use std::collections::{BTreeMap, HashMap, VecDeque};
use std::sync::{Arc, Mutex, RwLock};
use std::time::{Duration, SystemTime};

#[allow(unused_imports)]
use crate::compression::GradientCompressor;

#[derive(Debug, Clone)]
pub struct StalenessConfig {
    pub max_staleness: u32,
    pub staleness_strategy: StalenessStrategy,
    pub timeout_duration: Duration,
    pub adaptive_staleness: bool,
    pub staleness_tolerance: StalenessToleranceLevel,
    pub bounded_staleness: bool,
    pub staleness_compensation: StalenessCompensationMethod,
    pub priority_scheduling: bool,
    pub dynamic_batching: bool,
    pub gradient_accumulation: bool,
    pub staleness_aware_learning_rate: bool,
    pub version_vector_enabled: bool,
    pub consistency_model: ConsistencyModel,
}

#[derive(Debug, Clone, PartialEq)]
pub enum StalenessStrategy {
    Synchronous,
    BoundedStaleness,
    UnboundedStaleness,
    AdaptiveStaleness,
    HybridStaleness,
    ConditionalStaleness,
    PrioritizedStaleness,
    FlexibleStaleness,
}

#[derive(Debug, Clone, PartialEq)]
pub enum StalenessToleranceLevel {
    Strict,
    Moderate,
    Relaxed,
    Adaptive,
}

#[derive(Debug, Clone, PartialEq)]
pub enum StalenessCompensationMethod {
    None,
    LinearScaling,
    ExponentialDecay,
    PolynomialScaling,
    AdaptiveScaling,
    TrustRegionScaling,
    MomentumAdjustment,
    LearningRateAdjustment,
}

#[derive(Debug, Clone, PartialEq)]
pub enum ConsistencyModel {
    StrongConsistency,
    EventualConsistency,
    BoundedStaleness,
    SessionConsistency,
    MonotonicReadConsistency,
    MonotonicWriteConsistency,
    ReadYourWrites,
    WeakConsistency,
}

#[derive(Debug, Clone)]
pub struct StalenessAwareGradient {
    pub gradient: HashMap<String, Vec<f32>>,
    pub worker_id: u32,
    pub version: u64,
    pub timestamp: SystemTime,
    pub staleness: u32,
    pub priority: GradientPriority,
    pub computation_time: Duration,
    pub communication_delay: Duration,
    pub quality_score: f64,
    pub trust_score: f64,
    pub version_vector: VersionVector,
}

#[derive(Debug, Clone, PartialEq, Eq, PartialOrd, Ord, Hash)]
pub enum GradientPriority {
    Low,
    Normal,
    High,
    Critical,
    Urgent,
}

#[derive(Debug, Clone)]
pub struct VersionVector {
    pub worker_versions: HashMap<u32, u64>,
    pub global_version: u64,
    pub causal_dependencies: Vec<CausalDependency>,
}

#[derive(Debug, Clone)]
pub struct CausalDependency {
    pub source_worker: u32,
    pub target_worker: u32,
    pub dependency_version: u64,
    pub dependency_type: DependencyType,
}

#[derive(Debug, Clone, PartialEq)]
pub enum DependencyType {
    DataDependency,
    ControlDependency,
    ModelDependency,
    ParameterDependency,
}

#[allow(dead_code)]
#[derive(Debug)]
pub struct StalenessManager {
    config: StalenessConfig,
    pending_gradients: Arc<Mutex<BTreeMap<u64, StalenessAwareGradient>>>,
    applied_gradients: Arc<Mutex<VecDeque<AppliedGradient>>>,
    worker_states: Arc<RwLock<HashMap<u32, WorkerState>>>,
    global_version: Arc<Mutex<u64>>,
    staleness_metrics: Arc<Mutex<StalenessMetrics>>,
    scheduler: Arc<Mutex<StalenessScheduler>>,
    compensator: Arc<Mutex<StalenessCompensator>>,
    consistency_manager: Arc<Mutex<ConsistencyManager>>,
    adaptive_controller: Arc<Mutex<AdaptiveStalenessController>>,
    version_manager: Arc<Mutex<VersionManager>>,
}

#[derive(Debug, Clone)]
pub struct AppliedGradient {
    pub gradient_id: u64,
    pub worker_id: u32,
    pub version: u64,
    pub staleness: u32,
    pub application_time: SystemTime,
    pub compensation_factor: f64,
    pub impact_score: f64,
}

#[derive(Debug, Clone)]
pub struct WorkerState {
    pub worker_id: u32,
    pub last_update_version: u64,
    pub last_seen_time: SystemTime,
    pub average_staleness: f64,
    pub staleness_variance: f64,
    pub communication_latency: Duration,
    pub computation_speed: f64,
    pub reliability_score: f64,
    pub staleness_tolerance: f64,
    pub preferred_batch_size: usize,
    pub gradient_queue: VecDeque<u64>,
    pub performance_history: VecDeque<PerformanceSnapshot>,
}

#[derive(Debug, Clone)]
pub struct PerformanceSnapshot {
    pub timestamp: SystemTime,
    pub staleness: u32,
    pub computation_time: Duration,
    pub communication_time: Duration,
    pub gradient_quality: f64,
    pub throughput: f64,
}

#[derive(Debug, Default, Clone)]
pub struct StalenessMetrics {
    pub total_gradients_processed: u64,
    pub total_staleness_encountered: u64,
    pub average_staleness: f64,
    pub max_staleness_observed: u32,
    pub staleness_violations: u64,
    pub compensation_adjustments: u64,
    pub synchronization_delays: Duration,
    pub throughput_impact: f64,
    pub convergence_impact: f64,
    pub staleness_distribution: HashMap<u32, u64>,
    pub worker_staleness_profile: HashMap<u32, WorkerStalenessProfile>,
}

#[derive(Debug, Clone)]
pub struct WorkerStalenessProfile {
    pub worker_id: u32,
    pub average_staleness: f64,
    pub staleness_variance: f64,
    pub max_staleness: u32,
    pub staleness_trend: StalenessTrend,
    pub impact_on_convergence: f64,
}

