amberjs 1.17.0

// Performance Optimizer
// Optimizes resource usage and performance for edge computing

use serde::{Deserialize, Serialize};
use std::collections::{BTreeMap, HashMap};
use std::sync::{Arc, Mutex, RwLock};
use tokio::time::{TokioDuration, TokioInstant};
use std::time::{Duration, Instant};
use std::time::SystemTime;

/// Performance optimizer
#[derive(Debug)]
pub struct ResourceOptimizer {
    profiler: Arc<ResourceProfiler>,
    tuner: Arc<AutoTuner>,
}
/// Resource profiler
#[derive(Debug)]
pub struct ResourceProfiler {
    metrics: Arc<RwLock<ResourceMetrics>>,
}
/// Auto tuner
#[derive(Debug)]
pub struct AutoTuner {
    tuning_history: Arc<RwLock<Vec<TuningRecord>>>,
    current_config: Arc<RwLock<OptimizationConfig>>,
}
/// Optimization result
#[derive(Debug, Clone)]
pub struct OptimizationResult {
    pub improvement_percent: f64,
    pub config_changes: Vec<ConfigChange>,
    pub execution_time_ms: u64,
    pub confidence: f64,
}
/// Config change
#[derive(Debug, Clone)]
pub struct ConfigChange {
    pub parameter: String,
    pub old_value: f64,
    pub new_value: f64,
}
/// Resource profile
#[derive(Debug, Clone)]
pub struct ResourceProfile {
    pub cpu_usage_percent: f64,
    pub memory_usage_mb: u64,
    pub memory_usage_percent: f64,
    pub active_instances: u32,
    pub queue_size: u32,
    pub throughput: f64,
}
/// Resource metrics
#[derive(Debug, Clone)]
pub struct ResourceMetrics {
    pub timestamp: std::time::SystemTime,
    pub cpu_usage: f64,
    pub memory_usage: u64,
    pub disk_usage: u64,
    pub network_io: NetworkIO,
    pub active_tasks: u32,
}
/// Network I/O metrics
#[derive(Debug, Clone)]
pub struct NetworkIO {
    pub bytes_sent: u64,
    pub bytes_recv: u64,
    pub packets_sent: u64,
    pub packets_recv: u64,
}
/// Tuning record
#[derive(Debug, Clone)]
pub struct TuningRecord {
    pub timestamp: std::time::SystemTime,
    pub config: OptimizationConfig,
    pub performance_before: f64,
    pub performance_after: f64,
    pub improvement: f64,
}
/// Optimization configuration
#[derive(Debug, Clone)]
pub struct OptimizationConfig {
    pub cpu_limit: f64,
    pub memory_limit: f64,
    pub max_instances: u32,
    pub batch_size: u32,
    pub cache_size_mb: u64,
    pub optimization_level: OptimizationLevel,
}
/// Optimization level
#[derive(Debug, Clone, PartialEq)]
pub enum OptimizationLevel {
    Conservative,
    Moderate,
    Aggressive,
}
/// Battery optimizer
#[derive(Debug)]
pub struct BatteryOptimizer {
    monitor: Arc<BatteryMonitor>,
    scheduler: Arc<PowerScheduler>,
}
/// Battery monitor
#[derive(Debug)]
pub struct BatteryMonitor {
    current_level: Arc<RwLock<f64>>,
    is_charging: Arc<RwLock<bool>>,
    health_percent: Arc<RwLock<f64>>,
}
/// Power scheduler
#[derive(Debug)]
pub struct PowerScheduler {
    schedules: Arc<RwLock<Vec<PowerSchedule>>>,
}
/// Power schedule
#[derive(Debug, Clone)]
pub struct PowerSchedule {
    pub task_id: String,
    pub start_time: std::time::SystemTime,
    pub estimated_duration_ms: u64,
    pub power_consumption: f64,
    pub priority: PowerPriority,
}
/// Power priority
#[derive(Debug, Clone)]
pub enum PowerPriority {
    Low,
    Normal,
    High,
}
/// Power optimization result
#[derive(Debug, Clone)]
pub struct PowerOptimization {
    pub battery_saved_percent: f64,
    pub schedule_changes: Vec<ScheduleChange>,
    pub execution_time_ms: u64,
}
/// Schedule change
#[derive(Debug, Clone)]
pub struct ScheduleChange {
    pub task_id: String,
    pub old_schedule: PowerSchedule,
    pub new_schedule: PowerSchedule,
    pub reason: String,
}
impl ResourceOptimizer {
    /// Create a new resource optimizer
    pub async fn new() -> Result<Self> {
        let optimizer: _ = ResourceOptimizer {
            profiler: Arc::new(Mutex::new(ResourceProfiler::new()),.await?),
            tuner: Arc::new(Mutex::new(AutoTuner::new()),.await?),
        };
        println!("Resource optimizer initialized");
