate: registration?.metadata.successRate || 0.95,
        errorRate: 1 - (registration?.metadata.successRate || 0.95),
        throughput: 10, // requests per second
        resourceUtilization: {
          cpu: 10,
          memory: 50,
          network: 5,
          io: 2,
        },
        contextMetrics: {
          trustLevelPerformance: {},
          parameterSizeImpact: 1.0,
          timeOfDayVariance: 0.1,
          loadFactorImpact: 1.2,
        },
        lastUpdated: new Date(),
      };

      this.performanceProfiles.set(toolId, profile);
    }

    return profile;
  }

  /**
   * Predict performance for an invocation
   */
  async predictPerformance(invocation: A2AToolInvocation): Promise<{
    estimatedLatency: number;
    estimatedSuccessRate: number;
    estimatedResourceUsage: Record<string, number>;
    confidence: number;
  }> {
    const profile = await this.getPerformanceProfile(invocation.toolId);
    const systemLoad = await this.getCurrentSystemLoad();

    // Apply predictive models
    const latencyModel = this.predictionModels.get("latency");
    const successRateModel = this.predictionModels.get("success_rate");

    let estimatedLatency = profile.averageLatency;
    const estimatedSuccessRate = profile.successRate;
    let confidence = 0.7; // Base confidence

    // Adjust based on system load
    const loadFactor = (systemLoad.cpuUsage + systemLoad.memoryUsage) / 200;
    estimatedLatency *=
      1 + loadFactor * profile.contextMetrics.loadFactorImpact;

    // Adjust based on parameter size
    const parameterSize = JSON.stringify(invocation.parameters).length;
    const sizeFactor = Math.log(parameterSize + 1) / 10;
    estimatedLatency *=
      1 + sizeFactor * profile.contextMetrics.parameterSizeImpact;

    // Adjust based on trust level
    const trustPerformance =
      profile.contextMetrics.trustLevelPerformance[
        invocation.context.trustLevel
      ];
    if (trustPerformance) {
      estimatedLatency *= trustPerformance;
      confidence += 0.1;
    }

    // Time of day adjustment
    const hour = new Date().getHours();
    const timeVariance =
      Math.sin((hour / 24) * 2 * Math.PI) *
      profile.contextMetrics.timeOfDayVariance;
    estimatedLatency *= 1 + timeVariance;

    return {
      estimatedLatency,
      estimatedSuccessRate,
      estimatedResourceUsage: {
        cpu: profile.resourceUtilization.cpu * (1 + loadFactor),
        memory: profile.resourceUtilization.memory * (1 + sizeFactor),
        network: profile.resourceUtilization.network,
        io: profile.resourceUtilization.io,
      },
      confidence,
    };
  }

  /**
   * Enable or disable optimization strategies
   */
  configureOptimizationStrategy(strategyId: string, enabled: boolean): void {
    const strategy = this.optimizationStrategies.get(strategyId);
    if (strategy) {
      strategy.enabled = enabled;
      this.logger.info("Optimization strategy configured", {
        strategyId,
        enabled,
      });
    }
  }

  /**
   * Add custom optimization strategy
   */
  addOptimizationStrategy(strategy: OptimizationStrategy): void {
    this.optimizationStrategies.set(strategy.id, strategy);
    this.logger.info("Custom optimization strategy added", {
      id: strategy.id,
      name: strategy.name,
    });
  }

  /**
   * Get performance statistics
   */
  getPerformanceStatistics(): {
    totalOptimizations: number;
    averageImprovement: number;
    strategyEffectiveness: Record<string, number>;
    systemLoad: SystemLoadMetrics;
    profileCount: number;
  } {
    const strategies = Array.from(this.optimizationStrategies.values());
    const totalOptimizations = strategies.reduce(
      (sum, s) => sum + s.successRate,
      0,
    );
    const averageImprovement =
      strategies.reduce((sum, s) => sum + s.averageImprovement, 0) /
      strategies.length;

    const strategyEffectiveness: Record<string, number> = {};
    strategies.forEach((s) => {
      strategyEffectiveness[s.name] = s.successRate * s.averageImprovement;
    });

    return {
      totalOptimizations,
      averageImprovement,
      strategyEffectiveness,
      systemLoad: this.systemLoadHistory[this.systemLoadHistory.length - 1] || {
        cpuUsage: 0,
        memoryUsage: 0,
        networkLatency: 0,
        diskIO: 0,
        activeConnections: 0,
        queueLength: 0,
        timestamp: new Date(),
      },
      profileCount: this.performanceProfiles.size,
    };
  }

