quantrs2_device/quantum_network/distributed_protocols/implementations/
metrics.rs

1//! Metrics collection, alerting, and resource allocation for distributed quantum computation
2
3use super::super::types::*;
4use async_trait::async_trait;
5use chrono::{DateTime, Utc};
6use serde::{Deserialize, Serialize};
7use std::collections::{HashMap, VecDeque};
8use std::sync::Arc;
9use std::time::Duration;
10use uuid::Uuid;
11
12/// Metrics collection system
13#[derive(Debug)]
14pub struct MetricsCollector {
15    pub metrics_storage: Arc<dyn MetricsStorage + Send + Sync>,
16    pub collection_interval: Duration,
17    pub metrics_aggregator: Arc<MetricsAggregator>,
18    pub alerting_system: Arc<AlertingSystem>,
19}
20
21/// Trait for metrics storage
22#[async_trait]
23pub trait MetricsStorage: std::fmt::Debug {
24    async fn store_metric(&self, metric: &Metric) -> Result<()>;
25    async fn query_metrics(&self, query: &MetricsQuery) -> Result<Vec<Metric>>;
26    async fn aggregate_metrics(&self, aggregation: &AggregationQuery) -> Result<AggregatedMetrics>;
27}
28
29/// Individual metric data point
30#[derive(Debug, Clone, Serialize, Deserialize)]
31pub struct Metric {
32    pub metric_name: String,
33    pub value: f64,
34    pub timestamp: DateTime<Utc>,
35    pub tags: HashMap<String, String>,
36    pub node_id: Option<NodeId>,
37}
38
39/// Metrics query structure
40#[derive(Debug, Clone, Serialize, Deserialize)]
41pub struct MetricsQuery {
42    pub metric_names: Vec<String>,
43    pub time_range: (DateTime<Utc>, DateTime<Utc>),
44    pub filters: HashMap<String, String>,
45    pub limit: Option<u32>,
46}
47
48/// Aggregation query
49#[derive(Debug, Clone, Serialize, Deserialize)]
50pub struct AggregationQuery {
51    pub metric_name: String,
52    pub aggregation_function: AggregationFunction,
53    pub time_range: (DateTime<Utc>, DateTime<Utc>),
54    pub group_by: Vec<String>,
55}
56
57/// Aggregation functions
58#[derive(Debug, Clone, Serialize, Deserialize)]
59pub enum AggregationFunction {
60    Sum,
61    Average,
62    Min,
63    Max,
64    Count,
65    Percentile(f64),
66    StandardDeviation,
67}
68
69/// Aggregated metrics result
70#[derive(Debug, Clone, Serialize, Deserialize)]
71pub struct AggregatedMetrics {
72    pub metric_name: String,
73    pub aggregation_function: AggregationFunction,
74    pub value: f64,
75    pub time_range: (DateTime<Utc>, DateTime<Utc>),
76    pub group_by_values: HashMap<String, f64>,
77}
78
79/// Metrics aggregation engine
80#[derive(Debug)]
81pub struct MetricsAggregator {
82    pub aggregation_strategies: Vec<AggregationStrategy>,
83    pub real_time_aggregation: bool,
84    pub batch_size: u32,
85}
86
87/// Aggregation strategy
88#[derive(Debug, Clone)]
89pub struct AggregationStrategy {
90    pub metric_pattern: String,
91    pub aggregation_interval: Duration,
92    pub functions: Vec<AggregationFunction>,
93    pub retention_period: Duration,
94}
95
96/// Alerting system for monitoring
97#[derive(Debug)]
98pub struct AlertingSystem {
99    pub alert_rules: Vec<AlertRule>,
100    pub notification_channels: HashMap<String, Box<dyn NotificationChannel + Send + Sync>>,
101    pub alert_history: Arc<std::sync::RwLock<VecDeque<AlertNotification>>>,
102}
103
104/// Alert rule definition
105#[derive(Debug, Clone, Serialize, Deserialize)]
106pub struct AlertRule {
107    pub rule_id: String,
108    pub metric_name: String,
109    pub condition: AlertCondition,
110    pub threshold: f64,
111    pub severity: super::fault_tolerance::Severity,
112    pub notification_channels: Vec<String>,