#[derive(Debug, Clone, PartialEq)]
pub enum StalenessTrend {
    Increasing,
    Decreasing,
    Stable,
    Oscillating,
    Unknown,
}

#[allow(dead_code)]
#[derive(Debug)]
pub struct StalenessScheduler {
    strategy: StalenessStrategy,
    scheduling_queue: BTreeMap<SchedulingKey, StalenessAwareGradient>,
    batch_manager: BatchManager,
    priority_manager: PriorityManager,
    deadline_manager: DeadlineManager,
}

#[derive(Debug, Clone, PartialEq, Eq, PartialOrd, Ord)]
pub struct SchedulingKey {
    pub priority: GradientPriority,
    pub staleness: u32,
    pub timestamp: SystemTime,
    pub version: u64,
}

#[derive(Debug)]
pub struct BatchManager {
    pub current_batch: Vec<StalenessAwareGradient>,
    pub batch_size: usize,
    pub batch_timeout: Duration,
    pub batch_start_time: Option<SystemTime>,
    pub adaptive_batching: bool,
}

#[derive(Debug)]
pub struct PriorityManager {
    pub priority_queues: HashMap<GradientPriority, VecDeque<StalenessAwareGradient>>,
    pub priority_weights: HashMap<GradientPriority, f64>,
    pub dynamic_priorities: bool,
}

#[derive(Debug)]
pub struct DeadlineManager {
    pub gradient_deadlines: HashMap<u64, SystemTime>,
    pub deadline_violations: u64,
    pub deadline_extensions: HashMap<u64, u32>,
}

#[allow(dead_code)]
#[derive(Debug)]
pub struct StalenessCompensator {
    method: StalenessCompensationMethod,
    compensation_factors: HashMap<u32, f64>,
    learning_rate_adjustments: HashMap<u32, f64>,
    momentum_adjustments: HashMap<u32, f64>,
    trust_scores: HashMap<u32, f64>,
    adaptive_parameters: AdaptiveCompensationParameters,
}

#[derive(Debug)]
pub struct AdaptiveCompensationParameters {
    pub base_compensation_rate: f64,
    pub staleness_sensitivity: f64,
    pub adaptation_rate: f64,
    pub minimum_compensation: f64,
    pub maximum_compensation: f64,
    pub compensation_decay: f64,
}

#[allow(dead_code)]
#[derive(Debug)]
pub struct ConsistencyManager {
    model: ConsistencyModel,
    consistency_state: ConsistencyState,
    read_consistency_guarantees: HashMap<u32, ReadConsistencyLevel>,
    write_consistency_guarantees: HashMap<u32, WriteConsistencyLevel>,
}

#[derive(Debug)]
pub struct ConsistencyState {
    pub last_consistent_version: u64,
    pub pending_writes: HashMap<u64, PendingWrite>,
    pub read_timestamps: HashMap<u32, SystemTime>,
    pub write_timestamps: HashMap<u32, SystemTime>,
    pub causal_order: Vec<CausalEvent>,
}

#[derive(Debug, Clone)]
pub struct PendingWrite {
    pub version: u64,
    pub worker_id: u32,
    pub gradient_data: HashMap<String, Vec<f32>>,
    pub dependencies: Vec<u64>,
    pub timestamp: SystemTime,
}

#[derive(Debug, Clone)]
pub struct CausalEvent {
    pub event_id: u64,
    pub worker_id: u32,
    pub timestamp: SystemTime,
    pub event_type: EventType,
    pub dependencies: Vec<u64>,
}

#[derive(Debug, Clone, PartialEq)]
pub enum EventType {
    GradientComputation,
    ParameterUpdate,
    Synchronization,
    Communication,
}

#[derive(Debug, Clone, PartialEq)]
pub enum ReadConsistencyLevel {
    Strong,
    Bounded(Duration),
    Eventual,
    Session,
    MonotonicRead,
}

#[derive(Debug, Clone, PartialEq)]
pub enum WriteConsistencyLevel {
    Strong,
    Bounded(Duration),
    Eventual,
    MonotonicWrite,
    ReadYourWrites,
}

#[allow(dead_code)]
#[derive(Debug)]
pub struct AdaptiveStalenessController {
    current_max_staleness: u32,
    staleness_adaptation_rate: f64,
    performance_feedback: VecDeque<PerformanceFeedback>,
    adaptation_strategy: AdaptationStrategy,
    convergence_monitor: ConvergenceMonitor,
}

#[derive(Debug, Clone)]
pub struct PerformanceFeedback {
    pub timestamp: SystemTime,
    pub staleness_level: u32,
    pub throughput: f64,
    pub convergence_rate: f64,
    pub gradient_quality: f64,
    pub system_load: f64,
}

#[derive(Debug, Clone, PartialEq)]
pub enum AdaptationStrategy {
    GradientDescent,
    BinarySearch,
    ExponentialBackoff,
    LinearAdaptation,
    ProportionalControl,
    PIDControl,
    ReinforcementLearning,
}

#[derive(Debug)]
pub struct ConvergenceMonitor {
    pub loss_history: VecDeque<f64>,
    pub gradient_norm_history: VecDeque<f64>,
    pub convergence_rate: f64,
    pub staleness_impact: f64,
    pub convergence_threshold: f64,
}

#[derive(Debug)]
pub struct VersionManager {
    pub global_version_vector: VersionVector,
    pub worker_version_vectors: HashMap<u32, VersionVector>,
    pub causal_ordering: Vec<CausalEvent>,
    pub conflict_detection: ConflictDetector,
    pub version_history: VecDeque<VersionSnapshot>,
}

#[derive(Debug)]
pub struct ConflictDetector {
    pub concurrent_updates: HashMap<String, Vec<ConcurrentUpdate>>,
    pub conflict_resolution_strategy: ConflictResolutionStrategy,
    pub conflict_history: VecDeque<ConflictEvent>,
}

#[derive(Debug, Clone)]
pub struct ConcurrentUpdate {
    pub worker_id: u32,
    pub parameter_name: String,
    pub old_value: Vec<f32>,
    pub new_value: Vec<f32>,
    pub timestamp: SystemTime,
    pub version: u64,
}

