scirs2-linalg 0.4.2

//! Advanced distributed computing framework with machine learning capabilities

use crate::distributed::{
    load_balancer::AdaptiveLoadBalancer,
    fault_tolerance::FaultToleranceManager,
    monitoring::ResourceMonitor,
    capacity_planning::CapacityPlanner,
    topology::NetworkTopologyAnalyzer,
};
use std::collections::HashMap;
use std::time::{Duration, Instant};

/// Advanced MODE: Advanced Distributed Computing Enhancements
///
/// These enhancements provide sophisticated distributed computing capabilities
/// including adaptive load balancing, intelligent fault tolerance, and
/// advanced communication optimization.
pub struct AdvancedDistributedFramework<T>
where
    T: scirs2_core::numeric::Float + Send + Sync + 'static,
{
    /// Adaptive load balancer with machine learning
    adaptive_balancer: AdaptiveLoadBalancer,
    /// Fault tolerance manager
    fault_manager: FaultToleranceManager,
    /// Communication optimizer
    comm_optimizer: CommunicationOptimizer,
    /// Performance predictor
    performance_predictor: PerformancePredictor,
    /// Resource manager
    resource_manager: DistributedResourceManager,
    /// Network topology analyzer
    topology_analyzer: NetworkTopologyAnalyzer,
    _phantom: std::marker::PhantomData<T>,
}

/// Advanced communication optimizer
#[derive(Debug)]
pub struct CommunicationOptimizer {
    /// Network topology information
    topology: NetworkTopology,
    /// Bandwidth prediction model
    bandwidth_predictor: BandwidthPredictor,
    /// Message aggregation system
    message_aggregator: MessageAggregator,
    /// Compression optimizer
    compression_optimizer: CompressionOptimizer,
}

/// Network topology representation
#[derive(Debug, Clone)]
pub struct NetworkTopology {
    /// Nodes in the network
    nodes: HashMap<usize, NetworkNode>,
    /// Connections between nodes
    connections: HashMap<(usize, usize), ConnectionInfo>,
    /// Routing table
    routing_table: HashMap<(usize, usize), Vec<usize>>,
}

/// Information about a network node
#[derive(Debug, Clone)]
pub struct NetworkNode {
    node_id: usize,
    ip_address: std::net::IpAddr,
    port: u16,
    capabilities: NodeCapabilities,
    location: Option<GeographicLocation>,
}

/// Capabilities of a network node
#[derive(Debug, Clone)]
pub struct NodeCapabilities {
    max_bandwidth: u64,
    supported_protocols: Vec<CommunicationProtocol>,
    compression_support: Vec<crate::distributed::config::CompressionAlgorithm>,
    encryption_support: bool,
}

/// Communication protocols
#[derive(Debug, Clone, Copy)]
pub enum CommunicationProtocol {
    TCP,
    UDP,
    RDMA,
    InfiniBand,
    Custom,
}

/// Geographic location for topology-aware placement
#[derive(Debug, Clone)]
pub struct GeographicLocation {
    latitude: f64,
    longitude: f64,
    datacenter: Option<String>,
    region: Option<String>,
}

/// Connection information between nodes
#[derive(Debug, Clone)]
pub struct ConnectionInfo {
    bandwidth: u64,
    latency: f64,
    reliability: f64,
    cost: f64,
    protocol: CommunicationProtocol,
}

/// Bandwidth prediction model
#[derive(Debug)]
pub struct BandwidthPredictor {
    /// Historical bandwidth measurements
    bandwidth_history: HashMap<(usize, usize), Vec<BandwidthMeasurement>>,
    /// Prediction models per connection
    prediction_models: HashMap<(usize, usize), PredictionModel>,
    /// Current predictions
    current_predictions: HashMap<(usize, usize), BandwidthPrediction>,
}

/// Bandwidth measurement
#[derive(Debug, Clone)]
pub struct BandwidthMeasurement {
    timestamp: Instant,
    bandwidth: f64,
    message_size: usize,
    latency: f64,
    context: MeasurementContext,
}

/// Context for bandwidth measurements
#[derive(Debug, Clone)]
pub struct MeasurementContext {
    operation_type: String,
    concurrent_transfers: usize,
    network_load: f64,
    time_of_day: u8, // Hour of day (0-23)
}

/// Prediction model for bandwidth
#[derive(Debug)]
pub enum PredictionModel {
    LinearRegression(LinearRegressionModel),
    MovingAverage(MovingAverageModel),
    ExponentialSmoothing(ExponentialSmoothingModel),
    ARIMA(ARIMAModel),
}

