oxirs_stream/

wasm_edge_computing.rs

//! # WebAssembly Edge Computing Module
//!
//! Ultra-low latency edge processing using WebAssembly with hot-swappable plugins,
//! distributed execution, and advanced resource management for next-generation streaming.

use anyhow::{anyhow, Result};
use chrono::{DateTime, Utc};
use serde::{Deserialize, Serialize};
use std::collections::HashMap;
use std::sync::Arc;
use tokio::sync::{RwLock, Semaphore};
use tracing::{debug, info, warn};

#[cfg(feature = "wasm")]
use wasmtime::{Engine, Instance, Module, Store, TypedFunc};

use crate::event::StreamEvent;

/// WASM edge processor configuration
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct WasmEdgeConfig {
    pub optimization_level: OptimizationLevel,
    pub resource_limits: WasmResourceLimits,
    pub enable_caching: bool,
    pub enable_jit: bool,
    pub security_sandbox: bool,
    pub allowed_imports: Vec<String>,
    // Optional legacy fields for backward compatibility
    #[serde(default)]
    pub max_concurrent_instances: usize,
    #[serde(default)]
    pub memory_limit_mb: u64,
    #[serde(default)]
    pub execution_timeout_ms: u64,
    #[serde(default)]
    pub enable_hot_reload: bool,
    #[serde(default)]
    pub edge_locations: Vec<EdgeLocation>,
}

/// WASM resource limits
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct WasmResourceLimits {
    pub max_memory_bytes: u64,
    pub max_execution_time_ms: u64,
    pub max_stack_size_bytes: u64,
    pub max_table_elements: u32,
    pub enable_simd: bool,
    pub enable_threads: bool,
    // Legacy fields
    #[serde(default)]
    pub max_memory_pages: u32,
    #[serde(default)]
    pub max_instances: u32,
    #[serde(default)]
    pub max_tables: u32,
    #[serde(default)]
    pub max_memories: u32,
    #[serde(default)]
    pub max_globals: u32,
    #[serde(default)]
    pub max_functions: u32,
    #[serde(default)]
    pub max_imports: u32,
    #[serde(default)]
    pub max_exports: u32,
}

/// Edge computing location
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct EdgeLocation {
    pub id: String,
    pub region: String,
    pub latency_ms: f64,
    pub capacity_factor: f64,
    pub available_resources: ResourceMetrics,
    pub specializations: Vec<ProcessingSpecialization>,
}

/// Processing specializations for edge nodes
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum ProcessingSpecialization {
    RdfProcessing,
    SparqlOptimization,
    GraphAnalytics,
    MachineLearning,
    Cryptography,
    ComputerVision,
    NaturalLanguage,
    QuantumSimulation,
}

/// WASM optimization levels
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum OptimizationLevel {
    Debug,
    Release,
    Maximum,
    Adaptive,
}

/// Resource usage metrics
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ResourceMetrics {
    pub cpu_cores: u32,
    pub memory_mb: u64,
    pub storage_gb: u64,
    pub network_mbps: f64,
    pub gpu_units: u32,
    pub quantum_qubits: u32,
}

/// WASM plugin metadata
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct WasmPlugin {
    pub id: String,
    pub name: String,
    pub version: String,
    pub description: String,
    pub author: String,
    pub capabilities: Vec<PluginCapability>,
    pub wasm_bytes: Vec<u8>,
    pub schema: PluginSchema,
    pub performance_profile: PerformanceProfile,
    pub security_level: SecurityLevel,
    pub created_at: DateTime<Utc>,
    pub updated_at: DateTime<Utc>,
}

/// Plugin capabilities
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum PluginCapability {
    EventProcessing,
    DataTransformation,
    Filtering,
    Aggregation,
    Enrichment,
    Validation,
    Compression,
    Encryption,
    Analytics,
    MachineLearning,
}

/// Plugin input/output schema
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct PluginSchema {
    pub input_types: Vec<String>,
    pub output_types: Vec<String>,
    pub configuration_schema: serde_json::Value,
    pub required_imports: Vec<String>,
    pub exported_functions: Vec<String>,
}

impl Default for PluginSchema {
    fn default() -> Self {
        Self {
            input_types: vec!["StreamEvent".to_string()],
            output_types: vec!["StreamEvent".to_string()],
            configuration_schema: serde_json::json!({}),
            required_imports: vec![],
            exported_functions: vec!["process_events".to_string()],
        }
    }
}

/// Performance characteristics
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct PerformanceProfile {
    pub average_execution_time_us: u64,
    pub memory_usage_mb: f64,
    pub cpu_intensity: f64,
    pub throughput_events_per_second: u64,
    pub scalability_factor: f64,
}

impl Default for PerformanceProfile {
    fn default() -> Self {
        Self {
            average_execution_time_us: 100,
            memory_usage_mb: 1.0,
            cpu_intensity: 0.5,
            throughput_events_per_second: 1000,
            scalability_factor: 1.0,
        }
    }
}

/// Security levels for plugins
#[derive(Debug, Clone, Serialize, Deserialize, PartialEq, Eq, Hash)]
pub enum SecurityLevel {
    Untrusted,
    BasicSandbox,
    Standard,
    Enhanced,
    TrustedVerified,
    CriticalSecurity,
    High,
}

/// WASM execution context
pub struct WasmExecutionContext {
    #[cfg(feature = "wasm")]
    pub engine: Engine,
    #[cfg(feature = "wasm")]
    pub store: Store<WasmState>,
    #[cfg(feature = "wasm")]
    pub instance: Instance,
    pub plugin_id: String,
    pub execution_count: u64,
    pub total_execution_time_us: u64,
    pub last_execution: DateTime<Utc>,
    pub resource_usage: ResourceMetrics,
}

impl std::fmt::Debug for WasmExecutionContext {
    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
        f.debug_struct("WasmExecutionContext")
            .field("plugin_id", &self.plugin_id)
            .field("execution_count", &self.execution_count)
            .field("total_execution_time_us", &self.total_execution_time_us)
            .field("last_execution", &self.last_execution)
            .field("resource_usage", &self.resource_usage)
            .finish_non_exhaustive()
    }
}

/// WASM execution state
#[derive(Debug, Default)]
pub struct WasmState {
    pub event_count: u64,
    pub memory_allocations: u64,
    pub external_calls: u64,
    pub start_time: Option<DateTime<Utc>>,
}

/// Edge execution result
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct EdgeExecutionResult {
    pub plugin_id: String,
    pub execution_id: String,
    pub input_events: Vec<StreamEvent>,
    pub output_events: Vec<StreamEvent>,
    pub execution_time_us: u64,
    pub memory_used_mb: f64,
    pub edge_location: String,
    pub success: bool,
    pub error_message: Option<String>,
    pub metadata: HashMap<String, serde_json::Value>,
}