  /**
   * Private helper methods
   */

  private initializeOptimizationStrategies(): void {
    // Caching strategy
    this.addOptimizationStrategy({
      id: "intelligent_caching",
      name: "Intelligent Caching",
      description: "Cache results based on parameters and context",
      conditions: [
        {
          type: "latency",
          operator: "gt",
          value: 500, // Cache if latency > 500ms
        },
      ],
      actions: [
        {
          type: "cache",
          parameters: { ttl: 300000, strategy: "lru" },
          execute: async (invocation, context) =>
            this.applyCachingOptimization(invocation, context),
        },
      ],
      priority: 1,
      successRate: 0.85,
      averageImprovement: 0.7,
      enabled: true,
    });

    // Circuit breaker strategy
    this.addOptimizationStrategy({
      id: "circuit_breaker",
      name: "Circuit Breaker",
      description: "Prevent cascading failures with circuit breaker pattern",
      conditions: [
        {
          type: "error_rate",
          operator: "gt",
          value: 0.1, // Activate if error rate > 10%
        },
      ],
      actions: [
        {
          type: "circuit_breaker",
          parameters: { failureThreshold: 5, resetTimeout: 30000 },
          execute: async (invocation, context) =>
            this.applyCircuitBreakerOptimization(invocation, context),
        },
      ],
      priority: 2,
      successRate: 0.9,
      averageImprovement: 0.3,
      enabled: true,
    });

    // Load balancing strategy
    this.addOptimizationStrategy({
      id: "load_balancing",
      name: "Load Balancing",
      description: "Distribute load across multiple instances",
      conditions: [
        {
          type: "resource_usage",
          operator: "gt",
          value: 0.8, // Balance if resource usage > 80%
        },
      ],
      actions: [
        {
          type: "load_balance",
          parameters: { strategy: "round_robin", healthCheck: true },
          execute: async (invocation, context) =>
            this.applyLoadBalancingOptimization(invocation, context),
        },
      ],
      priority: 3,
      successRate: 0.75,
      averageImprovement: 0.4,
      enabled: true,
    });

    // Parallel execution strategy
    this.addOptimizationStrategy({
      id: "parallel_execution",
      name: "Parallel Execution",
      description: "Execute independent operations in parallel",
      conditions: [
        {
          type: "custom",
          operator: "eq",
          value: true,
          customCheck: (profile, context) =>
            this.canParallelize(profile, context),
        },
      ],
      actions: [
        {
          type: "parallel",
          parameters: { maxConcurrency: 5 },
          execute: async (invocation, context) =>
            this.applyParallelExecutionOptimization(invocation, context),
        },
      ],
      priority: 4,
      successRate: 0.8,
      averageImprovement: 0.5,
      enabled: true,
    });

    // Batch processing strategy
    this.addOptimizationStrategy({
      id: "batch_processing",
      name: "Batch Processing",
      description: "Batch similar requests for efficiency",
      conditions: [
        {
          type: "throughput",
          operator: "gt",
          value: 10, // Batch if high throughput
        },
      ],
      actions: [
        {
          type: "batch",
          parameters: { batchSize: 10, maxWaitTime: 100 },
          execute: async (invocation, context) =>
            this.applyBatchProcessingOptimization(invocation, context),
        },
      ],
      priority: 5,
      successRate: 0.7,
      averageImprovement: 0.6,
      enabled: true,
    });
  }

  private async selectOptimizationStrategies(
    context: OptimizationContext,
  ): Promise<OptimizationStrategy[]> {
    const applicable: OptimizationStrategy[] = [];

    for (const strategy of this.optimizationStrategies.values()) {
      if (!strategy.enabled) continue;

      const conditionsMet = await this.evaluateConditions(
        strategy.conditions,
        context,
      );
      if (conditionsMet) {
        applicable.push(strategy);
      }
    }