113    pub cooldown_period: Duration,
114}
115
116/// Alert conditions
117#[derive(Debug, Clone, Serialize, Deserialize)]
118pub enum AlertCondition {
119    GreaterThan,
120    LessThan,
121    Equals,
122    NotEquals,
123    RateOfChange(f64),
124    AnomalyDetection,
125}
126
127/// Alert notification
128#[derive(Debug, Clone, Serialize, Deserialize)]
129pub struct AlertNotification {
130    pub alert_id: Uuid,
131    pub rule_id: String,
132    pub timestamp: DateTime<Utc>,
133    pub severity: super::fault_tolerance::Severity,
134    pub message: String,
135    pub affected_nodes: Vec<NodeId>,
136    pub metric_value: f64,
137}
138
139/// Trait for notification channels
140#[async_trait]
141pub trait NotificationChannel: std::fmt::Debug {
142    async fn send_notification(&self, alert: &AlertNotification) -> Result<()>;
143    fn get_channel_type(&self) -> String;
144    fn is_available(&self) -> bool;
145}
146
147/// Resource allocation system
148#[derive(Debug)]
149pub struct ResourceAllocator {
150    pub allocation_strategies: HashMap<String, Box<dyn AllocationStrategy + Send + Sync>>,
151    pub resource_monitor: Arc<ResourceMonitor>,
152    pub allocation_history: Arc<std::sync::RwLock<VecDeque<AllocationRecord>>>,
153}
154
155/// Trait for resource allocation strategies
156pub trait AllocationStrategy: std::fmt::Debug {
157    fn allocate_resources(
158        &self,
159        request: &ExecutionRequest,
160        available_resources: &HashMap<NodeId, AvailableResources>,
161    ) -> Result<AllocationPlan>;
162
163    fn deallocate_resources(&self, allocation: &AllocationPlan) -> Result<()>;
164
165    fn estimate_allocation_time(&self, request: &ExecutionRequest) -> Duration;
166}
167
168/// Available resources on a node
169#[derive(Debug, Clone, Serialize, Deserialize)]
170pub struct AvailableResources {
171    pub available_qubits: u32,
172    pub available_memory_mb: u32,
173    pub available_cpu_percentage: f64,
174    pub available_network_bandwidth_mbps: f64,
175    pub estimated_availability_time: Duration,
176}
177
178/// Resource allocation plan
179#[derive(Debug, Clone, Serialize, Deserialize)]
180pub struct AllocationPlan {
181    pub plan_id: Uuid,
182    pub allocations: HashMap<NodeId, super::fault_tolerance::ResourceAllocation>,
183    pub estimated_cost: f64,
184    pub estimated_execution_time: Duration,
185    pub allocation_timestamp: DateTime<Utc>,
186}
187
188/// Resource allocation record
189#[derive(Debug, Clone, Serialize, Deserialize)]
190pub struct AllocationRecord {
191    pub record_id: Uuid,
192    pub allocation_plan: AllocationPlan,
193    pub actual_execution_time: Option<Duration>,
194    pub actual_cost: Option<f64>,
195    pub success: Option<bool>,
196    pub performance_metrics: Option<PerformanceMetrics>,
197}
198
199/// Resource monitoring system
200#[derive(Debug)]
201pub struct ResourceMonitor {
202    pub monitoring_agents: HashMap<NodeId, Box<dyn MonitoringAgent + Send + Sync>>,
203    pub monitoring_interval: Duration,
204    pub resource_predictions: Arc<ResourcePredictor>,
205}
206
207/// Trait for monitoring agents
208#[async_trait]
209pub trait MonitoringAgent: std::fmt::Debug {
210    async fn collect_resource_metrics(&self) -> Result<ResourceMetrics>;
211    async fn predict_resource_usage(&self, horizon: Duration) -> Result<ResourceUsagePrediction>;
212    fn get_agent_health(&self) -> AgentHealth;
213}
214
215/// Resource metrics from monitoring
216#[derive(Debug, Clone, Serialize, Deserialize)]