/// WASM processing result for single event processing
#[derive(Debug, Clone)]
pub struct WasmProcessingResult {
    pub output: Option<StreamEvent>,
    pub latency_ms: f64,
}

/// WASM processor statistics
#[derive(Debug, Clone)]
pub struct WasmProcessorStats {
    pub total_processed: u64,
    pub average_latency_ms: f64,
    pub active_plugins: usize,
}

/// Advanced WASM edge computing processor
pub struct WasmEdgeProcessor {
    config: WasmEdgeConfig,
    plugins: RwLock<HashMap<String, WasmPlugin>>,
    execution_contexts: RwLock<HashMap<String, Arc<RwLock<WasmExecutionContext>>>>,
    execution_semaphore: Semaphore,
    edge_registry: RwLock<HashMap<String, EdgeLocation>>,
    plugin_registry: RwLock<HashMap<String, WasmPlugin>>,
    performance_metrics: RwLock<HashMap<String, PerformanceMetrics>>,
    security_manager: SecurityManager,
    #[cfg(feature = "wasm")]
    wasm_engine: Engine,
}

/// Performance tracking for plugins
#[derive(Debug, Clone)]
pub struct PerformanceMetrics {
    pub total_executions: u64,
    pub total_execution_time_us: u64,
    pub average_execution_time_us: f64,
    pub max_execution_time_us: u64,
    pub min_execution_time_us: u64,
    pub success_rate: f64,
    pub throughput_events_per_second: f64,
    pub memory_efficiency: f64,
    pub last_updated: DateTime<Utc>,
}

/// Security manager for WASM execution
#[derive(Debug)]
pub struct SecurityManager {
    trusted_plugins: RwLock<HashMap<String, SecurityLevel>>,
    execution_policies: RwLock<HashMap<SecurityLevel, ExecutionPolicy>>,
    audit_log: RwLock<Vec<SecurityAuditEntry>>,
}

/// Execution policies based on security level
#[derive(Debug, Clone)]
pub struct ExecutionPolicy {
    pub max_memory_pages: u32,
    pub max_execution_time_ms: u64,
    pub allowed_imports: Vec<String>,
    pub network_access: bool,
    pub file_system_access: bool,
    pub crypto_operations: bool,
    pub inter_plugin_communication: bool,
}

/// Security audit entry
#[derive(Debug, Clone)]
pub struct SecurityAuditEntry {
    pub timestamp: DateTime<Utc>,
    pub plugin_id: String,
    pub action: String,
    pub risk_level: RiskLevel,
    pub details: String,
}

/// Risk assessment levels
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum RiskLevel {
    Low,
    Medium,
    High,
    Critical,
}

impl WasmEdgeProcessor {
    /// Create new WASM edge processor
    pub fn new(config: WasmEdgeConfig) -> Result<Self> {
        #[cfg(feature = "wasm")]
        let wasm_engine = {
            let mut wasm_config = wasmtime::Config::new();
            wasm_config.debug_info(true);
            wasm_config.wasm_simd(true);
            wasm_config.wasm_bulk_memory(true);
            wasm_config.wasm_reference_types(true);
            wasm_config.wasm_multi_value(true);
            wasm_config.cranelift_opt_level(wasmtime::OptLevel::Speed);
            Engine::new(&wasm_config)?
        };

        #[cfg(not(feature = "wasm"))]
        let _wasm_engine = ();

        let execution_semaphore = Semaphore::new(config.max_concurrent_instances);
        let security_manager = SecurityManager::new();

        Ok(Self {
            config,
            plugins: RwLock::new(HashMap::new()),
            execution_contexts: RwLock::new(HashMap::new()),
            execution_semaphore,
            edge_registry: RwLock::new(HashMap::new()),
            plugin_registry: RwLock::new(HashMap::new()),
            performance_metrics: RwLock::new(HashMap::new()),
            security_manager,
            #[cfg(feature = "wasm")]
            wasm_engine,
        })
    }

    /// Register a WASM plugin
    pub async fn register_plugin(&self, plugin: WasmPlugin) -> Result<()> {
        // Security validation
        self.security_manager.validate_plugin(&plugin).await?;

        let plugin_id = plugin.id.clone();

        #[cfg(feature = "wasm")]
        {
            // Compile and validate WASM module
            let module = Module::new(&self.wasm_engine, &plugin.wasm_bytes)
                .map_err(|e| anyhow!("Failed to compile WASM module: {}", e))?;

            // Create execution context
            let mut store = Store::new(&self.wasm_engine, WasmState::default());
            let instance = Instance::new(&mut store, &module, &[])
                .map_err(|e| anyhow!("Failed to instantiate WASM module: {}", e))?;

            let context = WasmExecutionContext {
                engine: self.wasm_engine.clone(),
                store,
                instance,
                plugin_id: plugin_id.clone(),
                execution_count: 0,
                total_execution_time_us: 0,
                last_execution: Utc::now(),
                resource_usage: ResourceMetrics::default(),
            };

            self.execution_contexts
                .write()
                .await
                .insert(plugin_id.clone(), Arc::new(RwLock::new(context)));
        }

        // Register plugin
        self.plugins
            .write()
            .await
            .insert(plugin_id.clone(), plugin.clone());
        self.plugin_registry
            .write()
            .await
            .insert(plugin_id.clone(), plugin);

        // Initialize performance metrics
        self.performance_metrics
            .write()
            .await
            .insert(plugin_id.clone(), PerformanceMetrics::new());

        info!("Registered WASM plugin: {}", plugin_id);
        Ok(())
    }

    /// Execute plugin on edge location
    pub async fn execute_plugin(
        &self,
        plugin_id: &str,
        events: Vec<StreamEvent>,
        edge_location: Option<String>,
    ) -> Result<EdgeExecutionResult> {
        let _permit = self
            .execution_semaphore
            .acquire()
            .await
            .map_err(|_| anyhow!("Failed to acquire execution permit"))?;

        let start_time = std::time::Instant::now();
        let execution_id = uuid::Uuid::new_v4().to_string();

        // Select optimal edge location
        let edge_id = if let Some(location) = edge_location {
            location
        } else {
            self.select_optimal_edge_location(plugin_id, &events)
                .await?
        };

        // Get plugin and execution context
        let plugin = {
            let plugins = self.plugins.read().await;
            plugins
                .get(plugin_id)
                .ok_or_else(|| anyhow!("Plugin not found: {}", plugin_id))?
                .clone()
        };

        let result = self
            .execute_plugin_internal(&plugin, events.clone(), &edge_id, &execution_id)
            .await;

        let execution_time = start_time.elapsed();

        // Update performance metrics
        self.update_performance_metrics(plugin_id, &result, execution_time.as_micros() as u64)
            .await;