#[derive(Debug, Clone, PartialEq)]
pub enum ConflictResolutionStrategy {
    LastWriterWins,
    FirstWriterWins,
    Merge,
    Rollback,
    Manual,
    VectorClock,
}

#[derive(Debug, Clone)]
pub struct ConflictEvent {
    pub conflict_id: u64,
    pub conflicting_workers: Vec<u32>,
    pub parameter_name: String,
    pub resolution_method: ConflictResolutionStrategy,
    pub timestamp: SystemTime,
}

#[derive(Debug, Clone)]
pub struct VersionSnapshot {
    pub version: u64,
    pub timestamp: SystemTime,
    pub active_workers: Vec<u32>,
    pub staleness_distribution: HashMap<u32, u32>,
}

impl Default for StalenessConfig {
    fn default() -> Self {
        Self {
            max_staleness: 10,
            staleness_strategy: StalenessStrategy::BoundedStaleness,
            timeout_duration: Duration::from_secs(30),
            adaptive_staleness: true,
            staleness_tolerance: StalenessToleranceLevel::Moderate,
            bounded_staleness: true,
            staleness_compensation: StalenessCompensationMethod::AdaptiveScaling,
            priority_scheduling: true,
            dynamic_batching: true,
            gradient_accumulation: true,
            staleness_aware_learning_rate: true,
            version_vector_enabled: true,
            consistency_model: ConsistencyModel::BoundedStaleness,
        }
    }
}

impl StalenessAwareGradient {
    pub fn new(
        gradient: HashMap<String, Vec<f32>>,
        worker_id: u32,
        version: u64,
        global_version: u64,
    ) -> Self {
        let staleness = if version <= global_version {
            (global_version - version) as u32
        } else {
            0
        };

        Self {
            gradient,
            worker_id,
            version,
            timestamp: SystemTime::now(),
            staleness,
            priority: GradientPriority::Normal,
            computation_time: Duration::from_millis(100),
            communication_delay: Duration::from_millis(50),
            quality_score: 1.0,
            trust_score: 1.0,
            version_vector: VersionVector {
                worker_versions: HashMap::new(),
                global_version,
                causal_dependencies: Vec::new(),
            },
        }
    }

    pub fn compute_staleness(&mut self, current_global_version: u64) {
        self.staleness = if self.version <= current_global_version {
            (current_global_version - self.version) as u32
        } else {
            0
        };
    }

    pub fn is_stale(&self, max_staleness: u32) -> bool {
        self.staleness > max_staleness
    }

    pub fn compute_priority(&mut self, staleness_tolerance: StalenessToleranceLevel) {
        self.priority = match staleness_tolerance {
            StalenessToleranceLevel::Strict => {
                if self.staleness == 0 {
                    GradientPriority::High
                } else {
                    GradientPriority::Low
                }
            }
            StalenessToleranceLevel::Moderate => match self.staleness {
                0..=2 => GradientPriority::High,
                3..=5 => GradientPriority::Normal,
                _ => GradientPriority::Low,
            },
            StalenessToleranceLevel::Relaxed => match self.staleness {
                0..=5 => GradientPriority::Normal,
                6..=10 => GradientPriority::Low,
                _ => GradientPriority::Low,
            },
            StalenessToleranceLevel::Adaptive => {
                let age = self.timestamp.elapsed().unwrap_or(Duration::from_secs(0));
                let priority_score = 1.0 / (1.0 + self.staleness as f64 + age.as_secs_f64());

                if priority_score > 0.8 {
                    GradientPriority::High
                } else if priority_score > 0.5 {
                    GradientPriority::Normal
                } else {
                    GradientPriority::Low
                }
            }
        };
    }

    pub fn apply_compensation(&mut self, compensation_factor: f64) {
        for gradient_vec in self.gradient.values_mut() {
            for value in gradient_vec.iter_mut() {
                *value *= compensation_factor as f32;
            }
        }
    }

    pub fn compute_quality_score(&mut self) {
        let staleness_penalty = 1.0 / (1.0 + 0.1 * self.staleness as f64);
        let time_penalty = 1.0
            / (1.0
                + self
                    .timestamp
                    .elapsed()
                    .unwrap_or(Duration::from_secs(0))
                    .as_secs_f64()
                    * 0.01);
        let computation_penalty = 1.0 / (1.0 + self.computation_time.as_millis() as f64 * 0.001);

        self.quality_score =
            staleness_penalty * time_penalty * computation_penalty * self.trust_score;
    }
}

impl StalenessManager {
    pub fn new(config: StalenessConfig) -> Self {
        Self {
            config: config.clone(),
            pending_gradients: Arc::new(Mutex::new(BTreeMap::new())),
            applied_gradients: Arc::new(Mutex::new(VecDeque::new())),
            worker_states: Arc::new(RwLock::new(HashMap::new())),
            global_version: Arc::new(Mutex::new(0)),
            staleness_metrics: Arc::new(Mutex::new(StalenessMetrics::default())),
            scheduler: Arc::new(Mutex::new(StalenessScheduler::new(
                config.staleness_strategy.clone(),
            ))),
            compensator: Arc::new(Mutex::new(StalenessCompensator::new(
                config.staleness_compensation.clone(),
            ))),
            consistency_manager: Arc::new(Mutex::new(ConsistencyManager::new(
                config.consistency_model.clone(),
            ))),
            adaptive_controller: Arc::new(Mutex::new(AdaptiveStalenessController::new(
                config.max_staleness,
            ))),
            version_manager: Arc::new(Mutex::new(VersionManager::new())),
        }
    }

    pub fn submit_gradient(
        &self,
        mut gradient: StalenessAwareGradient,
    ) -> Result<(), StalenessError> {
        let current_global_version = *self
            .global_version
            .lock()
            .expect("lock should not be poisoned");
        gradient.compute_staleness(current_global_version);
        gradient.compute_priority(self.config.staleness_tolerance.clone());
        gradient.compute_quality_score();

        if gradient.is_stale(self.config.max_staleness)
            && !self.should_accept_stale_gradient(&gradient)
        {
            self.record_staleness_violation(&gradient);
            return Err(StalenessError::StalenessExceeded);
        }

        let gradient_id = gradient.version;