217pub struct ResourceMetrics {
218    pub timestamp: DateTime<Utc>,
219    pub cpu_utilization: f64,
220    pub memory_utilization: f64,
221    pub network_utilization: f64,
222    pub qubit_utilization: f64,
223    pub queue_length: u32,
224    pub active_computations: u32,
225}
226
227/// Resource usage prediction
228#[derive(Debug, Clone, Serialize, Deserialize)]
229pub struct ResourceUsagePrediction {
230    pub prediction_horizon: Duration,
231    pub predicted_cpu_usage: f64,
232    pub predicted_memory_usage: f64,
233    pub predicted_network_usage: f64,
234    pub predicted_qubit_usage: f64,
235    pub confidence_interval: (f64, f64),
236}
237
238/// Monitoring agent health status
239#[derive(Debug, Clone, Serialize, Deserialize)]
240pub struct AgentHealth {
241    pub is_healthy: bool,
242    pub last_successful_collection: DateTime<Utc>,
243    pub error_rate: f64,
244    pub response_time: Duration,
245}
246
247/// Resource predictor for capacity planning
248#[derive(Debug)]
249pub struct ResourcePredictor {
250    pub prediction_models: HashMap<String, Box<dyn PredictionModel + Send + Sync>>,
251    pub training_scheduler: Arc<TrainingScheduler>,
252    pub model_evaluator: Arc<ModelEvaluator>,
253}
254
255/// Trait for prediction models
256#[async_trait]
257pub trait PredictionModel: std::fmt::Debug {
258    async fn predict(
259        &self,
260        features: &HashMap<String, f64>,
261        horizon: Duration,
262    ) -> Result<PredictionResult>;
263
264    async fn train(&mut self, training_data: &[TrainingDataPoint]) -> Result<TrainingResult>;
265
266    fn get_model_accuracy(&self) -> f64;
267}
268
269/// Prediction result
270#[derive(Debug, Clone, Serialize, Deserialize)]
271pub struct PredictionResult {
272    pub predicted_value: f64,
273    pub confidence: f64,
274    pub prediction_interval: (f64, f64),
275    pub model_used: String,
276}
277
278/// Training result for ML models
279#[derive(Debug, Clone, Serialize, Deserialize)]
280pub struct TrainingResult {
281    pub training_success: bool,
282    pub model_accuracy: f64,
283    pub training_time: Duration,
284    pub validation_metrics: HashMap<String, f64>,
285}
286
287/// Training scheduler for ML models
288#[derive(Debug)]
289pub struct TrainingScheduler {
290    pub training_schedule: HashMap<String, TrainingConfig>,
291    pub auto_retraining: bool,
292    pub performance_threshold: f64,
293}
294
295/// Training configuration
296#[derive(Debug, Clone, Serialize, Deserialize)]
297pub struct TrainingConfig {
298    pub model_name: String,
299    pub training_frequency: Duration,
300    pub training_data_size: u32,
301    pub validation_split: f64,
302    pub hyperparameters: HashMap<String, f64>,
303}
304
305/// Model evaluator for performance assessment
306#[derive(Debug)]
307pub struct ModelEvaluator {
308    pub evaluation_metrics: Vec<String>,
309    pub cross_validation_folds: u32,
310    pub benchmark_datasets: HashMap<String, Vec<TrainingDataPoint>>,
311}
312
313/// In-memory metrics storage for testing
314#[derive(Debug)]
315pub struct InMemoryMetricsStorage {
316    pub metrics: Arc<std::sync::RwLock<Vec<Metric>>>,
317}
318
319impl Default for InMemoryMetricsStorage {
320    fn default() -> Self {
321        Self::new()
322    }
323}
324
325impl InMemoryMetricsStorage {
326    pub fn new() -> Self {
327        Self {
328            metrics: Arc::new(std::sync::RwLock::new(vec![])),
329        }
330    }
331}
332
333#[async_trait]
334impl MetricsStorage for InMemoryMetricsStorage {
335    async fn store_metric(&self, metric: &Metric) -> Result<()> {