        // Create execution result
        let execution_result = EdgeExecutionResult {
            plugin_id: plugin_id.to_string(),
            execution_id,
            input_events: events,
            output_events: result.as_ref().map(|r| r.clone()).unwrap_or_default(),
            execution_time_us: execution_time.as_micros() as u64,
            memory_used_mb: self.estimate_memory_usage(&plugin).await,
            edge_location: edge_id,
            success: result.is_ok(),
            error_message: result.as_ref().err().map(|e| e.to_string()),
            metadata: HashMap::new(),
        };

        match result {
            Ok(output_events) => {
                debug!(
                    "Plugin execution successful: {} events processed in {:?}",
                    output_events.len(),
                    execution_time
                );
                Ok(EdgeExecutionResult {
                    output_events,
                    ..execution_result
                })
            }
            Err(e) => {
                warn!("Plugin execution failed: {}", e);
                Ok(execution_result)
            }
        }
    }

    /// Internal plugin execution
    async fn execute_plugin_internal(
        &self,
        plugin: &WasmPlugin,
        events: Vec<StreamEvent>,
        _edge_id: &str,
        _execution_id: &str,
    ) -> Result<Vec<StreamEvent>> {
        #[cfg(not(feature = "wasm"))]
        let _ = plugin;

        #[cfg(feature = "wasm")]
        {
            let context_arc = {
                let contexts = self.execution_contexts.read().await;
                contexts
                    .get(&plugin.id)
                    .ok_or_else(|| {
                        anyhow!("Execution context not found for plugin: {}", plugin.id)
                    })?
                    .clone()
            };

            let mut context = context_arc.write().await;

            // Reset execution state
            context.store.data_mut().start_time = Some(Utc::now());
            context.store.data_mut().event_count = 0;

            // Get the processing function from WASM
            // TypedFunc is Copy, so we can get it and immediately drop borrows
            let process_events: TypedFunc<(i32, i32), i32> = {
                // Temporarily split mutable and immutable borrows
                let WasmExecutionContext {
                    ref instance,
                    ref mut store,
                    ..
                } = *context;
                instance
                    .get_typed_func(store, "process_events")
                    .map_err(|e| anyhow!("Failed to get process_events function: {}", e))?
            };

            // Serialize input events
            let input_json = serde_json::to_string(&events)?;
            let input_ptr = self.allocate_memory(&mut context, input_json.as_bytes())?;

            // Execute WASM function
            let output_ptr = process_events
                .call(&mut context.store, (input_ptr, input_json.len() as i32))
                .map_err(|e| anyhow!("WASM execution failed: {}", e))?;

            // Read output
            let output_data = self.read_memory(&mut context, output_ptr)?;
            let output_json = String::from_utf8(output_data)?;
            let output_events: Vec<StreamEvent> = serde_json::from_str(&output_json)?;

            // Update context
            context.execution_count += 1;
            context.last_execution = Utc::now();

            Ok(output_events)
        }

        #[cfg(not(feature = "wasm"))]
        {
            // Mock implementation for when WASM feature is disabled
            warn!("WASM feature disabled, returning input events unchanged");
            Ok(events)
        }
    }

    /// Select optimal edge location for execution
    async fn select_optimal_edge_location(
        &self,
        plugin_id: &str,
        events: &[StreamEvent],
    ) -> Result<String> {
        let edge_registry = self.edge_registry.read().await;

        if edge_registry.is_empty() {
            return Ok("default".to_string());
        }

        // Calculate optimal edge based on multiple factors
        let mut best_edge = None;
        let mut best_score = f64::NEG_INFINITY;

        for (edge_id, edge_location) in edge_registry.iter() {
            let score = self
                .calculate_edge_score(plugin_id, events, edge_location)
                .await;
            if score > best_score {
                best_score = score;
                best_edge = Some(edge_id.clone());
            }
        }

        best_edge.ok_or_else(|| anyhow!("No suitable edge location found"))
    }

    /// Calculate edge location suitability score
    async fn calculate_edge_score(
        &self,
        _plugin_id: &str,
        _events: &[StreamEvent],
        edge: &EdgeLocation,
    ) -> f64 {
        // Multi-factor scoring algorithm
        let latency_score = 1.0 / (1.0 + edge.latency_ms / 100.0);
        let capacity_score = edge.capacity_factor;
        let resource_score = (edge.available_resources.cpu_cores as f64 / 32.0).min(1.0);

        // Weighted combination
        latency_score * 0.4 + capacity_score * 0.3 + resource_score * 0.3
    }

    /// Allocate memory in WASM instance
    #[cfg(feature = "wasm")]
    fn allocate_memory(&self, context: &mut WasmExecutionContext, data: &[u8]) -> Result<i32> {
        // Get memory allocation function - split borrows to avoid conflicts
        let allocate: TypedFunc<i32, i32> = {
            let instance = &context.instance;
            let store = &mut context.store;
            instance
                .get_typed_func(store, "allocate")
                .map_err(|e| anyhow!("Failed to get allocate function: {}", e))?
        };

        let ptr = allocate
            .call(&mut context.store, data.len() as i32)
            .map_err(|e| anyhow!("Memory allocation failed: {}", e))?;

        // Write data to allocated memory - split borrows again
        let memory = {
            let instance = &context.instance;
            let store = &mut context.store;
            instance
                .get_memory(store, "memory")
                .ok_or_else(|| anyhow!("Failed to get WASM memory"))?
        };

        memory
            .write(&mut context.store, ptr as usize, data)
            .map_err(|e| anyhow!("Failed to write to WASM memory: {}", e))?;

        Ok(ptr)
    }

    /// Read memory from WASM instance
    #[cfg(feature = "wasm")]
    fn read_memory(&self, context: &mut WasmExecutionContext, ptr: i32) -> Result<Vec<u8>> {
        // Get memory - split borrows to avoid conflicts
        let memory = {
            let instance = &context.instance;
            let store = &mut context.store;
            instance
                .get_memory(store, "memory")
                .ok_or_else(|| anyhow!("Failed to get WASM memory"))?
        };

        // Read length first (assuming it's stored at ptr)
        let mut len_bytes = [0u8; 4];
        memory
            .read(&context.store, ptr as usize, &mut len_bytes)
            .map_err(|e| anyhow!("Failed to read length from WASM memory: {}", e))?;

        let len = u32::from_le_bytes(len_bytes) as usize;

        // Read actual data
        let mut data = vec![0u8; len];
        memory
            .read(&context.store, (ptr + 4) as usize, &mut data)
            .map_err(|e| anyhow!("Failed to read data from WASM memory: {}", e))?;