        {
            let mut pending = self
                .pending_gradients
                .lock()
                .expect("lock should not be poisoned");
            pending.insert(gradient_id, gradient.clone());
        }

        self.update_worker_state(&gradient)?;
        self.schedule_gradient_processing(gradient)?;

        Ok(())
    }

    fn should_accept_stale_gradient(&self, gradient: &StalenessAwareGradient) -> bool {
        match self.config.staleness_strategy {
            StalenessStrategy::Synchronous => gradient.staleness == 0,
            StalenessStrategy::BoundedStaleness => gradient.staleness <= self.config.max_staleness,
            StalenessStrategy::UnboundedStaleness => true,
            StalenessStrategy::AdaptiveStaleness => {
                let controller = self
                    .adaptive_controller
                    .lock()
                    .expect("lock should not be poisoned");
                gradient.staleness <= controller.current_max_staleness
            }
            StalenessStrategy::ConditionalStaleness => {
                let quality_threshold = 0.5;
                gradient.quality_score >= quality_threshold
                    || gradient.staleness <= self.config.max_staleness / 2
            }
            StalenessStrategy::PrioritizedStaleness => match gradient.priority {
                GradientPriority::Critical | GradientPriority::Urgent => true,
                GradientPriority::High => gradient.staleness <= self.config.max_staleness,
                _ => gradient.staleness <= self.config.max_staleness / 2,
            },
            _ => gradient.staleness <= self.config.max_staleness,
        }
    }

    fn record_staleness_violation(&self, gradient: &StalenessAwareGradient) {
        let mut metrics = self
            .staleness_metrics
            .lock()
            .expect("lock should not be poisoned");
        metrics.staleness_violations += 1;

        if let Some(worker_profile) = metrics
            .worker_staleness_profile
            .get_mut(&gradient.worker_id)
        {
            worker_profile.max_staleness = worker_profile.max_staleness.max(gradient.staleness);
        }
    }

    fn update_worker_state(&self, gradient: &StalenessAwareGradient) -> Result<(), StalenessError> {
        let mut workers = self
            .worker_states
            .write()
            .expect("lock should not be poisoned");

        let worker_state = workers
            .entry(gradient.worker_id)
            .or_insert_with(|| WorkerState {
                worker_id: gradient.worker_id,
                last_update_version: 0,
                last_seen_time: SystemTime::now(),
                average_staleness: 0.0,
                staleness_variance: 0.0,
                communication_latency: Duration::from_millis(100),
                computation_speed: 1.0,
                reliability_score: 1.0,
                staleness_tolerance: 1.0,
                preferred_batch_size: 1,
                gradient_queue: VecDeque::new(),
                performance_history: VecDeque::new(),
            });

        worker_state.last_update_version = gradient.version;
        worker_state.last_seen_time = gradient.timestamp;

        let alpha = 0.1;
        worker_state.average_staleness =
            (1.0 - alpha) * worker_state.average_staleness + alpha * gradient.staleness as f64;

        let variance_update = (gradient.staleness as f64 - worker_state.average_staleness).powi(2);
        worker_state.staleness_variance =
            (1.0 - alpha) * worker_state.staleness_variance + alpha * variance_update;

        worker_state.communication_latency = gradient.communication_delay;
        worker_state.reliability_score = gradient.trust_score;

        let performance_snapshot = PerformanceSnapshot {
            timestamp: gradient.timestamp,
            staleness: gradient.staleness,
            computation_time: gradient.computation_time,
            communication_time: gradient.communication_delay,
            gradient_quality: gradient.quality_score,
            throughput: 1.0 / gradient.computation_time.as_secs_f64(),
        };

        worker_state
            .performance_history
            .push_back(performance_snapshot);
        if worker_state.performance_history.len() > 100 {
            worker_state.performance_history.pop_front();
        }

        worker_state.gradient_queue.push_back(gradient.version);

        Ok(())
    }

    fn schedule_gradient_processing(
        &self,
        gradient: StalenessAwareGradient,
    ) -> Result<(), StalenessError> {
        let mut scheduler = self.scheduler.lock().expect("lock should not be poisoned");
        scheduler.schedule_gradient(gradient)?;
        Ok(())
    }

    pub fn process_gradients(&self) -> Result<Vec<StalenessAwareGradient>, StalenessError> {
        let mut scheduler = self.scheduler.lock().expect("lock should not be poisoned");
        let gradients_to_process = scheduler.get_next_batch()?;

        drop(scheduler);

        let mut processed_gradients = Vec::new();

        for mut gradient in gradients_to_process {
            let compensation_factor = self.compute_compensation_factor(&gradient)?;
            gradient.apply_compensation(compensation_factor);

            if self.config.version_vector_enabled {
                self.update_version_vector(&gradient)?;
            }

            self.apply_gradient(&gradient)?;
            processed_gradients.push(gradient);
        }

        self.update_metrics(&processed_gradients)?;

        if self.config.adaptive_staleness {
            self.adapt_staleness_parameters(&processed_gradients)?;
        }

        Ok(processed_gradients)
    }

    fn compute_compensation_factor(
        &self,
        gradient: &StalenessAwareGradient,
    ) -> Result<f64, StalenessError> {
        let compensator = self
            .compensator
            .lock()
            .expect("lock should not be poisoned");
        compensator.compute_compensation_factor(gradient)
    }

    fn update_version_vector(
        &self,
        gradient: &StalenessAwareGradient,
    ) -> Result<(), StalenessError> {
        let mut version_manager = self
            .version_manager
            .lock()
            .expect("lock should not be poisoned");
        version_manager.update_version_vector(gradient.worker_id, gradient.version)?;
        Ok(())
    }

    fn apply_gradient(&self, gradient: &StalenessAwareGradient) -> Result<(), StalenessError> {
        let applied_gradient = AppliedGradient {
            gradient_id: gradient.version,
            worker_id: gradient.worker_id,
            version: gradient.version,
            staleness: gradient.staleness,
            application_time: SystemTime::now(),
            compensation_factor: 1.0,
            impact_score: gradient.quality_score,
        };