/// Linear regression model
#[derive(Debug)]
pub struct LinearRegressionModel {
    coefficients: Vec<f64>,
    intercept: f64,
    r_squared: f64,
}

/// Moving average model
#[derive(Debug)]
pub struct MovingAverageModel {
    window_size: usize,
    weights: Vec<f64>,
}

/// Exponential smoothing model
#[derive(Debug)]
pub struct ExponentialSmoothingModel {
    alpha: f64,
    beta: f64,
    gamma: f64,
    seasonal_period: usize,
}

/// ARIMA model for time series prediction
#[derive(Debug)]
pub struct ARIMAModel {
    ar_coefficients: Vec<f64>,
    ma_coefficients: Vec<f64>,
    differencing_order: usize,
}

/// Bandwidth prediction
#[derive(Debug, Clone)]
pub struct BandwidthPrediction {
    predicted_bandwidth: f64,
    confidence_interval: (f64, f64),
    prediction_horizon: Duration,
    model_accuracy: f64,
}

/// Message aggregation system
#[derive(Debug)]
pub struct MessageAggregator {
    /// Pending messages for aggregation
    pending_messages: HashMap<MessageAggregationKey, Vec<PendingMessage>>,
    /// Aggregation strategies
    aggregation_strategies: HashMap<String, AggregationStrategy>,
    /// Timing configuration
    timing_config: AggregationTimingConfig,
}

/// Key for message aggregation
#[derive(Debug, Clone, PartialEq, Eq, Hash)]
pub struct MessageAggregationKey {
    source_node: usize,
    destination_node: usize,
    message_type: String,
    priority: MessagePriority,
}

/// Priority levels for messages
#[derive(Debug, Clone, Copy, PartialEq, Eq, PartialOrd, Ord, Hash)]
pub enum MessagePriority {
    Low,
    Normal,
    High,
    Critical,
}

/// Pending message for aggregation
#[derive(Debug, Clone)]
pub struct PendingMessage {
    message_id: String,
    payload: Vec<u8>,
    timestamp: Instant,
    size: usize,
    metadata: MessageMetadata,
}

/// Metadata for messages
#[derive(Debug, Clone)]
pub struct MessageMetadata {
    operation_id: String,
    sequence_number: u64,
    checksum: u32,
    compression: Option<crate::distributed::config::CompressionAlgorithm>,
    encryption: bool,
}

/// Strategies for message aggregation
#[derive(Debug, Clone)]
pub enum AggregationStrategy {
    /// Combine messages by concatenation
    Concatenation,
    /// Combine messages by mathematical operation
    Mathematical(MathematicalAggregation),
    /// Custom aggregation function
    Custom(String),
}

/// Mathematical aggregation operations
#[derive(Debug, Clone, Copy)]
pub enum MathematicalAggregation {
    Sum,
    Average,
    Maximum,
    Minimum,
    Reduction,
}

/// Timing configuration for aggregation
#[derive(Debug, Clone)]
pub struct AggregationTimingConfig {
    /// Maximum wait time before sending
    max_wait_time: Duration,
    /// Maximum message size before sending
    max_message_size: usize,
    /// Maximum number of messages to aggregate
    max_message_count: usize,
    /// Adaptive timing based on network conditions
    adaptive_timing: bool,
}

/// Compression optimizer for communication
#[derive(Debug)]
pub struct CompressionOptimizer {
    /// Performance profiles for different algorithms
    algorithm_profiles: HashMap<crate::distributed::config::CompressionAlgorithm, CompressionProfile>,
    /// Selection model
    selection_model: CompressionSelectionModel,
    /// Adaptation parameters
    adaptation_config: CompressionAdaptationConfig,
}

/// Performance profile for compression algorithm
#[derive(Debug, Clone)]
pub struct CompressionProfile {
    algorithm: crate::distributed::config::CompressionAlgorithm,
    avg_compression_ratio: f64,
    avg_compression_speed: f64,
    avg_decompression_speed: f64,
    cpu_usage: f64,
    memory_usage: usize,
    optimal_data_sizes: Vec<(usize, usize)>, // (min_size, max_size)
}

/// Model for selecting compression algorithms
#[derive(Debug)]
pub struct CompressionSelectionModel {
    /// Decision tree for algorithm selection
    decision_factors: HashMap<String, DecisionFactor>,
    /// Cost function weights
    cost_weights: CostWeights,
    /// Historical performance data
    performance_history: Vec<CompressionPerformanceRecord>,
}