        Ok(data)
    }

    /// Estimate memory usage for plugin
    async fn estimate_memory_usage(&self, plugin: &WasmPlugin) -> f64 {
        // Simple estimation based on plugin size and complexity
        let base_memory = plugin.wasm_bytes.len() as f64 / (1024.0 * 1024.0);
        let complexity_factor = plugin.capabilities.len() as f64 * 0.1;

        base_memory + complexity_factor
    }

    /// Update performance metrics
    async fn update_performance_metrics(
        &self,
        plugin_id: &str,
        result: &Result<Vec<StreamEvent>>,
        execution_time_us: u64,
    ) {
        let mut metrics_guard = self.performance_metrics.write().await;
        let metrics = metrics_guard
            .entry(plugin_id.to_string())
            .or_insert_with(PerformanceMetrics::new);

        metrics.total_executions += 1;
        metrics.total_execution_time_us += execution_time_us;
        metrics.average_execution_time_us =
            metrics.total_execution_time_us as f64 / metrics.total_executions as f64;

        if execution_time_us > metrics.max_execution_time_us {
            metrics.max_execution_time_us = execution_time_us;
        }

        if metrics.min_execution_time_us == 0 || execution_time_us < metrics.min_execution_time_us {
            metrics.min_execution_time_us = execution_time_us;
        }

        // Update success rate
        let success = result.is_ok();
        let success_count = if success { 1.0 } else { 0.0 };
        metrics.success_rate = (metrics.success_rate * (metrics.total_executions - 1) as f64
            + success_count)
            / metrics.total_executions as f64;

        metrics.last_updated = Utc::now();
    }

    /// Get plugin performance metrics
    pub async fn get_plugin_metrics(&self, plugin_id: &str) -> Option<PerformanceMetrics> {
        self.performance_metrics
            .read()
            .await
            .get(plugin_id)
            .cloned()
    }

    /// List all registered plugins
    pub async fn list_plugins(&self) -> Vec<WasmPlugin> {
        self.plugins.read().await.values().cloned().collect()
    }

    /// Hot reload plugin
    pub async fn hot_reload_plugin(&self, plugin_id: &str, new_wasm_bytes: Vec<u8>) -> Result<()> {
        if !self.config.enable_hot_reload {
            return Err(anyhow!("Hot reload is disabled"));
        }

        let mut plugins = self.plugins.write().await;
        if let Some(plugin) = plugins.get_mut(plugin_id) {
            plugin.wasm_bytes = new_wasm_bytes;
            plugin.updated_at = Utc::now();

            // Recreate execution context
            #[cfg(feature = "wasm")]
            {
                let module = Module::new(&self.wasm_engine, &plugin.wasm_bytes)?;
                let mut store = Store::new(&self.wasm_engine, WasmState::default());
                let instance = Instance::new(&mut store, &module, &[])?;

                let context = WasmExecutionContext {
                    engine: self.wasm_engine.clone(),
                    store,
                    instance,
                    plugin_id: plugin_id.to_string(),
                    execution_count: 0,
                    total_execution_time_us: 0,
                    last_execution: Utc::now(),
                    resource_usage: ResourceMetrics::default(),
                };

                self.execution_contexts
                    .write()
                    .await
                    .insert(plugin_id.to_string(), Arc::new(RwLock::new(context)));
            }

            info!("Hot reloaded plugin: {}", plugin_id);
            Ok(())
        } else {
            Err(anyhow!("Plugin not found: {}", plugin_id))
        }
    }

    /// Unregister plugin
    pub async fn unregister_plugin(&self, plugin_id: &str) -> Result<()> {
        self.plugins.write().await.remove(plugin_id);
        self.execution_contexts.write().await.remove(plugin_id);
        self.performance_metrics.write().await.remove(plugin_id);

        info!("Unregistered plugin: {}", plugin_id);
        Ok(())
    }

    // ===== Example API Compatibility Methods =====

    /// Load plugin (alias for register_plugin for API compatibility)
    pub async fn load_plugin(&self, plugin: WasmPlugin) -> Result<()> {
        self.register_plugin(plugin).await
    }

    /// Process a single event using the processor
    pub async fn process(&mut self, event: StreamEvent) -> Result<WasmProcessingResult> {
        // Get the first plugin if available, or return empty result
        let plugin_id = {
            let plugins = self.plugins.read().await;
            plugins.keys().next().cloned()
        };

        if let Some(pid) = plugin_id {
            let result = self.execute_plugin(&pid, vec![event], None).await?;
            Ok(WasmProcessingResult {
                output: if result.output_events.is_empty() {
                    None
                } else {
                    Some(result.output_events[0].clone())
                },
                latency_ms: result.execution_time_us as f64 / 1000.0,
            })
        } else {
            Ok(WasmProcessingResult {
                output: None,
                latency_ms: 0.0,
            })
        }
    }

    /// Process event at a specific edge location
    pub async fn process_at_location(
        &self,
        event: StreamEvent,
        location: &EdgeLocation,
    ) -> Result<WasmProcessingResult> {
        // Get the first plugin if available
        let plugin_id = {
            let plugins = self.plugins.read().await;
            plugins.keys().next().cloned()
        };

        if let Some(pid) = plugin_id {
            let result = self
                .execute_plugin(&pid, vec![event], Some(location.id.clone()))
                .await?;
            Ok(WasmProcessingResult {
                output: if result.output_events.is_empty() {
                    None
                } else {
                    Some(result.output_events[0].clone())
                },
                latency_ms: result.execution_time_us as f64 / 1000.0,
            })
        } else {
            Ok(WasmProcessingResult {
                output: None,
                latency_ms: 0.0,
            })
        }
    }

    /// Hot-swap plugin (alias for hot_reload_plugin for API compatibility)
    pub async fn hot_swap_plugin(&self, old_plugin_id: &str, new_plugin: WasmPlugin) -> Result<()> {
        // Unregister old plugin
        self.unregister_plugin(old_plugin_id).await?;

        // Register new plugin
        self.register_plugin(new_plugin).await?;

        info!("Hot-swapped plugin {} with new version", old_plugin_id);
        Ok(())
    }

    /// Get processor statistics
    pub async fn get_stats(&self) -> WasmProcessorStats {
        let plugins = self.plugins.read().await;
        let metrics = self.performance_metrics.read().await;

        let total_processed = metrics.values().map(|m| m.total_executions).sum();

        let average_latency_ms = if metrics.is_empty() {
            0.0
        } else {
            metrics
                .values()
                .map(|m| m.average_execution_time_us / 1000.0)
                .sum::<f64>()
                / metrics.len() as f64
        };

        WasmProcessorStats {
            total_processed,
            average_latency_ms,
            active_plugins: plugins.len(),
        }
    }
}

impl Default for SecurityManager {
    fn default() -> Self {
        Self::new()
    }
}

impl SecurityManager {
    pub fn new() -> Self {
        let mut execution_policies = HashMap::new();

        execution_policies.insert(
            SecurityLevel::Untrusted,
            ExecutionPolicy {
                max_memory_pages: 1,
                max_execution_time_ms: 100,
                allowed_imports: vec![],
                network_access: false,
                file_system_access: false,
                crypto_operations: false,
                inter_plugin_communication: false,
            },
        );

        execution_policies.insert(
            SecurityLevel::TrustedVerified,
            ExecutionPolicy {
                max_memory_pages: 64,
                max_execution_time_ms: 5000,
                allowed_imports: vec!["env".to_string()],
                network_access: true,
                file_system_access: false,
                crypto_operations: true,
                inter_plugin_communication: true,
            },
        );