        {
            let mut applied = self
                .applied_gradients
                .lock()
                .expect("lock should not be poisoned");
            applied.push_back(applied_gradient);

            if applied.len() > 1000 {
                applied.pop_front();
            }
        }

        {
            let mut global_version = self
                .global_version
                .lock()
                .expect("lock should not be poisoned");
            *global_version += 1;
        }

        {
            let mut pending = self
                .pending_gradients
                .lock()
                .expect("lock should not be poisoned");
            pending.remove(&gradient.version);
        }

        Ok(())
    }

    fn update_metrics(
        &self,
        processed_gradients: &[StalenessAwareGradient],
    ) -> Result<(), StalenessError> {
        let mut metrics = self
            .staleness_metrics
            .lock()
            .expect("lock should not be poisoned");

        metrics.total_gradients_processed += processed_gradients.len() as u64;

        for gradient in processed_gradients {
            metrics.total_staleness_encountered += gradient.staleness as u64;
            metrics.max_staleness_observed = metrics.max_staleness_observed.max(gradient.staleness);

            *metrics
                .staleness_distribution
                .entry(gradient.staleness)
                .or_insert(0) += 1;

            let worker_profile = metrics
                .worker_staleness_profile
                .entry(gradient.worker_id)
                .or_insert_with(|| WorkerStalenessProfile {
                    worker_id: gradient.worker_id,
                    average_staleness: 0.0,
                    staleness_variance: 0.0,
                    max_staleness: 0,
                    staleness_trend: StalenessTrend::Unknown,
                    impact_on_convergence: 0.0,
                });

            let alpha = 0.1;
            worker_profile.average_staleness = (1.0 - alpha) * worker_profile.average_staleness
                + alpha * gradient.staleness as f64;
            worker_profile.max_staleness = worker_profile.max_staleness.max(gradient.staleness);
        }

        if metrics.total_gradients_processed > 0 {
            metrics.average_staleness = metrics.total_staleness_encountered as f64
                / metrics.total_gradients_processed as f64;
        }

        Ok(())
    }

    fn adapt_staleness_parameters(
        &self,
        processed_gradients: &[StalenessAwareGradient],
    ) -> Result<(), StalenessError> {
        let mut controller = self
            .adaptive_controller
            .lock()
            .expect("lock should not be poisoned");

        let average_staleness = if !processed_gradients.is_empty() {
            processed_gradients
                .iter()
                .map(|g| g.staleness as f64)
                .sum::<f64>()
                / processed_gradients.len() as f64
        } else {
            0.0
        };

        let average_quality = if !processed_gradients.is_empty() {
            processed_gradients
                .iter()
                .map(|g| g.quality_score)
                .sum::<f64>()
                / processed_gradients.len() as f64
        } else {
            1.0
        };

        let feedback = PerformanceFeedback {
            timestamp: SystemTime::now(),
            staleness_level: average_staleness as u32,
            throughput: processed_gradients.len() as f64,
            convergence_rate: 0.95,
            gradient_quality: average_quality,
            system_load: 0.5,
        };

        controller.performance_feedback.push_back(feedback);
        if controller.performance_feedback.len() > 100 {
            controller.performance_feedback.pop_front();
        }

        controller.adapt_staleness_threshold()?;

        Ok(())
    }

    pub fn get_staleness_metrics(&self) -> StalenessMetrics {
        (*self
            .staleness_metrics
            .lock()
            .expect("lock should not be poisoned"))
        .clone()
    }

    pub fn get_worker_states(&self) -> HashMap<u32, WorkerState> {
        self.worker_states
            .read()
            .expect("lock should not be poisoned")
            .clone()
    }

    pub fn set_max_staleness(&self, max_staleness: u32) -> Result<(), StalenessError> {
        if self.config.adaptive_staleness {
            let mut controller = self
                .adaptive_controller
                .lock()
                .expect("lock should not be poisoned");
            controller.current_max_staleness = max_staleness;
        }
        Ok(())
    }

    pub fn cleanup_old_gradients(&self) -> Result<(), StalenessError> {
        let cleanup_threshold = SystemTime::now() - self.config.timeout_duration;

        {
            let mut pending = self
                .pending_gradients
                .lock()
                .expect("lock should not be poisoned");
            pending.retain(|_, gradient| gradient.timestamp >= cleanup_threshold);
        }

        {
            let mut applied = self
                .applied_gradients
                .lock()
                .expect("lock should not be poisoned");
            applied.retain(|gradient| gradient.application_time >= cleanup_threshold);
        }

        Ok(())
    }
}

impl StalenessScheduler {
    pub fn new(strategy: StalenessStrategy) -> Self {
        Self {
            strategy,
            scheduling_queue: BTreeMap::new(),
            batch_manager: BatchManager {
                current_batch: Vec::new(),
                batch_size: 32,
                batch_timeout: Duration::from_millis(100),
                batch_start_time: None,
                adaptive_batching: true,
            },
            priority_manager: PriorityManager {
                priority_queues: HashMap::new(),
                priority_weights: {
                    let mut weights = HashMap::new();
                    weights.insert(GradientPriority::Critical, 1.0);
                    weights.insert(GradientPriority::Urgent, 0.9);
                    weights.insert(GradientPriority::High, 0.7);
                    weights.insert(GradientPriority::Normal, 0.5);
                    weights.insert(GradientPriority::Low, 0.3);
                    weights
                },
                dynamic_priorities: true,
            },
            deadline_manager: DeadlineManager {
                gradient_deadlines: HashMap::new(),
                deadline_violations: 0,
                deadline_extensions: HashMap::new(),
            },
        }
    }

    pub fn schedule_gradient(
        &mut self,
        gradient: StalenessAwareGradient,
    ) -> Result<(), StalenessError> {
        match self.strategy {
            StalenessStrategy::Synchronous => {
                if gradient.staleness == 0 {
                    self.add_to_batch(gradient);
                } else {
                    return Err(StalenessError::StalenessExceeded);
                }
            }
            StalenessStrategy::BoundedStaleness => {
                let key = SchedulingKey {
                    priority: gradient.priority.clone(),
                    staleness: gradient.staleness,
                    timestamp: gradient.timestamp,
                    version: gradient.version,
                };
                self.scheduling_queue.insert(key, gradient);
            }
            StalenessStrategy::PrioritizedStaleness => {
                self.priority_manager.add_to_priority_queue(gradient);
            }
            _ => {
                self.add_to_batch(gradient);
            }
        }