    // Sort by priority and effectiveness
    return applicable.sort((a, b) => {
      const scoreA = a.priority * a.successRate * a.averageImprovement;
      const scoreB = b.priority * b.successRate * b.averageImprovement;
      return scoreB - scoreA;
    });
  }

  private async evaluateConditions(
    conditions: OptimizationCondition[],
    context: OptimizationContext,
  ): Promise<boolean> {
    for (const condition of conditions) {
      if (!(await this.evaluateCondition(condition, context))) {
        return false;
      }
    }
    return true;
  }

  private async evaluateCondition(
    condition: OptimizationCondition,
    context: OptimizationContext,
  ): Promise<boolean> {
    const { profile } = context;

    let actualValue: any;

    switch (condition.type) {
      case "latency":
        actualValue = profile.averageLatency;
        break;
      case "error_rate":
        actualValue = profile.errorRate;
        break;
      case "throughput":
        actualValue = profile.throughput;
        break;
      case "resource_usage":
        actualValue =
          Math.max(
            profile.resourceUtilization.cpu,
            profile.resourceUtilization.memory,
          ) / 100;
        break;
      case "custom":
        return condition.customCheck
          ? condition.customCheck(profile, context.originalInvocation.context)
          : false;
      default:
        return false;
    }

    return this.compareValues(actualValue, condition.operator, condition.value);
  }

  private compareValues(actual: any, operator: string, expected: any): boolean {
    switch (operator) {
      case "gt":
        return actual > expected;
      case "lt":
        return actual < expected;
      case "eq":
        return actual === expected;
      case "gte":
        return actual >= expected;
      case "lte":
        return actual <= expected;
      case "contains":
        return String(actual).includes(String(expected));
      case "matches":
        return new RegExp(expected).test(String(actual));
      default:
        return false;
    }
  }

  private async applyOptimizationStrategy(
    strategy: OptimizationStrategy,
    context: OptimizationContext,
  ): Promise<OptimizationResult> {
    const startTime = Date.now();

    // Execute the primary action
    const action = strategy.actions[0]; // Use first action for simplicity
    const result = await action.execute(context.originalInvocation, context);

    result.optimizationApplied = [strategy.name];
    result.metadata.optimizationOverhead = Date.now() - startTime;

    return result;
  }

  // Optimization action implementations

  private async applyCachingOptimization(
    invocation: A2AToolInvocation,
    context: OptimizationContext,
  ): Promise<OptimizationResult> {
    const cacheKey = this.generateCacheKey(invocation);
    const cached = await this.cache.get<A2AToolResponse>(cacheKey);

    if (cached) {
      return {
        success: true,
        optimizationApplied: ["caching"],
        performanceImprovement: {
          latencyReduction: 0.9,
          throughputIncrease: 0.5,
          resourceSavings: { cpu: 90, memory: 50 },
        },
        response: cached,
        metadata: {
          executionTime: 10,
          optimizationOverhead: 5,
          cacheHit: true,
          fallbackUsed: false,
        },
      };
    }

    // Execute and cache result
    const result = await this.executeWithoutOptimization(
      invocation,
      context,
      Date.now(),
    );

    if (result.response && result.response.success) {
      await this.cache.set(cacheKey, result.response, 300000); // 5 minutes
    }

    return result;
  }

  private async applyCircuitBreakerOptimization(
    invocation: A2AToolInvocation,
    context: OptimizationContext,
  ): Promise<OptimizationResult> {
    const circuitBreaker = this.getOrCreateCircuitBreaker(invocation.toolId);

    if (circuitBreaker.isOpen()) {
      throw new Error("Circuit breaker is open - tool temporarily unavailable");
    }

    try {
      const result = await this.executeWithoutOptimization(
        invocation,
        context,
        Date.now(),
      );
      circuitBreaker.recordSuccess();
      return result;
    } catch (error) {
      circuitBreaker.recordFailure();
      throw error;
    }
  }

  private async applyLoadBalancingOptimization(
    invocation: A2AToolInvocation,
    context: OptimizationContext,
  ): Promise<OptimizationResult> {
    const loadBalancer = this.getOrCreateLoadBalancer(invocation.toolId);
    const selectedInstance = loadBalancer.selectInstance();

    // Simulate load balancing by adjusting execution
    const result = await this.executeWithoutOptimization(
      invocation,
      context,
      Date.now(),
    );

    result.performanceImprovement = {
      latencyReduction: 0.3,
      throughputIncrease: 0.4,
      resourceSavings: { cpu: 20, memory: 15 },
    };

    return result;
  }

  private async applyParallelExecutionOptimization(
    invocation: A2AToolInvocation,
    context: OptimizationContext,
  ): Promise<OptimizationResult> {
    // Simulate parallel execution
    const result = await this.executeWithoutOptimization(
      invocation,
      context,
      Date.now(),
    );

    result.performanceImprovement = {
      latencyReduction: 0.5,
      throughputIncrease: 0.8,
      resourceSavings: { cpu: 30, memory: 20 },
    };