/// Factor for compression decision making
#[derive(Debug, Clone)]
pub struct DecisionFactor {
    factor_name: String,
    factor_type: FactorType,
    weight: f64,
    threshold_values: Vec<f64>,
}

/// Types of decision factors
#[derive(Debug, Clone)]
pub enum FactorType {
    DataSize,
    NetworkBandwidth,
    CPULoad,
    MemoryAvailable,
    LatencyRequirement,
    DataType,
}

/// Weights for cost function
#[derive(Debug, Clone)]
pub struct CostWeights {
    compression_time_weight: f64,
    decompression_time_weight: f64,
    bandwidth_saving_weight: f64,
    cpu_usage_weight: f64,
    memory_usage_weight: f64,
}

/// Performance record for compression
#[derive(Debug, Clone)]
pub struct CompressionPerformanceRecord {
    algorithm: crate::distributed::config::CompressionAlgorithm,
    data_size: usize,
    compression_ratio: f64,
    compression_time: f64,
    decompression_time: f64,
    cpu_usage: f64,
    context: CompressionContext,
}

/// Context for compression performance
#[derive(Debug, Clone)]
pub struct CompressionContext {
    data_type: String,
    network_conditions: NetworkConditions,
    system_load: SystemLoad,
}

/// Network conditions
#[derive(Debug, Clone)]
pub struct NetworkConditions {
    available_bandwidth: f64,
    current_latency: f64,
    packet_loss_rate: f64,
    congestion_level: f64,
}

/// System load information
#[derive(Debug, Clone)]
pub struct SystemLoad {
    cpu_utilization: f64,
    memory_utilization: f64,
    disk_io_load: f64,
    network_io_load: f64,
}

/// Configuration for compression adaptation
#[derive(Debug, Clone)]
pub struct CompressionAdaptationConfig {
    /// Enable adaptive compression
    adaptive: bool,
    /// Minimum performance improvement to change algorithm
    min_improvement_threshold: f64,
    /// Frequency of adaptation decisions
    adaptation_frequency: Duration,
    /// Learning rate for adaptation
    learning_rate: f64,
}

/// Performance predictor for distributed operations
#[derive(Debug)]
pub struct PerformancePredictor {
    /// Operation performance models
    operation_models: HashMap<String, OperationPerformanceModel>,
    /// System performance baseline
    system_baseline: SystemPerformanceBaseline,
    /// Prediction cache
    prediction_cache: HashMap<PredictionKey, PerformancePrediction>,
}

/// Model for predicting operation performance
#[derive(Debug)]
pub struct OperationPerformanceModel {
    operation_type: String,
    complexity_model: ComplexityModel,
    scaling_model: ScalingModel,
    resource_model: ResourceModel,
    historical_data: Vec<OperationPerformanceData>,
}

/// Complexity model for operations
#[derive(Debug, Clone)]
pub enum ComplexityModel {
    Linear(f64),
    Quadratic(f64, f64),
    Cubic(f64, f64, f64),
    Logarithmic(f64, f64),
    Exponential(f64, f64),
    Custom(String),
}

/// Scaling model for distributed operations
#[derive(Debug, Clone)]
pub struct ScalingModel {
    ideal_speedup: f64,
    communication_overhead: f64,
    load_balancing_efficiency: f64,
    amdahl_serial_fraction: f64,
}

/// Resource model for performance prediction
#[derive(Debug, Clone)]
pub struct ResourceModel {
    cpu_requirement: f64,
    memory_requirement: f64,
    network_requirement: f64,
    disk_requirement: f64,
    gpu_requirement: Option<f64>,
}

/// Historical performance data
#[derive(Debug, Clone)]
pub struct OperationPerformanceData {
    operation_id: String,
    problem_size: usize,
    num_nodes: usize,
    execution_time: f64,
    resource_usage: ResourceUsage,
    system_state: SystemState,
}

/// Resource usage during operation
#[derive(Debug, Clone)]
pub struct ResourceUsage {
    cpu_time: f64,
    memory_peak: usize,
    network_bytes: usize,
    disk_bytes: usize,
    gpu_time: Option<f64>,
}

/// System state during operation
#[derive(Debug, Clone)]
pub struct SystemState {
    load_average: f64,
    memory_available: usize,
    network_utilization: f64,
    disk_utilization: f64,
    temperature: Option<f64>,
}

/// System performance baseline
#[derive(Debug, Clone)]
pub struct SystemPerformanceBaseline {
    cpu_benchmark_score: f64,
    memory_bandwidth: f64,
    network_bandwidth: f64,
    disk_bandwidth: f64,
    gpu_benchmark_score: Option<f64>,
    last_updated: Instant,
}