        Ok(())
    }

    pub fn get_next_batch(&mut self) -> Result<Vec<StalenessAwareGradient>, StalenessError> {
        match self.strategy {
            StalenessStrategy::Synchronous => self.get_synchronous_batch(),
            StalenessStrategy::BoundedStaleness => self.get_bounded_staleness_batch(),
            StalenessStrategy::PrioritizedStaleness => self.get_prioritized_batch(),
            _ => self.get_default_batch(),
        }
    }

    fn add_to_batch(&mut self, gradient: StalenessAwareGradient) {
        if self.batch_manager.current_batch.is_empty() {
            self.batch_manager.batch_start_time = Some(SystemTime::now());
        }

        self.batch_manager.current_batch.push(gradient);
    }

    fn get_synchronous_batch(&mut self) -> Result<Vec<StalenessAwareGradient>, StalenessError> {
        if self.batch_manager.current_batch.len() >= self.batch_manager.batch_size
            || self.batch_timeout_exceeded()
        {
            let batch = std::mem::take(&mut self.batch_manager.current_batch);
            self.batch_manager.batch_start_time = None;
            Ok(batch)
        } else {
            Ok(Vec::new())
        }
    }

    fn get_bounded_staleness_batch(
        &mut self,
    ) -> Result<Vec<StalenessAwareGradient>, StalenessError> {
        let mut batch = Vec::new();
        let mut keys_to_remove = Vec::new();

        for (key, gradient) in &self.scheduling_queue {
            if batch.len() >= self.batch_manager.batch_size {
                break;
            }
            batch.push(gradient.clone());
            keys_to_remove.push(key.clone());
        }

        for key in keys_to_remove {
            self.scheduling_queue.remove(&key);
        }

        Ok(batch)
    }

    fn get_prioritized_batch(&mut self) -> Result<Vec<StalenessAwareGradient>, StalenessError> {
        self.priority_manager
            .get_prioritized_batch(self.batch_manager.batch_size)
    }

    fn get_default_batch(&mut self) -> Result<Vec<StalenessAwareGradient>, StalenessError> {
        let batch = std::mem::take(&mut self.batch_manager.current_batch);
        self.batch_manager.batch_start_time = None;
        Ok(batch)
    }

    fn batch_timeout_exceeded(&self) -> bool {
        if let Some(start_time) = self.batch_manager.batch_start_time {
            start_time.elapsed().unwrap_or(Duration::from_secs(0))
                >= self.batch_manager.batch_timeout
        } else {
            false
        }
    }
}

impl PriorityManager {
    pub fn add_to_priority_queue(&mut self, gradient: StalenessAwareGradient) {
        let queue = self
            .priority_queues
            .entry(gradient.priority.clone())
            .or_insert_with(VecDeque::new);
        queue.push_back(gradient);
    }

    pub fn get_prioritized_batch(
        &mut self,
        batch_size: usize,
    ) -> Result<Vec<StalenessAwareGradient>, StalenessError> {
        let mut batch = Vec::new();

        let priorities = vec![
            GradientPriority::Critical,
            GradientPriority::Urgent,
            GradientPriority::High,
            GradientPriority::Normal,
            GradientPriority::Low,
        ];

        for priority in priorities {
            if let Some(queue) = self.priority_queues.get_mut(&priority) {
                while batch.len() < batch_size && !queue.is_empty() {
                    if let Some(gradient) = queue.pop_front() {
                        batch.push(gradient);
                    }
                }
            }
        }

        Ok(batch)
    }
}

impl StalenessCompensator {
    pub fn new(method: StalenessCompensationMethod) -> Self {
        Self {
            method,
            compensation_factors: HashMap::new(),
            learning_rate_adjustments: HashMap::new(),
            momentum_adjustments: HashMap::new(),
            trust_scores: HashMap::new(),
            adaptive_parameters: AdaptiveCompensationParameters {
                base_compensation_rate: 1.0,
                staleness_sensitivity: 0.1,
                adaptation_rate: 0.01,
                minimum_compensation: 0.1,
                maximum_compensation: 2.0,
                compensation_decay: 0.95,
            },
        }
    }

    pub fn compute_compensation_factor(
        &self,
        gradient: &StalenessAwareGradient,
    ) -> Result<f64, StalenessError> {
        match self.method {
            StalenessCompensationMethod::None => Ok(1.0),
            StalenessCompensationMethod::LinearScaling => Ok(1.0
                / (1.0
                    + self.adaptive_parameters.staleness_sensitivity * gradient.staleness as f64)),
            StalenessCompensationMethod::ExponentialDecay => Ok((-self
                .adaptive_parameters
                .staleness_sensitivity
                * gradient.staleness as f64)
                .exp()),
            StalenessCompensationMethod::PolynomialScaling => {
                let poly_factor = 1.0 + gradient.staleness as f64;
                Ok(1.0 / poly_factor.powf(self.adaptive_parameters.staleness_sensitivity))
            }
            StalenessCompensationMethod::AdaptiveScaling => {
                let base_factor = 1.0
                    / (1.0
                        + self.adaptive_parameters.staleness_sensitivity
                            * gradient.staleness as f64);
                let quality_adjustment = gradient.quality_score;
                let trust_adjustment = gradient.trust_score;

