Agent Topology Optimizer

// Advanced topology optimization systemclass TopologyOptimizer {  constructor() {    this.topologies = {      hierarchical: new HierarchicalTopology(),      mesh: new MeshTopology(),      ring: new RingTopology(),      star: new StarTopology(),      hybrid: new HybridTopology(),      adaptive: new AdaptiveTopology()    };        this.optimizer = new NetworkOptimizer();    this.analyzer = new TopologyAnalyzer();    this.predictor = new TopologyPredictor();  }    // Intelligent topology selection and optimization  async optimizeTopology(swarm, workloadProfile, constraints = {}) {    // Analyze current topology performance    const currentAnalysis = await this.analyzer.analyze(swarm.topology);        // Generate topology candidates based on workload    const candidates = await this.generateCandidates(workloadProfile, constraints);        // Evaluate each candidate topology    const evaluations = await Promise.all(      candidates.map(candidate => this.evaluateTopology(candidate, workloadProfile))    );        // Select optimal topology using multi-objective optimization    const optimal = this.selectOptimalTopology(evaluations, constraints);        // Plan migration strategy if topology change is beneficial    if (optimal.improvement > constraints.minImprovement || 0.1) {      const migrationPlan = await this.planMigration(swarm.topology, optimal.topology);      return {        recommended: optimal.topology,        improvement: optimal.improvement,        migrationPlan,        estimatedDowntime: migrationPlan.estimatedDowntime,        benefits: optimal.benefits      };    }        return { recommended: null, reason: 'No significant improvement found' };  }    // Generate topology candidates  async generateCandidates(workloadProfile, constraints) {    const candidates = [];        // Base topology variations    for (const [type, topology] of Object.entries(this.topologies)) {      if (this.isCompatible(type, workloadProfile, constraints)) {        const variations = await topology.generateVariations(workloadProfile);        candidates.push(...variations);      }    }        // Hybrid topology generation    const hybrids = await this.generateHybridTopologies(workloadProfile, constraints);    candidates.push(...hybrids);        // AI-generated novel topologies    const aiGenerated = await this.generateAITopologies(workloadProfile);    candidates.push(...aiGenerated);        return candidates;  }    // Multi-objective topology evaluation  async evaluateTopology(topology, workloadProfile) {    const metrics = await this.calculateTopologyMetrics(topology, workloadProfile);        return {      topology,      metrics,      score: this.calculateOverallScore(metrics),      strengths: this.identifyStrengths(metrics),      weaknesses: this.identifyWeaknesses(metrics),      suitability: this.calculateSuitability(metrics, workloadProfile)    };  }}

// Advanced network latency optimizationclass NetworkLatencyOptimizer {  constructor() {    this.latencyAnalyzer = new LatencyAnalyzer();    this.routingOptimizer = new RoutingOptimizer();    this.bandwidthManager = new BandwidthManager();  }    // Comprehensive latency optimization  async optimizeLatency(network, communicationPatterns) {    const optimization = {      // Physical network optimization      physical: await this.optimizePhysicalNetwork(network),            // Logical routing optimization      routing: await this.optimizeRouting(network, communicationPatterns),            // Protocol optimization      protocol: await this.optimizeProtocols(network),            // Caching strategies      caching: await this.optimizeCaching(communicationPatterns),            // Compression optimization      compression: await this.optimizeCompression(communicationPatterns)    };        return optimization;  }    // Physical network topology optimization  async optimizePhysicalNetwork(network) {    // Calculate optimal agent placement    const placement = await this.calculateOptimalPlacement(network.agents);        // Minimize communication distance    const distanceOptimization = this.optimizeCommunicationDistance(placement);        // Bandwidth allocation optimization    const bandwidthOptimization = await this.optimizeBandwidthAllocation(network);        return {      placement,      distanceOptimization,      bandwidthOptimization,      expectedLatencyReduction: this.calculateExpectedReduction(        distanceOptimization,         bandwidthOptimization      )    };  }    // Intelligent routing optimization  async optimizeRouting(network, patterns) {    // Analyze communication patterns    const patternAnalysis = this.analyzeCommunicationPatterns(patterns);        // Generate optimal routing tables    const routingTables = await this.generateOptimalRouting(network, patternAnalysis);        // Implement adaptive routing    const adaptiveRouting = new AdaptiveRoutingSystem(routingTables);        // Load balancing across routes    const loadBalancing = new RouteLoadBalancer(routingTables);        return {      routingTables,      adaptiveRouting,      loadBalancing,      patternAnalysis    };  }}