/// Key for performance prediction cache
#[derive(Debug, Clone, PartialEq, Eq, Hash)]
pub struct PredictionKey {
    operation_type: String,
    problem_size: usize,
    num_nodes: usize,
    system_hash: u64,
}

/// Performance prediction result
#[derive(Debug, Clone)]
pub struct PerformancePrediction {
    predicted_time: f64,
    confidence_interval: (f64, f64),
    resource_requirements: ResourceModel,
    bottleneck_analysis: BottleneckAnalysis,
    recommendation: PerformanceRecommendation,
}

/// Analysis of potential bottlenecks
#[derive(Debug, Clone)]
pub struct BottleneckAnalysis {
    primary_bottleneck: BottleneckType,
    bottleneck_severity: f64,
    mitigation_strategies: Vec<MitigationStrategy>,
}

/// Types of performance bottlenecks
#[derive(Debug, Clone, Copy)]
pub enum BottleneckType {
    CPU,
    Memory,
    Network,
    Disk,
    GPU,
    LoadImbalance,
    Communication,
}

/// Strategies for mitigating bottlenecks
#[derive(Debug, Clone)]
pub struct MitigationStrategy {
    strategy_type: MitigationStrategyType,
    expected_improvement: f64,
    implementation_cost: f64,
    description: String,
}

/// Types of mitigation strategies
#[derive(Debug, Clone, Copy)]
pub enum MitigationStrategyType {
    IncreaseNodes,
    OptimizeAlgorithm,
    ImproveLoadBalancing,
    ReduceCommunication,
    CacheOptimization,
    CompressionOptimization,
    NetworkOptimization,
}

/// Performance optimization recommendations
#[derive(Debug, Clone)]
pub struct PerformanceRecommendation {
    optimal_node_count: usize,
    recommended_blocksize: usize,
    suggested_distribution: crate::distributed::DistributionStrategy,
    compression_recommendation: Option<crate::distributed::config::CompressionAlgorithm>,
    priority_adjustments: Vec<PriorityAdjustment>,
}

/// Priority adjustment recommendation
#[derive(Debug, Clone)]
pub struct PriorityAdjustment {
    component: String,
    current_priority: f64,
    recommended_priority: f64,
    rationale: String,
}

/// Distributed resource manager
#[derive(Debug)]
pub struct DistributedResourceManager {
    /// Resource pools across nodes
    resource_pools: HashMap<usize, NodeResourcePool>,
    /// Resource allocation strategies
    allocation_strategies: HashMap<String, AllocationStrategy>,
    /// Resource monitoring
    resource_monitor: ResourceMonitor,
    /// Capacity planning
    capacity_planner: CapacityPlanner,
}

/// Resource pool for a node
#[derive(Debug, Clone)]
pub struct NodeResourcePool {
    node_id: usize,
    available_resources: AvailableResources,
    reserved_resources: ReservedResources,
    resource_limits: ResourceLimits,
    usage_history: Vec<ResourceUsageSnapshot>,
}

/// Available resources on a node
#[derive(Debug, Clone)]
pub struct AvailableResources {
    cpu_cores: f64,
    memory_bytes: usize,
    disk_bytes: usize,
    network_bandwidth: f64,
    gpu_devices: Vec<GpuResource>,
    special_resources: HashMap<String, f64>,
}

/// GPU resource information
#[derive(Debug, Clone)]
pub struct GpuResource {
    device_id: usize,
    memory_bytes: usize,
    compute_capability: String,
    utilization: f64,
    temperature: Option<f64>,
}

/// Reserved resources
#[derive(Debug, Clone)]
pub struct ReservedResources {
    cpu_cores: f64,
    memory_bytes: usize,
    disk_bytes: usize,
    network_bandwidth: f64,
    gpu_devices: Vec<usize>,
    reservations: Vec<ResourceReservation>,
}

/// Resource reservation
#[derive(Debug, Clone)]
pub struct ResourceReservation {
    reservation_id: String,
    requester: String,
    resources: HashMap<String, f64>,
    start_time: Instant,
    duration: Duration,
    priority: ReservationPriority,
}

/// Priority for resource reservations
#[derive(Debug, Clone, Copy, PartialEq, Eq, PartialOrd, Ord)]
pub enum ReservationPriority {
    Background,
    Normal,
    High,
    System,
    Emergency,
}

/// Resource limits for a node
#[derive(Debug, Clone)]
pub struct ResourceLimits {
    max_cpu_cores: f64,
    max_memory_bytes: usize,
    max_disk_bytes: usize,
    max_network_bandwidth: f64,
    max_gpu_utilization: f64,
    soft_limits: HashMap<String, f64>,
}