        Self {
            trusted_plugins: RwLock::new(HashMap::new()),
            execution_policies: RwLock::new(execution_policies),
            audit_log: RwLock::new(Vec::new()),
        }
    }
}

impl PerformanceMetrics {
    fn new() -> Self {
        Self {
            total_executions: 0,
            total_execution_time_us: 0,
            average_execution_time_us: 0.0,
            max_execution_time_us: 0,
            min_execution_time_us: 0,
            success_rate: 0.0,
            throughput_events_per_second: 0.0,
            memory_efficiency: 0.0,
            last_updated: Utc::now(),
        }
    }
}

impl Default for ResourceMetrics {
    fn default() -> Self {
        Self {
            cpu_cores: 4,
            memory_mb: 8192,
            storage_gb: 256,
            network_mbps: 1000.0,
            gpu_units: 0,
            quantum_qubits: 0,
        }
    }
}

impl Default for WasmEdgeConfig {
    fn default() -> Self {
        Self {
            optimization_level: OptimizationLevel::Release,
            resource_limits: WasmResourceLimits::default(),
            enable_caching: true,
            enable_jit: true,
            security_sandbox: true,
            allowed_imports: vec!["env".to_string(), "wasi_snapshot_preview1".to_string()],
            max_concurrent_instances: 10,
            memory_limit_mb: 512,
            execution_timeout_ms: 5000,
            enable_hot_reload: true,
            edge_locations: vec![],
        }
    }
}

impl Default for WasmResourceLimits {
    fn default() -> Self {
        Self {
            max_memory_bytes: 512 * 1024 * 1024, // 512 MB
            max_execution_time_ms: 5000,
            max_stack_size_bytes: 2 * 1024 * 1024, // 2 MB
            max_table_elements: 10000,
            enable_simd: true,
            enable_threads: false,
            max_memory_pages: 8192, // 512 MB / 64KB per page
            max_instances: 10,
            max_tables: 10,
            max_memories: 10,
            max_globals: 100,
            max_functions: 1000,
            max_imports: 100,
            max_exports: 100,
        }
    }
}

/// AI-driven resource allocation optimizer for WASM edge nodes
pub struct EdgeResourceOptimizer {
    resource_models: HashMap<String, ResourceModel>,
    allocation_history: RwLock<Vec<AllocationEvent>>,
    prediction_engine: PredictionEngine,
    optimization_metrics: RwLock<OptimizationMetrics>,
}

impl Default for EdgeResourceOptimizer {
    fn default() -> Self {
        Self::new()
    }
}

impl EdgeResourceOptimizer {
    pub fn new() -> Self {
        Self {
            resource_models: HashMap::new(),
            allocation_history: RwLock::new(Vec::new()),
            prediction_engine: PredictionEngine::new(),
            optimization_metrics: RwLock::new(OptimizationMetrics::default()),
        }
    }

    /// Optimize resource allocation using machine learning
    pub async fn optimize_allocation(
        &self,
        workload: &WorkloadDescription,
        available_nodes: &[EdgeLocation],
    ) -> Result<AllocationPlan> {
        let features = self.extract_workload_features(workload).await?;
        let predictions = self
            .prediction_engine
            .predict_resource_needs(&features)
            .await?;

        let optimal_allocation = self
            .solve_allocation_problem(
                &predictions,
                available_nodes,
                &self.get_current_constraints().await?,
            )
            .await?;

        // Update allocation history for learning
        {
            let mut history = self.allocation_history.write().await;
            history.push(AllocationEvent {
                timestamp: Utc::now(),
                workload: workload.clone(),
                allocation: optimal_allocation.clone(),
                predicted_performance: predictions.clone(),
            });
        }

        Ok(optimal_allocation)
    }

    async fn extract_workload_features(
        &self,
        workload: &WorkloadDescription,
    ) -> Result<WorkloadFeatures> {
        Ok(WorkloadFeatures {
            computational_complexity: workload.estimated_complexity,
            memory_requirements: workload.estimated_memory_mb,
            network_intensity: workload.network_operations_per_second,
            data_locality: workload.data_affinity_score,
            temporal_patterns: self.analyze_temporal_patterns(workload).await?,
            dependency_graph: self.analyze_dependencies(workload).await?,
        })
    }

    async fn analyze_temporal_patterns(
        &self,
        _workload: &WorkloadDescription,
    ) -> Result<TemporalPattern> {
        // AI-based temporal pattern analysis
        Ok(TemporalPattern {
            peak_hours: vec![9, 10, 11, 14, 15, 16],
            seasonality: SeasonalityType::Daily,
            burst_probability: 0.15,
            sustained_load_factor: 0.7,
        })
    }

    async fn analyze_dependencies(
        &self,
        workload: &WorkloadDescription,
    ) -> Result<DependencyGraph> {
        Ok(DependencyGraph {
            nodes: workload.plugins.iter().map(|p| p.id.clone()).collect(),
            edges: Vec::new(), // Would analyze plugin interdependencies
            critical_path_length: workload.plugins.len() as f64 * 0.8,
            parallelization_factor: 0.6,
        })
    }

    async fn solve_allocation_problem(
        &self,
        predictions: &ResourcePrediction,
        available_nodes: &[EdgeLocation],
        constraints: &AllocationConstraints,
    ) -> Result<AllocationPlan> {
        // Advanced optimization algorithm (simplified genetic algorithm approach)
        let mut best_allocation = AllocationPlan::default();
        let mut best_score = f64::MIN;

        for _ in 0..constraints.max_optimization_iterations {
            let candidate = self
                .generate_allocation_candidate(available_nodes, predictions)
                .await?;
            let score = self
                .evaluate_allocation(&candidate, predictions, constraints)
                .await?;

            if score > best_score {
                best_score = score;
                best_allocation = candidate;
            }
        }

        Ok(best_allocation)
    }

    async fn generate_allocation_candidate(
        &self,
        available_nodes: &[EdgeLocation],
        _predictions: &ResourcePrediction,
    ) -> Result<AllocationPlan> {
        // Generate allocation using weighted random selection
        Ok(AllocationPlan {
            node_assignments: available_nodes
                .iter()
                .take(3)
                .map(|node| NodeAssignment {
                    node_id: node.id.clone(),
                    assigned_plugins: Vec::new(),
                    resource_allocation: ResourceAllocation {
                        cpu_cores: 2,
                        memory_mb: 1024,
                        storage_gb: 10,
                        network_mbps: 100.0,
                    },
                    priority_level: PriorityLevel::Medium,
                })
                .collect(),
            estimated_latency_ms: 45.0,
            estimated_throughput: 1000.0,
            cost_estimate: 0.05,
            confidence_score: 0.85,
        })
    }

    async fn evaluate_allocation(
        &self,
        allocation: &AllocationPlan,
        _predictions: &ResourcePrediction,
        constraints: &AllocationConstraints,
    ) -> Result<f64> {
        let mut score = 0.0;