        Ok(optimizer)
    }
    /// Optimize resources
    pub async fn optimize_resources(&self) -> Result<OptimizationResult> {
        let start: _ = Instant::now();
        println!("Starting resource optimization...");
        // Profile current resource usage
        let profile: _ = self.profiler.profile_usage().await?;
        // Tune configuration based on profile
        let config: _ = self.tuner.tune_config(&profile).await?;
        // Apply optimization
        let changes: _ = self.apply_optimization(&config).await?;
        let elapsed: _ = start.elapsed();
        let result: _ = OptimizationResult {
            improvement_percent: 15.5, // Simulated improvement
            config_changes: changes,
            execution_time_ms: elapsed.as_millis() as u64,
            confidence: 0.85,
        };
        println!("Resource optimization completed in {}ms ({}% improvement)",
                 result.execution_time_ms, result.improvement_percent);
        Ok(result)
    }
    /// Profile resource usage
    pub async fn profile_usage(&self) -> Result<ResourceProfile> {
        let profile: _ = self.profiler.profile().await?;
        Ok(profile)
    }
    /// Apply optimization configuration
    async fn apply_optimization(&self, config: &OptimizationConfig) -> Result<Vec<ConfigChange> {
        let mut changes = Vec::new();
        // Simulate applying configuration changes
        tokio::time::sleep(Duration::from_millis(10)).await;
        changes.push(ConfigChange {
            parameter: "cpu_limit".to_string(),
            old_value: 80.0,
            new_value: config.cpu_limit,
        });
        changes.push(ConfigChange {
            parameter: "memory_limit".to_string(),
            old_value: 1024.0,
            new_value: config.memory_limit,
        });
        println!("Applied {} configuration changes", changes.len());
        Ok(changes)
    }
}
impl ResourceProfiler {
    /// Create a new resource profiler
    pub async fn new() -> Result<Self> {
        let profiler: _ = ResourceProfiler {
            metrics: Arc::new(Mutex::new(ResourceMetrics {)),
                timestamp: std::time::SystemTime::now())
                cpu_usage: 50.0,
                memory_usage: 1024,
                disk_usage: 2048,
                network_io: NetworkIO {
                    bytes_sent: 1024 * 1024,
                    bytes_recv: 2 * 1024 * 1024,
                    packets_sent: 1000,
                    packets_recv: 1500,
                },
                active_tasks: 10,
            })),
        };
        println!("Resource profiler initialized");
        Ok(profiler)
    }
    /// Profile resource usage
    pub async fn profile(&self) -> Result<ResourceProfile> {
        let metrics: _ = self.metrics.read().await;
        let profile: _ = ResourceProfile {
            cpu_usage_percent: metrics.cpu_usage,
            memory_usage_mb: metrics.memory_usage,
            memory_usage_percent: (metrics.memory_usage as f64 / 2048.0) * 100.0,
            active_instances: metrics.active_tasks,
            queue_size: metrics.active_tasks / 2,
            throughput: 100.0, // ops/sec
        };
        Ok(profile)
    }
    /// Update metrics
    pub async fn update_metrics(&self, metrics: ResourceMetrics) {
        let mut current = self.metrics.write().await;
        *current = metrics;
    }
    /// Get current metrics
    pub async fn get_metrics(&self) -> Result<ResourceMetrics> {
        let metrics: _ = self.metrics.read().await;
        Ok(metrics.clone())
    }
}
impl AutoTuner {
    /// Create a new auto tuner
    pub async fn new() -> Result<Self> {
        let tuner: _ = AutoTuner {
            tuning_history: Arc::new(Mutex::new(Vec::new()))
            current_config: Arc::new(Mutex::new(OptimizationConfig {)),
                cpu_limit: 80.0,
                memory_limit: 1024.0,
                max_instances: 100,
                batch_size: 32,
                cache_size_mb: 256,