                let compensation = base_factor * quality_adjustment * trust_adjustment;
                Ok(compensation.clamp(
                    self.adaptive_parameters.minimum_compensation,
                    self.adaptive_parameters.maximum_compensation,
                ))
            }
            StalenessCompensationMethod::TrustRegionScaling => {
                let trust_factor = gradient.trust_score;
                let staleness_factor = 1.0 / (1.0 + gradient.staleness as f64 * 0.1);
                Ok(trust_factor * staleness_factor)
            }
            _ => Ok(1.0),
        }
    }
}

impl ConsistencyManager {
    pub fn new(model: ConsistencyModel) -> Self {
        Self {
            model,
            consistency_state: ConsistencyState {
                last_consistent_version: 0,
                pending_writes: HashMap::new(),
                read_timestamps: HashMap::new(),
                write_timestamps: HashMap::new(),
                causal_order: Vec::new(),
            },
            read_consistency_guarantees: HashMap::new(),
            write_consistency_guarantees: HashMap::new(),
        }
    }
}

impl AdaptiveStalenessController {
    pub fn new(initial_max_staleness: u32) -> Self {
        Self {
            current_max_staleness: initial_max_staleness,
            staleness_adaptation_rate: 0.1,
            performance_feedback: VecDeque::new(),
            adaptation_strategy: AdaptationStrategy::ProportionalControl,
            convergence_monitor: ConvergenceMonitor {
                loss_history: VecDeque::new(),
                gradient_norm_history: VecDeque::new(),
                convergence_rate: 0.0,
                staleness_impact: 0.0,
                convergence_threshold: 1e-6,
            },
        }
    }

    pub fn adapt_staleness_threshold(&mut self) -> Result<(), StalenessError> {
        if self.performance_feedback.len() < 10 {
            return Ok(());
        }

        let recent_feedback: Vec<_> = self.performance_feedback.iter().rev().take(10).collect();
        let average_throughput = recent_feedback.iter().map(|f| f.throughput).sum::<f64>()
            / recent_feedback.len() as f64;
        let average_quality = recent_feedback
            .iter()
            .map(|f| f.gradient_quality)
            .sum::<f64>()
            / recent_feedback.len() as f64;
        let average_convergence = recent_feedback
            .iter()
            .map(|f| f.convergence_rate)
            .sum::<f64>()
            / recent_feedback.len() as f64;

        let performance_score =
            0.4 * average_throughput + 0.3 * average_quality + 0.3 * average_convergence;

        match self.adaptation_strategy {
            AdaptationStrategy::ProportionalControl => {
                let error = 1.0 - performance_score;
                let adjustment = (self.staleness_adaptation_rate * error) as i32;

                if adjustment > 0 {
                    self.current_max_staleness =
                        self.current_max_staleness.saturating_add(adjustment as u32);
                } else {
                    self.current_max_staleness = self
                        .current_max_staleness
                        .saturating_sub((-adjustment) as u32);
                }

                self.current_max_staleness = self.current_max_staleness.clamp(1, 100);
            }
            AdaptationStrategy::GradientDescent => {
                let gradient = self.compute_performance_gradient(&recent_feedback);
                let _step_size = self.staleness_adaptation_rate;

                if gradient > 0.0 {
                    self.current_max_staleness = self.current_max_staleness.saturating_add(1);
                } else if gradient < 0.0 {
                    self.current_max_staleness = self.current_max_staleness.saturating_sub(1);
                }

                self.current_max_staleness = self.current_max_staleness.clamp(1, 100);
            }
            _ => {}
        }

        Ok(())
    }

    fn compute_performance_gradient(&self, feedback: &[&PerformanceFeedback]) -> f64 {
        if feedback.len() < 2 {
            return 0.0;
        }

        let latest = feedback[0];
        let previous = feedback[1];

        let throughput_change = latest.throughput - previous.throughput;
        let quality_change = latest.gradient_quality - previous.gradient_quality;
        let convergence_change = latest.convergence_rate - previous.convergence_rate;

        0.4 * throughput_change + 0.3 * quality_change + 0.3 * convergence_change
    }
}

impl VersionManager {
    pub fn new() -> Self {
        Self {
            global_version_vector: VersionVector {
                worker_versions: HashMap::new(),
                global_version: 0,
                causal_dependencies: Vec::new(),
            },
            worker_version_vectors: HashMap::new(),
            causal_ordering: Vec::new(),
            conflict_detection: ConflictDetector {
                concurrent_updates: HashMap::new(),
                conflict_resolution_strategy: ConflictResolutionStrategy::LastWriterWins,
                conflict_history: VecDeque::new(),
            },
            version_history: VecDeque::new(),
        }
    }

    pub fn update_version_vector(
        &mut self,
        worker_id: u32,
        version: u64,
    ) -> Result<(), StalenessError> {
        self.global_version_vector
            .worker_versions
            .insert(worker_id, version);
        self.global_version_vector.global_version =
            self.global_version_vector.global_version.max(version);

        let worker_vector = self
            .worker_version_vectors
            .entry(worker_id)
            .or_insert_with(|| VersionVector {
                worker_versions: HashMap::new(),
                global_version: 0,
                causal_dependencies: Vec::new(),
            });

        worker_vector.worker_versions.insert(worker_id, version);
        worker_vector.global_version = version;

        let snapshot = VersionSnapshot {
            version: self.global_version_vector.global_version,
            timestamp: SystemTime::now(),
            active_workers: self
                .global_version_vector
                .worker_versions
                .keys()
                .cloned()
                .collect(),
            staleness_distribution: HashMap::new(),
        };

        self.version_history.push_back(snapshot);
        if self.version_history.len() > 1000 {
            self.version_history.pop_front();
        }