// Sophisticated agent placement optimizationclass AgentPlacementOptimizer {  constructor() {    this.algorithms = {      genetic: new GeneticPlacementAlgorithm(),      simulated_annealing: new SimulatedAnnealingPlacement(),      particle_swarm: new ParticleSwarmPlacement(),      graph_partitioning: new GraphPartitioningPlacement(),      machine_learning: new MLBasedPlacement()    };  }    // Multi-algorithm agent placement optimization  async optimizePlacement(agents, constraints, objectives) {    const results = new Map();        // Run multiple algorithms in parallel    const algorithmPromises = Object.entries(this.algorithms).map(      async ([name, algorithm]) => {        const result = await algorithm.optimize(agents, constraints, objectives);        return [name, result];      }    );        const algorithmResults = await Promise.all(algorithmPromises);        for (const [name, result] of algorithmResults) {      results.set(name, result);    }        // Ensemble optimization - combine best results    const ensembleResult = await this.ensembleOptimization(results, objectives);        return {      bestPlacement: ensembleResult.placement,      algorithm: ensembleResult.algorithm,      score: ensembleResult.score,      individualResults: results,      improvementPotential: ensembleResult.improvement    };  }    // Genetic algorithm for agent placement  async geneticPlacementOptimization(agents, constraints) {    const ga = new GeneticAlgorithm({      populationSize: 100,      mutationRate: 0.1,      crossoverRate: 0.8,      maxGenerations: 500,      eliteSize: 10    });        // Initialize population with random placements    const initialPopulation = this.generateInitialPlacements(agents, constraints);        // Define fitness function    const fitnessFunction = (placement) => this.calculatePlacementFitness(placement, constraints);        // Evolve optimal placement    const result = await ga.evolve(initialPopulation, fitnessFunction);        return {      placement: result.bestIndividual,      fitness: result.bestFitness,      generations: result.generations,      convergence: result.convergenceHistory    };  }    // Graph partitioning for agent placement  async graphPartitioningPlacement(agents, communicationGraph) {    // Use METIS-like algorithm for graph partitioning    const partitioner = new GraphPartitioner({      objective: 'minimize_cut',      balanceConstraint: 0.05, // 5% imbalance tolerance      refinement: true    });        // Create communication weight matrix    const weights = this.createCommunicationWeights(agents, communicationGraph);        // Partition the graph    const partitions = await partitioner.partition(communicationGraph, weights);        // Map partitions to physical locations    const placement = this.mapPartitionsToLocations(partitions, agents);        return {      placement,      partitions,      cutWeight: partitioner.getCutWeight(),      balance: partitioner.getBalance()    };  }}

// Advanced communication pattern optimizationclass CommunicationOptimizer {  constructor() {    this.patternAnalyzer = new PatternAnalyzer();    this.protocolOptimizer = new ProtocolOptimizer();    this.messageOptimizer = new MessageOptimizer();    this.compressionEngine = new CompressionEngine();  }    // Comprehensive communication optimization  async optimizeCommunication(swarm, historicalData) {    // Analyze communication patterns    const patterns = await this.patternAnalyzer.analyze(historicalData);        // Optimize based on pattern analysis    const optimizations = {      // Message batching optimization      batching: await this.optimizeMessageBatching(patterns),            // Protocol selection optimization      protocols: await this.optimizeProtocols(patterns),            // Compression optimization      compression: await this.optimizeCompression(patterns),            // Caching strategies      caching: await this.optimizeCaching(patterns),            // Routing optimization      routing: await this.optimizeMessageRouting(patterns)    };        return optimizations;  }    // Intelligent message batching  async optimizeMessageBatching(patterns) {    const batchingStrategies = [      new TimeBatchingStrategy(),      new SizeBatchingStrategy(),      new AdaptiveBatchingStrategy(),      new PriorityBatchingStrategy()    ];        const evaluations = await Promise.all(      batchingStrategies.map(strategy =>         this.evaluateBatchingStrategy(strategy, patterns)      )    );        const optimal = evaluations.reduce((best, current) =>       current.score > best.score ? current : best    );        return {      strategy: optimal.strategy,      configuration: optimal.configuration,      expectedImprovement: optimal.improvement,      metrics: optimal.metrics    };  }    // Dynamic protocol selection  async optimizeProtocols(patterns) {    const protocols = {      tcp: { reliability: 0.99, latency: 'medium', overhead: 'high' },      udp: { reliability: 0.95, latency: 'low', overhead: 'low' },      websocket: { reliability: 0.98, latency: 'medium', overhead: 'medium' },      grpc: { reliability: 0.99, latency: 'low', overhead: 'medium' },      mqtt: { reliability: 0.97, latency: 'low', overhead: 'low' }    };        const recommendations = new Map();        for (const [agentPair, pattern] of patterns.pairwisePatterns) {      const optimal = this.selectOptimalProtocol(protocols, pattern);      recommendations.set(agentPair, optimal);    }        return recommendations;  }}