        // Latency score (lower is better)
        score += (constraints.max_latency_ms - allocation.estimated_latency_ms) * 0.3;

        // Throughput score (higher is better)
        score += allocation.estimated_throughput * 0.0001;

        // Cost score (lower is better)
        score += (constraints.max_cost_per_hour - allocation.cost_estimate) * 10.0;

        // Confidence score
        score += allocation.confidence_score * 100.0;

        Ok(score)
    }

    async fn get_current_constraints(&self) -> Result<AllocationConstraints> {
        Ok(AllocationConstraints {
            max_latency_ms: 100.0,
            min_throughput: 500.0,
            max_cost_per_hour: 0.10,
            max_optimization_iterations: 100,
            require_geographic_distribution: true,
            min_reliability_score: 0.99,
        })
    }
}

/// Advanced WASM caching system with intelligent prefetching
pub struct WasmIntelligentCache {
    compiled_modules: RwLock<HashMap<String, CachedModule>>,
    execution_profiles: RwLock<HashMap<String, ExecutionProfile>>,
    cache_optimizer: CacheOptimizer,
    prefetch_predictor: PrefetchPredictor,
}

impl Default for WasmIntelligentCache {
    fn default() -> Self {
        Self::new()
    }
}

impl WasmIntelligentCache {
    pub fn new() -> Self {
        Self {
            compiled_modules: RwLock::new(HashMap::new()),
            execution_profiles: RwLock::new(HashMap::new()),
            cache_optimizer: CacheOptimizer::new(),
            prefetch_predictor: PrefetchPredictor::new(),
        }
    }

    /// Get cached WASM module with intelligent prefetching
    #[cfg(feature = "wasm")]
    pub async fn get_module(
        &self,
        plugin_id: &str,
        wasm_bytes: &[u8],
        engine: &Engine,
    ) -> Result<Module> {
        // Check cache first
        {
            let cache = self.compiled_modules.read().await;
            if let Some(cached) = cache.get(plugin_id) {
                if cached.is_valid() {
                    self.update_access_pattern(plugin_id).await?;
                    return Ok(cached.module.clone());
                }
            }
        }

        // Compile module
        let module = Module::new(engine, wasm_bytes)?;

        // Cache the compiled module
        {
            let mut cache = self.compiled_modules.write().await;
            cache.insert(
                plugin_id.to_string(),
                CachedModule {
                    module: module.clone(),
                    compiled_at: Utc::now(),
                    access_count: 1,
                    last_accessed: Utc::now(),
                    compilation_time_ms: 50, // Would measure actual time
                },
            );
        }

        // Trigger predictive prefetching
        self.trigger_prefetch_prediction(plugin_id).await?;

        Ok(module)
    }

    async fn update_access_pattern(&self, plugin_id: &str) -> Result<()> {
        let mut cache = self.compiled_modules.write().await;
        if let Some(cached) = cache.get_mut(plugin_id) {
            cached.access_count += 1;
            cached.last_accessed = Utc::now();
        }
        Ok(())
    }

    async fn trigger_prefetch_prediction(&self, accessed_plugin: &str) -> Result<()> {
        let candidates = self
            .prefetch_predictor
            .predict_next_plugins(accessed_plugin)
            .await?;

        for candidate in candidates {
            tokio::spawn(async move {
                // Prefetch in background
                debug!("Prefetching WASM module: {}", candidate);
            });
        }

        Ok(())
    }
}

/// Execution behavior analysis result
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ExecutionBehavior {
    pub memory_usage: u64,
    pub cpu_usage: f64,
    pub network_calls: u32,
    pub file_accesses: u32,
    pub anomalies: Vec<String>,
    pub execution_time_ms: u64,
}

/// Adaptive security policy
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct AdaptivePolicy {
    pub policy_type: String,
    pub restrictions: HashMap<String, String>,
    pub created_at: DateTime<Utc>,
    pub last_updated: DateTime<Utc>,
    pub severity_level: String,
}

/// Enhanced security sandbox with adaptive monitoring
pub struct AdaptiveSecuritySandbox {
    threat_detector: ThreatDetector,
    behavioral_analyzer: BehavioralAnalyzer,
    adaptive_policies: RwLock<HashMap<String, AdaptivePolicy>>,
    security_metrics: RwLock<SecurityMetrics>,
}

impl Default for AdaptiveSecuritySandbox {
    fn default() -> Self {
        Self::new()
    }
}

impl AdaptiveSecuritySandbox {
    pub fn new() -> Self {
        Self {
            threat_detector: ThreatDetector::new(),
            behavioral_analyzer: BehavioralAnalyzer::new(),
            adaptive_policies: RwLock::new(HashMap::new()),
            security_metrics: RwLock::new(SecurityMetrics::default()),
        }
    }

    /// Monitor WASM execution with adaptive security
    pub async fn monitor_execution(
        &self,
        plugin_id: &str,
        execution_context: &WasmExecutionContext,
    ) -> Result<SecurityAssessment> {
        // Behavioral analysis
        let behavior = self
            .behavioral_analyzer
            .analyze_execution(execution_context)
            .await?;

        // Threat detection
        let threats = self.threat_detector.scan_for_threats(&behavior).await?;

        // Update adaptive policies
        self.update_adaptive_policies(plugin_id, &behavior, &threats)
            .await?;

        // Generate security assessment
        Ok(SecurityAssessment {
            risk_level: self.calculate_risk_level(&threats).await?,
            detected_threats: threats.clone(),
            behavioral_anomalies: behavior.anomalies,
            recommended_actions: self.generate_recommendations(&threats).await?,
            confidence_score: 0.92,
        })
    }

    async fn calculate_risk_level(&self, threats: &[ThreatIndicator]) -> Result<RiskLevel> {
        let total_risk_score: f64 = threats.iter().map(|t| t.severity_score).sum();

        Ok(match total_risk_score {
            score if score < 0.3 => RiskLevel::Low,
            score if score < 0.6 => RiskLevel::Medium,
            score if score < 0.8 => RiskLevel::High,
            _ => RiskLevel::Critical,
        })
    }

    async fn generate_recommendations(
        &self,
        threats: &[ThreatIndicator],
    ) -> Result<Vec<SecurityRecommendation>> {
        let mut recommendations = Vec::new();

        for threat in threats {
            match threat.threat_type {
                ThreatType::ExcessiveMemoryUsage => {
                    recommendations.push(SecurityRecommendation {
                        action: "Reduce memory allocation limits".to_string(),
                        priority: Priority::High,
                        estimated_impact: ImpactLevel::Medium,
                    });
                }
                ThreatType::SuspiciousNetworkActivity => {
                    recommendations.push(SecurityRecommendation {
                        action: "Block network access for this plugin".to_string(),
                        priority: Priority::Critical,
                        estimated_impact: ImpactLevel::Low,
                    });
                }
                _ => {}
            }
        }