        Ok(())
    }
}

#[derive(Debug, Clone)]
pub enum StalenessError {
    StalenessExceeded,
    InvalidConfiguration,
    WorkerNotFound,
    VersionConflict,
    ConsistencyViolation,
    SchedulingFailed,
    CompensationFailed,
    AdaptationFailed,
}

impl std::fmt::Display for StalenessError {
    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
        match self {
            StalenessError::StalenessExceeded => write!(f, "Staleness exceeded maximum threshold"),
            StalenessError::InvalidConfiguration => write!(f, "Invalid staleness configuration"),
            StalenessError::WorkerNotFound => write!(f, "Worker not found"),
            StalenessError::VersionConflict => write!(f, "Version conflict detected"),
            StalenessError::ConsistencyViolation => write!(f, "Consistency violation"),
            StalenessError::SchedulingFailed => write!(f, "Gradient scheduling failed"),
            StalenessError::CompensationFailed => write!(f, "Staleness compensation failed"),
            StalenessError::AdaptationFailed => write!(f, "Adaptive staleness control failed"),
        }
    }
}

impl std::error::Error for StalenessError {}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn test_staleness_aware_gradient_creation() {
        let mut gradient_data = HashMap::new();
        gradient_data.insert("param_1".to_string(), vec![1.0, 2.0, 3.0]);

        let gradient = StalenessAwareGradient::new(gradient_data, 1, 10, 15);
        assert_eq!(gradient.worker_id, 1);
        assert_eq!(gradient.version, 10);
        assert_eq!(gradient.staleness, 5);
    }

    #[test]
    fn test_staleness_computation() {
        let mut gradient_data = HashMap::new();
        gradient_data.insert("param_1".to_string(), vec![1.0, 2.0, 3.0]);

        let mut gradient = StalenessAwareGradient::new(gradient_data, 1, 10, 15);
        gradient.compute_staleness(20);
        assert_eq!(gradient.staleness, 10);
    }

    #[test]
    fn test_staleness_manager_creation() {
        let config = StalenessConfig::default();
        let manager = StalenessManager::new(config);
        assert_eq!(
            *manager
                .global_version
                .lock()
                .expect("lock should not be poisoned"),
            0
        );
    }

    #[test]
    fn test_gradient_submission() {
        let config = StalenessConfig::default();
        let manager = StalenessManager::new(config);

        let mut gradient_data = HashMap::new();
        gradient_data.insert("param_1".to_string(), vec![1.0, 2.0, 3.0]);

        let gradient = StalenessAwareGradient::new(gradient_data, 1, 1, 0);
        let result = manager.submit_gradient(gradient);
        assert!(result.is_ok());
    }

    #[test]
    fn test_staleness_exceeds_threshold() {
        let mut config = StalenessConfig::default();
        config.max_staleness = 5;
        let manager = StalenessManager::new(config);

        // Set the global version to a high value to make the gradient stale
        {
            let mut global_version = manager
                .global_version
                .lock()
                .expect("lock should not be poisoned");
            *global_version = 10;
        }

        let mut gradient_data = HashMap::new();
        gradient_data.insert("param_1".to_string(), vec![1.0, 2.0, 3.0]);

        // Create gradient with version 3, which will be stale (staleness = 10 - 3 = 7 > 5)
        let gradient = StalenessAwareGradient::new(gradient_data, 1, 3, 0);
        let result = manager.submit_gradient(gradient);
        assert!(result.is_err());
    }

    #[test]
    fn test_priority_computation() {
        let mut gradient_data = HashMap::new();
        gradient_data.insert("param_1".to_string(), vec![1.0, 2.0, 3.0]);

        let mut gradient = StalenessAwareGradient::new(gradient_data, 1, 10, 15);
        gradient.compute_priority(StalenessToleranceLevel::Strict);
        assert_eq!(gradient.priority, GradientPriority::Low);

        gradient.staleness = 0;
        gradient.compute_priority(StalenessToleranceLevel::Strict);
        assert_eq!(gradient.priority, GradientPriority::High);
    }

    #[test]
    fn test_staleness_scheduler() {
        let mut scheduler = StalenessScheduler::new(StalenessStrategy::BoundedStaleness);

        let mut gradient_data = HashMap::new();
        gradient_data.insert("param_1".to_string(), vec![1.0, 2.0, 3.0]);

        let gradient = StalenessAwareGradient::new(gradient_data, 1, 1, 0);
        let result = scheduler.schedule_gradient(gradient);
        assert!(result.is_ok());
    }

    #[test]
    fn test_staleness_compensation() {
        let compensator = StalenessCompensator::new(StalenessCompensationMethod::LinearScaling);

        let mut gradient_data = HashMap::new();
        gradient_data.insert("param_1".to_string(), vec![1.0, 2.0, 3.0]);

        let gradient = StalenessAwareGradient::new(gradient_data, 1, 5, 10);
        let compensation = compensator.compute_compensation_factor(&gradient);
        assert!(compensation.is_ok());
        assert!(compensation.unwrap() < 1.0);
    }

    #[test]
    fn test_adaptive_staleness_controller() {
        let mut controller = AdaptiveStalenessController::new(10);
        assert_eq!(controller.current_max_staleness, 10);

        let result = controller.adapt_staleness_threshold();
        assert!(result.is_ok());
    }

    #[test]
    fn test_version_manager() {
        let mut version_manager = VersionManager::new();
        let result = version_manager.update_version_vector(1, 5);
        assert!(result.is_ok());
        assert_eq!(version_manager.global_version_vector.global_version, 5);
    }

    #[test]
    fn test_staleness_strategies() {
        assert_eq!(
            StalenessStrategy::Synchronous,
            StalenessStrategy::Synchronous
        );
        assert_ne!(
            StalenessStrategy::Synchronous,
            StalenessStrategy::BoundedStaleness
        );
    }

    #[test]
    fn test_staleness_tolerance_levels() {
        assert_eq!(
            StalenessToleranceLevel::Strict,
            StalenessToleranceLevel::Strict
        );
        assert_ne!(
            StalenessToleranceLevel::Strict,
            StalenessToleranceLevel::Relaxed
        );
    }

    #[test]
    fn test_gradient_priorities() {
        assert!(GradientPriority::Critical > GradientPriority::High);
        assert!(GradientPriority::High > GradientPriority::Normal);
        assert!(GradientPriority::Normal > GradientPriority::Low);
    }

    #[test]
    fn test_staleness_error_display() {
        let error = StalenessError::StalenessExceeded;
        assert_eq!(format!("{}", error), "Staleness exceeded maximum threshold");

        let error = StalenessError::WorkerNotFound;
        assert_eq!(format!("{}", error), "Worker not found");
    }
}