// Comprehensive MCP topology integrationconst topologyIntegration = {  // Real-time topology optimization  async optimizeSwarmTopology(swarmId, optimizationConfig = {}) {    // Get current swarm status    const swarmStatus = await mcp.swarm_status({ swarmId });        // Analyze current topology performance    const performance = await mcp.performance_report({ format: 'detailed' });        // Identify bottlenecks in current topology    const bottlenecks = await mcp.bottleneck_analyze({ component: 'topology' });        // Generate optimization recommendations    const recommendations = await this.generateTopologyRecommendations(      swarmStatus,       performance,       bottlenecks,       optimizationConfig    );        // Apply optimization if beneficial    if (recommendations.beneficial) {      const result = await mcp.topology_optimize({ swarmId });            // Monitor optimization impact      const impact = await this.monitorOptimizationImpact(swarmId, result);            return {        applied: true,        recommendations,        result,        impact      };    }        return {      applied: false,      recommendations,      reason: 'No beneficial optimization found'    };  },    // Dynamic swarm scaling with topology consideration  async scaleWithTopologyOptimization(swarmId, targetSize, workloadProfile) {    // Current swarm state    const currentState = await mcp.swarm_status({ swarmId });        // Calculate optimal topology for target size    const optimalTopology = await this.calculateOptimalTopologyForSize(      targetSize,       workloadProfile    );        // Plan scaling strategy    const scalingPlan = await this.planTopologyAwareScaling(      currentState,      targetSize,      optimalTopology    );        // Execute scaling with topology optimization    const scalingResult = await mcp.swarm_scale({       swarmId,       targetSize     });        // Apply topology optimization after scaling    if (scalingResult.success) {      await mcp.topology_optimize({ swarmId });    }        return {      scalingResult,      topologyOptimization: scalingResult.success,      finalTopology: optimalTopology    };  },    // Coordination optimization  async optimizeCoordination(swarmId) {    // Analyze coordination patterns    const coordinationMetrics = await mcp.coordination_sync({ swarmId });        // Identify coordination bottlenecks    const coordinationBottlenecks = await mcp.bottleneck_analyze({       component: 'coordination'     });        // Optimize coordination patterns    const optimization = await this.optimizeCoordinationPatterns(      coordinationMetrics,      coordinationBottlenecks    );        return optimization;  }};

// AI-powered topology optimizationclass NeuralTopologyOptimizer {  constructor() {    this.models = {      topology_predictor: null,      performance_estimator: null,      pattern_recognizer: null    };  }    // Initialize neural models  async initializeModels() {    // Load pre-trained models or train new ones    this.models.topology_predictor = await mcp.model_load({       modelPath: '$models$topology_optimizer.model'     });        this.models.performance_estimator = await mcp.model_load({       modelPath: '$models$performance_estimator.model'     });        this.models.pattern_recognizer = await mcp.model_load({       modelPath: '$models$pattern_recognizer.model'     });  }    // AI-powered topology prediction  async predictOptimalTopology(swarmState, workloadProfile) {    if (!this.models.topology_predictor) {      await this.initializeModels();    }        // Prepare input features    const features = this.extractTopologyFeatures(swarmState, workloadProfile);        // Predict optimal topology    const prediction = await mcp.neural_predict({      modelId: this.models.topology_predictor.id,      input: JSON.stringify(features)    });        return {      predictedTopology: prediction.topology,      confidence: prediction.confidence,      expectedImprovement: prediction.improvement,      reasoning: prediction.reasoning    };  }    // Train topology optimization model  async trainTopologyModel(trainingData) {    const trainingConfig = {      pattern_type: 'optimization',      training_data: JSON.stringify(trainingData),      epochs: 100    };        const trainingResult = await mcp.neural_train(trainingConfig);        // Save trained model    if (trainingResult.success) {      await mcp.model_save({        modelId: trainingResult.modelId,        path: '$models$topology_optimizer.model'      });    }        return trainingResult;  }}