                optimization_level: OptimizationLevel::Moderate,
            }))
        };
        println!("Auto tuner initialized");
        Ok(tuner)
    }
    /// Tune configuration based on profile
    pub async fn tune_config(&self, profile: &ResourceProfile) -> Result<OptimizationConfig> {
        let mut config = self.current_config.read().await.clone();
        // Analyze profile and adjust configuration
        if profile.cpu_usage_percent > 90.0 {
            config.cpu_limit = 85.0; // Reduce CPU limit
            config.max_instances = (config.max_instances * 9) / 10; // Reduce instances by 10%
        } else if profile.cpu_usage_percent < 50.0 {
            config.cpu_limit = 90.0; // Increase CPU limit
            config.max_instances = (config.max_instances * 11) / 10; // Increase instances by 10%
        }
        if profile.memory_usage_percent > 85.0 {
            config.memory_limit *= 0.9; // Reduce memory limit
        } else if profile.memory_usage_percent < 60.0 {
            config.memory_limit *= 1.1; // Increase memory limit
        }
        // Adjust batch size based on throughput
        if profile.throughput > 500.0 {
            config.batch_size = (config.batch_size * 11) / 10;
        } else if profile.throughput < 100.0 {
            config.batch_size = (config.batch_size * 9) / 10;
        }
        // Save tuning record
        {
            let mut history = self.tuning_history.write().await;
            history.push(TuningRecord {
                timestamp: std::time::SystemTime::now(),
                config: config.clone(),
                performance_before: 100.0,
                performance_after: 115.0,
                improvement: 15.0,
            });
            // Keep only last 100 records
            if history.len() > 100 {
                history.drain(0..history.len() - 100);
            }
        }
        // Update current config
        {
            let mut current = self.current_config.write().await;
            *current = config.clone();
        }
        println!("Tuned configuration based on profile (CPU: {:.1}%, Memory: {:.1}%, Throughput: {:.1})",
                 profile.cpu_usage_percent, profile.memory_usage_percent, profile.throughput);
        Ok(config)
    }
    /// Get tuning history
    pub async fn get_tuning_history(&self) -> Vec<TuningRecord> {
        let history: _ = self.tuning_history.read().await;
        history.clone()
    }
}
impl BatteryOptimizer {
    /// Create a new battery optimizer
    pub async fn new() -> Result<Self> {
        let optimizer: _ = BatteryOptimizer {
            monitor: Arc::new(Mutex::new(BatteryMonitor::new()),.await?),
            scheduler: Arc::new(Mutex::new(PowerScheduler::new()),.await?),
        };
        println!("Battery optimizer initialized");
        Ok(optimizer)
    }
    /// Optimize power usage
    pub async fn optimize_power(&self) -> Result<PowerOptimization> {
        let start: _ = Instant::now();
        println!("Starting power optimization...");
        // Get battery status
        let battery_status: _ = self.monitor.get_status().await?;
        // Schedule tasks based on battery level
        let schedule_changes: _ = self.scheduler.optimize_schedule(battery_status).await?;
        // Calculate battery saved
        let battery_saved: _ = self.calculate_battery_saved(&schedule_changes).await?;
        let elapsed: _ = start.elapsed();
        let result: _ = PowerOptimization {
            battery_saved_percent: battery_saved,
            schedule_changes,
            execution_time_ms: elapsed.as_millis() as u64,
        };
        println!("Power optimization completed in {}ms ({}% battery saved)",
                 result.execution_time_ms, result.battery_saved_percent);
        Ok(result)
    }
    /// Schedule tasks based on battery
    pub async fn schedule_tasks(&self, tasks: &[Task]) -> Result<Vec<PowerSchedule> {
        let schedules: _ = self.scheduler.create_schedules(tasks).await?;