    return result;
  }

  private async applyBatchProcessingOptimization(
    invocation: A2AToolInvocation,
    context: OptimizationContext,
  ): Promise<OptimizationResult> {
    const batchProcessor = this.getOrCreateBatchProcessor(invocation.toolId);

    return new Promise((resolve) => {
      batchProcessor.addRequest(invocation, (result) => {
        resolve({
          success: true,
          optimizationApplied: ["batch_processing"],
          performanceImprovement: {
            latencyReduction: 0.4,
            throughputIncrease: 0.6,
            resourceSavings: { cpu: 25, memory: 20, network: 40 },
          },
          response: result,
          metadata: {
            executionTime: 200,
            optimizationOverhead: 50,
            cacheHit: false,
            fallbackUsed: false,
          },
        });
      });
    });
  }

  private async executeWithoutOptimization(
    invocation: A2AToolInvocation,
    context: OptimizationContext,
    startTime: number,
  ): Promise<OptimizationResult> {
    // Simulate tool execution
    const executionTime = Math.random() * 1000 + 500; // 500-1500ms
    await new Promise((resolve) => setTimeout(resolve, executionTime));

    const response: A2AToolResponse = {
      requestId: invocation.requestId,
      toolId: invocation.toolId,
      success: Math.random() > 0.1, // 90% success rate
      data: { result: "simulated execution" },
      metadata: {
        executionTime,
        resourceUsage: { cpu: 10, memory: 20, network: 5 },
        cached: false,
        trustVerified: true,
        securityFlags: [],
      },
      timestamp: Date.now(),
    };

    return {
      success: response.success,
      optimizationApplied: [],
      performanceImprovement: {
        latencyReduction: 0,
        throughputIncrease: 0,
        resourceSavings: {},
      },
      response,
      metadata: {
        executionTime: Date.now() - startTime,
        optimizationOverhead: 0,
        cacheHit: false,
        fallbackUsed: false,
      },
    };
  }

  private generateCacheKey(invocation: A2AToolInvocation): string {
    const keyData = {
      toolId: invocation.toolId,
      parameters: invocation.parameters,
      trustLevel: invocation.context.trustLevel,
    };
    return `opt_cache:${Buffer.from(JSON.stringify(keyData)).toString("base64")}`;
  }

  private canParallelize(
    profile: PerformanceProfile,
    context: A2AToolContext,
  ): boolean {
    // Simple heuristic for parallel execution capability
    return profile.resourceUtilization.cpu < 50 && profile.averageLatency > 200;
  }

  private extractConstraints(
    invocation: A2AToolInvocation,
  ): PerformanceConstraints {
    // Extract constraints from invocation metadata
    return {
      maxLatency: invocation.context.metadata?.maxLatency,
      maxResourceUsage: invocation.context.metadata?.maxResourceUsage,
      minSuccessRate: invocation.context.metadata?.minSuccessRate || 0.95,
    };
  }

  private async getCurrentSystemLoad(): Promise<SystemLoadMetrics> {
    // Simulate system load metrics
    return {
      cpuUsage: Math.random() * 100,
      memoryUsage: Math.random() * 100,
      networkLatency: Math.random() * 100,
      diskIO: Math.random() * 100,
      activeConnections: Math.floor(Math.random() * 1000),
      queueLength: Math.floor(Math.random() * 50),
      timestamp: new Date(),
    };
  }

  private async getHistoricalData(
    toolId: string,
  ): Promise<HistoricalPerformanceData> {
    // Simulate historical data
    return {
      timeWindow: "24h",
      invocations: Math.floor(Math.random() * 1000),
      patterns: {
        peakHours: [9, 10, 11, 14, 15, 16],
        commonParameterSizes: [100, 500, 1000],
        frequentErrors: ["timeout", "network_error"],
        performanceTrends: [],
      },
    };
  }

  private async updatePerformanceProfile(
    toolId: string,
    result: OptimizationResult,
  ): Promise<void> {
    const profile = await this.getPerformanceProfile(toolId);

    if (result.response) {
      const latency = result.response.metadata.executionTime;

      // Update moving averages
      profile.averageLatency = profile.averageLatency * 0.9 + latency * 0.1;
      profile.successRate =
        profile.successRate * 0.9 + (result.response.success ? 1 : 0) * 0.1;
      profile.errorRate = 1 - profile.successRate;
      profile.lastUpdated = new Date();
    }
  }

  private async updateStrategyMetrics(
    strategyId: string,
    success: boolean,
    improvement?: OptimizationResult["performanceImprovement"],
  ): Promise<void> {
    const strategy = this.optimizationStrategies.get(strategyId);
    if (strategy) {
      // Update success rate
      strategy.successRate =
        strategy.successRate * 0.9 + (success ? 1 : 0) * 0.1;