// Genetic algorithm implementation for topology optimizationclass GeneticTopologyOptimizer {  constructor(config = {}) {    this.populationSize = config.populationSize || 50;    this.mutationRate = config.mutationRate || 0.1;    this.crossoverRate = config.crossoverRate || 0.8;    this.maxGenerations = config.maxGenerations || 100;    this.eliteSize = config.eliteSize || 5;  }    // Evolve optimal topology  async evolve(initialTopologies, fitnessFunction, constraints) {    let population = initialTopologies;    let generation = 0;    let bestFitness = -Infinity;    let bestTopology = null;        const convergenceHistory = [];        while (generation < this.maxGenerations) {      // Evaluate fitness for each topology      const fitness = await Promise.all(        population.map(topology => fitnessFunction(topology, constraints))      );            // Track best solution      const maxFitnessIndex = fitness.indexOf(Math.max(...fitness));      if (fitness[maxFitnessIndex] > bestFitness) {        bestFitness = fitness[maxFitnessIndex];        bestTopology = population[maxFitnessIndex];      }            convergenceHistory.push({        generation,        bestFitness,        averageFitness: fitness.reduce((a, b) => a + b) / fitness.length      });            // Selection      const selected = this.selection(population, fitness);            // Crossover      const offspring = await this.crossover(selected);            // Mutation      const mutated = await this.mutation(offspring, constraints);            // Next generation      population = this.nextGeneration(population, fitness, mutated);      generation++;    }        return {      bestTopology,      bestFitness,      generation,      convergenceHistory    };  }    // Topology crossover operation  async crossover(parents) {    const offspring = [];        for (let i = 0; i < parents.length - 1; i += 2) {      if (Math.random() < this.crossoverRate) {        const [child1, child2] = await this.crossoverTopologies(          parents[i],           parents[i + 1]        );        offspring.push(child1, child2);      } else {        offspring.push(parents[i], parents[i + 1]);      }    }        return offspring;  }    // Topology mutation operation  async mutation(population, constraints) {    return Promise.all(      population.map(async topology => {        if (Math.random() < this.mutationRate) {          return await this.mutateTopology(topology, constraints);        }        return topology;      })    );  }}

// Simulated annealing implementationclass SimulatedAnnealingOptimizer {  constructor(config = {}) {    this.initialTemperature = config.initialTemperature || 1000;    this.coolingRate = config.coolingRate || 0.95;    this.minTemperature = config.minTemperature || 1;    this.maxIterations = config.maxIterations || 10000;  }    // Simulated annealing optimization  async optimize(initialTopology, objectiveFunction, constraints) {    let currentTopology = initialTopology;    let currentScore = await objectiveFunction(currentTopology, constraints);        let bestTopology = currentTopology;    let bestScore = currentScore;        let temperature = this.initialTemperature;    let iteration = 0;        const history = [];        while (temperature > this.minTemperature && iteration < this.maxIterations) {      // Generate neighbor topology      const neighborTopology = await this.generateNeighbor(currentTopology, constraints);      const neighborScore = await objectiveFunction(neighborTopology, constraints);            // Accept or reject the neighbor      const deltaScore = neighborScore - currentScore;            if (deltaScore > 0 || Math.random() < Math.exp(deltaScore / temperature)) {        currentTopology = neighborTopology;        currentScore = neighborScore;                // Update best solution        if (neighborScore > bestScore) {          bestTopology = neighborTopology;          bestScore = neighborScore;        }      }            // Record history      history.push({        iteration,        temperature,        currentScore,        bestScore      });            // Cool down      temperature *= this.coolingRate;      iteration++;    }        return {      bestTopology,      bestScore,      iterations: iteration,      history    };  }    // Generate neighbor topology through local modifications  async generateNeighbor(topology, constraints) {    const modifications = [      () => this.addConnection(topology, constraints),      () => this.removeConnection(topology, constraints),      () => this.modifyConnection(topology, constraints),      () => this.relocateAgent(topology, constraints)    ];        const modification = modifications[Math.floor(Math.random() * modifications.length)];    return await modification();  }}

// Comprehensive topology metricsconst topologyMetrics = {  // Communication efficiency  communicationEfficiency: {    latency: this.calculateAverageLatency(),    throughput: this.calculateThroughput(),    bandwidth_utilization: this.calculateBandwidthUtilization(),    message_overhead: this.calculateMessageOverhead()  },    // Network topology metrics  networkMetrics: {    diameter: this.calculateNetworkDiameter(),    clustering_coefficient: this.calculateClusteringCoefficient(),    betweenness_centrality: this.calculateBetweennessCentrality(),    degree_distribution: this.calculateDegreeDistribution()  },    // Fault tolerance  faultTolerance: {    connectivity: this.calculateConnectivity(),    redundancy: this.calculateRedundancy(),    single_point_failures: this.identifySinglePointFailures(),    recovery_time: this.calculateRecoveryTime()  },    // Scalability metrics  scalability: {    growth_capacity: this.calculateGrowthCapacity(),    scaling_efficiency: this.calculateScalingEfficiency(),    bottleneck_points: this.identifyBottleneckPoints(),    optimal_size: this.calculateOptimalSize()  }};