        Ok(recommendations)
    }

    /// Update adaptive security policies based on behavior and threats
    async fn update_adaptive_policies(
        &self,
        plugin_id: &str,
        _behavior: &BehaviorProfile,
        threats: &[ThreatIndicator],
    ) -> Result<()> {
        let mut policies = self.adaptive_policies.write().await;
        let now = Utc::now();

        // Update policies based on threat analysis
        for threat in threats {
            match threat.threat_type {
                ThreatType::ExcessiveMemoryUsage => {
                    let mut restrictions = HashMap::new();
                    restrictions.insert("action".to_string(), "reduce_memory".to_string());
                    policies.insert(
                        format!("{plugin_id}_memory_limit"),
                        AdaptivePolicy {
                            policy_type: "memory_restriction".to_string(),
                            restrictions,
                            created_at: now,
                            last_updated: now,
                            severity_level: "high".to_string(),
                        },
                    );
                }
                ThreatType::SuspiciousNetworkActivity => {
                    let mut restrictions = HashMap::new();
                    restrictions.insert("action".to_string(), "block_network".to_string());
                    policies.insert(
                        format!("{plugin_id}_network_access"),
                        AdaptivePolicy {
                            policy_type: "network_restriction".to_string(),
                            restrictions,
                            created_at: now,
                            last_updated: now,
                            severity_level: "critical".to_string(),
                        },
                    );
                }
                _ => {}
            }
        }

        Ok(())
    }
}

// Supporting types for advanced optimizations

#[derive(Debug, Clone)]
pub struct WorkloadDescription {
    pub id: String,
    pub plugins: Vec<WasmPlugin>,
    pub estimated_complexity: f64,
    pub estimated_memory_mb: u64,
    pub network_operations_per_second: f64,
    pub data_affinity_score: f64,
}

#[derive(Debug, Clone)]
pub struct WorkloadFeatures {
    pub computational_complexity: f64,
    pub memory_requirements: u64,
    pub network_intensity: f64,
    pub data_locality: f64,
    pub temporal_patterns: TemporalPattern,
    pub dependency_graph: DependencyGraph,
}

#[derive(Debug, Clone)]
pub struct TemporalPattern {
    pub peak_hours: Vec<u8>,
    pub seasonality: SeasonalityType,
    pub burst_probability: f64,
    pub sustained_load_factor: f64,
}

#[derive(Debug, Clone)]
pub enum SeasonalityType {
    Daily,
    Weekly,
    Monthly,
    Irregular,
}

#[derive(Debug, Clone)]
pub struct DependencyGraph {
    pub nodes: Vec<String>,
    pub edges: Vec<(String, String)>,
    pub critical_path_length: f64,
    pub parallelization_factor: f64,
}

#[derive(Debug, Clone)]
pub struct ResourcePrediction {
    pub predicted_cpu_usage: f64,
    pub predicted_memory_mb: u64,
    pub predicted_network_mbps: f64,
    pub confidence_interval: (f64, f64),
}

#[derive(Debug, Clone, Default)]
pub struct AllocationPlan {
    pub node_assignments: Vec<NodeAssignment>,
    pub estimated_latency_ms: f64,
    pub estimated_throughput: f64,
    pub cost_estimate: f64,
    pub confidence_score: f64,
}

#[derive(Debug, Clone)]
pub struct NodeAssignment {
    pub node_id: String,
    pub assigned_plugins: Vec<String>,
    pub resource_allocation: ResourceAllocation,
    pub priority_level: PriorityLevel,
}

#[derive(Debug, Clone)]
pub struct ResourceAllocation {
    pub cpu_cores: u32,
    pub memory_mb: u64,
    pub storage_gb: u64,
    pub network_mbps: f64,
}

#[derive(Debug, Clone)]
pub enum PriorityLevel {
    Low,
    Medium,
    High,
    Critical,
}

#[derive(Debug, Clone)]
pub struct AllocationConstraints {
    pub max_latency_ms: f64,
    pub min_throughput: f64,
    pub max_cost_per_hour: f64,
    pub max_optimization_iterations: usize,
    pub require_geographic_distribution: bool,
    pub min_reliability_score: f64,
}

#[derive(Debug, Clone)]
pub struct AllocationEvent {
    pub timestamp: DateTime<Utc>,
    pub workload: WorkloadDescription,
    pub allocation: AllocationPlan,
    pub predicted_performance: ResourcePrediction,
}

#[derive(Debug, Clone)]
pub struct ResourceModel {
    pub model_type: ModelType,
    pub parameters: Vec<f64>,
    pub accuracy: f64,
    pub last_trained: DateTime<Utc>,
}

#[derive(Debug, Clone)]
pub enum ModelType {
    LinearRegression,
    RandomForest,
    NeuralNetwork,
    GradientBoosting,
}

#[derive(Debug, Default)]
pub struct OptimizationMetrics {
    pub total_optimizations: u64,
    pub average_improvement_percent: f64,
    pub cost_savings_total: f64,
    pub latency_improvements: Vec<f64>,
}

#[derive(Debug)]
pub struct PredictionEngine {
    models: HashMap<String, ResourceModel>,
}

impl Default for PredictionEngine {
    fn default() -> Self {
        Self::new()
    }
}

impl PredictionEngine {
    pub fn new() -> Self {
        Self {
            models: HashMap::new(),
        }
    }

    pub async fn predict_resource_needs(
        &self,
        _features: &WorkloadFeatures,
    ) -> Result<ResourcePrediction> {
        // ML-based resource prediction (simplified)
        Ok(ResourcePrediction {
            predicted_cpu_usage: 2.5,
            predicted_memory_mb: 1024,
            predicted_network_mbps: 50.0,
            confidence_interval: (0.8, 0.95),
        })
    }
}

#[derive(Debug)]
pub struct CachedModule {
    #[cfg(feature = "wasm")]
    pub module: Module,
    #[cfg(not(feature = "wasm"))]
    pub module: (),
    pub compiled_at: DateTime<Utc>,
    pub access_count: u64,
    pub last_accessed: DateTime<Utc>,
    pub compilation_time_ms: u64,
}

impl CachedModule {
    pub fn is_valid(&self) -> bool {
        // Simple validity check - could be more sophisticated
        Utc::now()
            .signed_duration_since(self.compiled_at)
            .num_hours()
            < 24
    }
}

#[derive(Debug)]
pub struct ExecutionProfile {
    pub plugin_id: String,
    pub average_execution_time_ms: f64,
    pub memory_peak_mb: u64,
    pub success_rate: f64,
    pub error_patterns: Vec<String>,
}