      // Update average improvement
      if (success && improvement) {
        const totalImprovement =
          improvement.latencyReduction + improvement.throughputIncrease;
        strategy.averageImprovement =
          strategy.averageImprovement * 0.9 + totalImprovement * 0.1;
      }
    }
  }

  private startPerformanceMonitoring(): void {
    // Collect system load metrics every 30 seconds
    setInterval(async () => {
      const load = await this.getCurrentSystemLoad();
      this.systemLoadHistory.push(load);

      // Keep only last 100 measurements
      if (this.systemLoadHistory.length > 100) {
        this.systemLoadHistory.shift();
      }
    }, 30000);
  }

  // Helper classes for optimization strategies

  private getOrCreateCircuitBreaker(toolId: string): CircuitBreaker {
    if (!this.circuitBreakers.has(toolId)) {
      this.circuitBreakers.set(toolId, new CircuitBreaker(toolId));
    }
    return this.circuitBreakers.get(toolId)!;
  }

  private getOrCreateLoadBalancer(toolId: string): LoadBalancer {
    if (!this.loadBalancers.has(toolId)) {
      this.loadBalancers.set(toolId, new LoadBalancer(toolId));
    }
    return this.loadBalancers.get(toolId)!;
  }

  private getOrCreateBatchProcessor(toolId: string): BatchProcessor {
    if (!this.batchProcessors.has(toolId)) {
      this.batchProcessors.set(toolId, new BatchProcessor(toolId));
    }
    return this.batchProcessors.get(toolId)!;
  }
}

/**
 * Circuit Breaker implementation
 */
class CircuitBreaker {
  private failures = 0;
  private lastFailureTime = 0;
  private state: "closed" | "open" | "half-open" = "closed";

  constructor(
    private toolId: string,
    private failureThreshold = 5,
    private resetTimeout = 30000,
  ) {}

  isOpen(): boolean {
    if (this.state === "open") {
      if (Date.now() - this.lastFailureTime > this.resetTimeout) {
        this.state = "half-open";
      }
    }
    return this.state === "open";
  }

  recordSuccess(): void {
    this.failures = 0;
    this.state = "closed";
  }

  recordFailure(): void {
    this.failures++;
    this.lastFailureTime = Date.now();

    if (this.failures >= this.failureThreshold) {
      this.state = "open";
    }
  }
}

/**
 * Load Balancer implementation
 */
class LoadBalancer {
  private instances = ["instance1", "instance2", "instance3"];
  private currentIndex = 0;

  constructor(private toolId: string) {}

  selectInstance(): string {
    const instance = this.instances[this.currentIndex];
    this.currentIndex = (this.currentIndex + 1) % this.instances.length;
    return instance;
  }
}

/**
 * Batch Processor implementation
 */
class BatchProcessor {
  private pending: Array<{
    invocation: A2AToolInvocation;
    callback: (result: A2AToolResponse) => void;
  }> = [];
  private timer?: ReturnType<typeof setTimeout>;

  constructor(
    private toolId: string,
    private batchSize = 10,
    private maxWaitTime = 100,
  ) {}

  addRequest(
    invocation: A2AToolInvocation,
    callback: (result: A2AToolResponse) => void,
  ): void {
    this.pending.push({ invocation, callback });

    if (this.pending.length >= this.batchSize) {
      this.processBatch();
    } else if (!this.timer) {
      this.timer = setTimeout(() => this.processBatch(), this.maxWaitTime);
    }
  }

  private processBatch(): void {
    if (this.timer) {
      clearTimeout(this.timer);
      this.timer = undefined;
    }

    const batch = this.pending.splice(0, this.batchSize);

    // Simulate batch processing
    setTimeout(() => {
      batch.forEach(({ invocation, callback }) => {
        const response: A2AToolResponse = {
          requestId: invocation.requestId,
          toolId: invocation.toolId,
          success: true,
          data: { result: "batch processed" },
          metadata: {
            executionTime: 150,
            resourceUsage: { cpu: 5, memory: 10, network: 2 },
            cached: false,
            trustVerified: true,
            securityFlags: [],
          },
          timestamp: Date.now(),
        };
        callback(response);
      });
    }, 150);
  }
}