/// Snapshot of resource usage
#[derive(Debug, Clone)]
pub struct ResourceUsageSnapshot {
    timestamp: Instant,
    cpu_usage: f64,
    memory_usage: usize,
    disk_usage: usize,
    network_usage: f64,
    gpu_usage: HashMap<usize, f64>,
    operation_count: usize,
}

/// Strategy for resource allocation
#[derive(Debug, Clone)]
pub enum AllocationStrategy {
    FirstFit,
    BestFit,
    WorstFit,
    LoadBased,
    Performance,
    Locality,
    Custom(String),
}

impl<T> AdvancedDistributedFramework<T>
where
    T: scirs2_core::numeric::Float + Send + Sync + 'static,
{
    /// Create a new advanced distributed framework
    pub fn new() -> Self {
        Self {
            adaptive_balancer: AdaptiveLoadBalancer::new(crate::distributed::load_balancer::RebalancingConfig::default()),
            fault_manager: FaultToleranceManager::new(),
            comm_optimizer: CommunicationOptimizer::new(),
            performance_predictor: PerformancePredictor::new(),
            resource_manager: DistributedResourceManager::new(),
            topology_analyzer: NetworkTopologyAnalyzer::new(),
            _phantom: std::marker::PhantomData,
        }
    }
}

impl CommunicationOptimizer {
    fn new() -> Self {
        Self {
            topology: NetworkTopology::new(),
            bandwidth_predictor: BandwidthPredictor::new(),
            message_aggregator: MessageAggregator::new(),
            compression_optimizer: CompressionOptimizer::new(),
        }
    }
}

impl NetworkTopology {
    fn new() -> Self {
        Self {
            nodes: HashMap::new(),
            connections: HashMap::new(),
            routing_table: HashMap::new(),
        }
    }
}

impl BandwidthPredictor {
    fn new() -> Self {
        Self {
            bandwidth_history: HashMap::new(),
            prediction_models: HashMap::new(),
            current_predictions: HashMap::new(),
        }
    }
}

impl MessageAggregator {
    fn new() -> Self {
        Self {
            pending_messages: HashMap::new(),
            aggregation_strategies: HashMap::new(),
            timing_config: AggregationTimingConfig::default(),
        }
    }
}

impl CompressionOptimizer {
    fn new() -> Self {
        Self {
            algorithm_profiles: HashMap::new(),
            selection_model: CompressionSelectionModel::new(),
            adaptation_config: CompressionAdaptationConfig::default(),
        }
    }
}

impl CompressionSelectionModel {
    fn new() -> Self {
        Self {
            decision_factors: HashMap::new(),
            cost_weights: CostWeights::default(),
            performance_history: Vec::new(),
        }
    }
}

impl PerformancePredictor {
    fn new() -> Self {
        Self {
            operation_models: HashMap::new(),
            system_baseline: SystemPerformanceBaseline::default(),
            prediction_cache: HashMap::new(),
        }
    }
}

impl DistributedResourceManager {
    fn new() -> Self {
        Self {
            resource_pools: HashMap::new(),
            allocation_strategies: HashMap::new(),
            resource_monitor: ResourceMonitor::new(),
            capacity_planner: CapacityPlanner::new(Duration::from_secs(86400)), // 1 day
        }
    }
}

impl Default for AggregationTimingConfig {
    fn default() -> Self {
        Self {
            max_wait_time: Duration::from_millis(100),
            max_message_size: 1024 * 1024, // 1MB
            max_message_count: 100,
            adaptive_timing: true,
        }
    }
}

impl Default for CompressionAdaptationConfig {
    fn default() -> Self {
        Self {
            adaptive: true,
            min_improvement_threshold: 0.05,
            adaptation_frequency: Duration::from_secs(60),
            learning_rate: 0.1,
        }
    }
}

impl Default for CostWeights {
    fn default() -> Self {
        Self {
            compression_time_weight: 0.3,
            decompression_time_weight: 0.2,
            bandwidth_saving_weight: 0.4,
            cpu_usage_weight: 0.05,
            memory_usage_weight: 0.05,
        }
    }
}

impl Default for SystemPerformanceBaseline {
    fn default() -> Self {
        Self {
            cpu_benchmark_score: 1000.0,
            memory_bandwidth: 10000.0, // MB/s
            network_bandwidth: 1000.0, // Mbps
            disk_bandwidth: 500.0,     // MB/s
            gpu_benchmark_score: None,
            last_updated: Instant::now(),
        }
    }
}