        Ok(schedules)
    }
    /// Calculate battery saved
    async fn calculate_battery_saved(&self, changes: &[ScheduleChange]) -> Result<f64> {
        // Simulate battery savings calculation
        let total_saved: _ = changes.len() as f64 * 2.5; // 2.5% per change
        Ok(total_saved.min(20.0)) // Max 20% savings
    }
}
impl BatteryMonitor {
    /// Create a new battery monitor
    pub async fn new() -> Result<Self> {
        let monitor: _ = BatteryMonitor {
            current_level: Arc::new(Mutex::new(85.0)))
            is_charging: Arc::new(Mutex::new(false)))
            health_percent: Arc::new(Mutex::new(95.0)))
        };
        println!("Battery monitor initialized");
        Ok(monitor)
    }
    /// Get battery status
    pub async fn get_status(&self) -> Result<BatteryStatus> {
        let level: _ = *self.current_level.read().await;
        let is_charging: _ = *self.is_charging.read().await;
        let health: _ = *self.health_percent.read().await;
        Ok(BatteryStatus {
            level_percent: level,
            is_charging,
            health_percent: health,
            time_remaining_minutes: if is_charging { None } else { Some((level * 60.0 / 10.0) as u32) },
        })
    }
    /// Update battery level
    pub async fn update_level(&self, level: f64) {
        let mut current = self.current_level.write().await;
        *current = level;
    }
}
/// Battery status
#[derive(Debug, Clone)]
pub struct BatteryStatus {
    pub level_percent: f64,
    pub is_charging: bool,
    pub health_percent: f64,
    pub time_remaining_minutes: Option<u32>,
}
impl PowerScheduler {
    /// Create a new power scheduler
    pub async fn new() -> Result<Self> {
        let scheduler: _ = PowerScheduler {
            schedules: Arc::new(Mutex::new(Vec::new()))
        };
        println!("Power scheduler initialized");
        Ok(scheduler)
    }
    /// Create schedules for tasks
    pub async fn create_schedules(&self, tasks: &[Task]) -> Result<Vec<PowerSchedule> {
        let mut schedules = Vec::new();
        for task in tasks {
            let schedule: _ = PowerSchedule {
                task_id: task.id.clone(),
                start_time: std::time::SystemTime::now(),
                estimated_duration_ms: 1000,
                power_consumption: 5.0,
                priority: PowerPriority::Normal,
            };
            schedules.push(schedule);
        }
        // Save schedules
        {
            let mut current = self.schedules.write().await;
            *current = schedules.clone();
        }
        Ok(schedules)
    }
    /// Optimize schedule based on battery status
    pub async fn optimize_schedule(&self, battery_status: BatteryStatus) -> Result<Vec<ScheduleChange> {
        let mut changes = Vec::new();
        if battery_status.level_percent < 20.0 && !battery_status.is_charging {
            // Low battery: defer non-critical tasks
            let mut schedules = self.schedules.read().await;
            for schedule in schedules.iter() {
                if schedule.priority == PowerPriority::Low {
                    changes.push(ScheduleChange {
                        task_id: schedule.task_id.clone(),
                        old_schedule: schedule.clone(),
                        new_schedule: PowerSchedule {
                            task_id: schedule.task_id.clone(),
                            start_time: std::time::SystemTime::now(),
                            estimated_duration_ms: schedule.estimated_duration_ms,
                            power_consumption: schedule.power_consumption * 0.7, // Reduce power
                            priority: PowerPriority::Low,
                        },
                        reason: "Low battery - reduced power mode".to_string(),
                    });
                }
            }
        }
        println!("Optimized {} task schedules", changes.len());
        Ok(changes)
    }
}