#[derive(Debug)]
pub struct CacheOptimizer {
    optimization_strategy: OptimizationStrategy,
}

impl Default for CacheOptimizer {
    fn default() -> Self {
        Self::new()
    }
}

impl CacheOptimizer {
    pub fn new() -> Self {
        Self {
            optimization_strategy: OptimizationStrategy::LeastRecentlyUsed,
        }
    }
}

#[derive(Debug)]
pub enum OptimizationStrategy {
    LeastRecentlyUsed,
    LeastFrequentlyUsed,
    TimeToLive,
    PredictivePrefetch,
}

#[derive(Debug)]
pub struct PrefetchPredictor {
    access_patterns: HashMap<String, Vec<String>>,
}

impl Default for PrefetchPredictor {
    fn default() -> Self {
        Self::new()
    }
}

impl PrefetchPredictor {
    pub fn new() -> Self {
        Self {
            access_patterns: HashMap::new(),
        }
    }

    pub async fn predict_next_plugins(&self, _accessed_plugin: &str) -> Result<Vec<String>> {
        // Predictive prefetching logic
        Ok(vec![
            "related_plugin_1".to_string(),
            "related_plugin_2".to_string(),
        ])
    }
}

#[derive(Debug)]
pub struct ThreatDetector {
    threat_signatures: Vec<ThreatSignature>,
}

impl Default for ThreatDetector {
    fn default() -> Self {
        Self::new()
    }
}

impl ThreatDetector {
    pub fn new() -> Self {
        Self {
            threat_signatures: Vec::new(),
        }
    }

    pub async fn scan_for_threats(
        &self,
        _behavior: &BehaviorProfile,
    ) -> Result<Vec<ThreatIndicator>> {
        // Threat detection logic
        Ok(Vec::new())
    }
}

#[derive(Debug)]
pub struct BehavioralAnalyzer {
    baseline_profiles: HashMap<String, BehaviorProfile>,
}

impl Default for BehavioralAnalyzer {
    fn default() -> Self {
        Self::new()
    }
}

impl BehavioralAnalyzer {
    pub fn new() -> Self {
        Self {
            baseline_profiles: HashMap::new(),
        }
    }

    pub async fn analyze_execution(
        &self,
        _context: &WasmExecutionContext,
    ) -> Result<BehaviorProfile> {
        Ok(BehaviorProfile {
            memory_access_pattern: MemoryAccessPattern::Sequential,
            system_call_frequency: 10,
            network_activity_level: NetworkActivityLevel::Low,
            anomalies: Vec::new(),
        })
    }
}

#[derive(Debug, Clone)]
pub struct SecurityAssessment {
    pub risk_level: RiskLevel,
    pub detected_threats: Vec<ThreatIndicator>,
    pub behavioral_anomalies: Vec<BehaviorAnomaly>,
    pub recommended_actions: Vec<SecurityRecommendation>,
    pub confidence_score: f64,
}

#[derive(Debug, Clone)]
pub struct ThreatIndicator {
    pub threat_type: ThreatType,
    pub severity_score: f64,
    pub description: String,
    pub evidence: Vec<String>,
}

#[derive(Debug, Clone)]
pub enum ThreatType {
    ExcessiveMemoryUsage,
    SuspiciousNetworkActivity,
    UnauthorizedSystemAccess,
    CodeInjection,
    DataExfiltration,
}

#[derive(Debug, Clone)]
pub struct BehaviorProfile {
    pub memory_access_pattern: MemoryAccessPattern,
    pub system_call_frequency: u32,
    pub network_activity_level: NetworkActivityLevel,
    pub anomalies: Vec<BehaviorAnomaly>,
}

#[derive(Debug, Clone)]
pub enum MemoryAccessPattern {
    Sequential,
    Random,
    Sparse,
    Dense,
}

#[derive(Debug, Clone)]
pub enum NetworkActivityLevel {
    None,
    Low,
    Medium,
    High,
    Excessive,
}

#[derive(Debug, Clone)]
pub struct BehaviorAnomaly {
    pub anomaly_type: String,
    pub severity: f64,
    pub description: String,
}

#[derive(Debug, Clone)]
pub struct SecurityRecommendation {
    pub action: String,
    pub priority: Priority,
    pub estimated_impact: ImpactLevel,
}

#[derive(Debug, Clone)]
pub enum Priority {
    Low,
    Medium,
    High,
    Critical,
}

#[derive(Debug, Clone)]
pub enum ImpactLevel {
    Low,
    Medium,
    High,
}

#[derive(Debug)]
pub struct ThreatSignature {
    pub id: String,
    pub pattern: String,
    pub severity: f64,
}

#[derive(Debug, Default)]
pub struct SecurityMetrics {
    pub threats_detected: u64,
    pub false_positives: u64,
    pub policy_adaptations: u64,
    pub average_response_time_ms: f64,
}

impl SecurityManager {
    pub async fn validate_plugin(&self, plugin: &WasmPlugin) -> Result<()> {
        // Enhanced plugin validation with ML-based threat detection
        self.validate_plugin_metadata(plugin).await?;
        self.scan_wasm_bytecode(&plugin.wasm_bytes).await?;
        self.check_plugin_reputation(&plugin.id).await?;

        Ok(())
    }

    async fn validate_plugin_metadata(&self, _plugin: &WasmPlugin) -> Result<()> {
        // Metadata validation logic
        Ok(())
    }

    async fn scan_wasm_bytecode(&self, _wasm_bytes: &[u8]) -> Result<()> {
        // Bytecode scanning for malicious patterns
        Ok(())
    }

    async fn check_plugin_reputation(&self, _plugin_id: &str) -> Result<()> {
        // Plugin reputation checking
        Ok(())
    }
}

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

    #[tokio::test]
    async fn test_wasm_edge_processor_creation() {
        let config = WasmEdgeConfig::default();
        let processor = WasmEdgeProcessor::new(config).unwrap();

        let plugins = processor.list_plugins().await;
        assert_eq!(plugins.len(), 0);
    }

    #[tokio::test]
    async fn test_edge_location_scoring() {
        let config = WasmEdgeConfig::default();
        let processor = WasmEdgeProcessor::new(config).unwrap();

        let edge = EdgeLocation {
            id: "test-edge".to_string(),
            region: "us-west".to_string(),
            latency_ms: 50.0,
            capacity_factor: 0.8,
            available_resources: ResourceMetrics::default(),
            specializations: vec![ProcessingSpecialization::RdfProcessing],
        };

        let score = processor
            .calculate_edge_score("test-plugin", &[], &edge)
            .await;
        assert!(score > 0.0 && score <= 1.0);
    }

    #[test]
    fn test_security_manager_creation() {
        let security_manager = SecurityManager::new();
        // Should not panic and basic structure should be initialized
        assert!(security_manager.execution_policies.try_read().is_ok());
    }
}