336        let mut metrics = self.metrics.write().expect("Metrics RwLock poisoned");
337        metrics.push(metric.clone());
338        Ok(())
339    }
340
341    async fn query_metrics(&self, query: &MetricsQuery) -> Result<Vec<Metric>> {
342        let metrics = self.metrics.read().expect("Metrics RwLock poisoned");
343        let filtered: Vec<Metric> = metrics
344            .iter()
345            .filter(|m| {
346                query.metric_names.contains(&m.metric_name)
347                    && m.timestamp >= query.time_range.0
348                    && m.timestamp <= query.time_range.1
349            })
350            .cloned()
351            .collect();
352        Ok(filtered)
353    }
354
355    async fn aggregate_metrics(&self, aggregation: &AggregationQuery) -> Result<AggregatedMetrics> {
356        let metrics = self.metrics.read().expect("Metrics RwLock poisoned");
357        let filtered: Vec<&Metric> = metrics
358            .iter()
359            .filter(|m| {
360                m.metric_name == aggregation.metric_name
361                    && m.timestamp >= aggregation.time_range.0
362                    && m.timestamp <= aggregation.time_range.1
363            })
364            .collect();
365
366        let value = match aggregation.aggregation_function {
367            AggregationFunction::Average => {
368                let sum: f64 = filtered.iter().map(|m| m.value).sum();
369                if filtered.is_empty() {
370                    0.0
371                } else {
372                    sum / filtered.len() as f64
373                }
374            }
375            AggregationFunction::Sum => filtered.iter().map(|m| m.value).sum(),
376            AggregationFunction::Max => filtered
377                .iter()
378                .map(|m| m.value)
379                .fold(f64::NEG_INFINITY, f64::max),
380            AggregationFunction::Min => filtered
381                .iter()
382                .map(|m| m.value)
383                .fold(f64::INFINITY, f64::min),
384            AggregationFunction::Count => filtered.len() as f64,
385            _ => 0.0, // Simplified for other functions
386        };
387
388        Ok(AggregatedMetrics {
389            metric_name: aggregation.metric_name.clone(),
390            aggregation_function: aggregation.aggregation_function.clone(),
391            value,
392            time_range: aggregation.time_range,
393            group_by_values: HashMap::new(),
394        })
395    }
396}
397
398impl Default for MetricsCollector {
399    fn default() -> Self {
400        Self::new()
401    }
402}
403
404impl MetricsCollector {
405    pub fn new() -> Self {
406        Self {
407            metrics_storage: Arc::new(InMemoryMetricsStorage::new()),
408            collection_interval: Duration::from_secs(1),
409            metrics_aggregator: Arc::new(MetricsAggregator::new()),
410            alerting_system: Arc::new(AlertingSystem::new()),
411        }
412    }
413}
414
415impl Default for MetricsAggregator {
416    fn default() -> Self {
417        Self::new()
418    }
419}
420
421impl MetricsAggregator {
422    pub const fn new() -> Self {
423        Self {
424            aggregation_strategies: vec![],
425            real_time_aggregation: true,
426            batch_size: 1000,
427        }
428    }
429}
430
431impl Default for AlertingSystem {
432    fn default() -> Self {
433        Self::new()
434    }
435}
436
437impl AlertingSystem {
438    pub fn new() -> Self {
439        Self {
440            alert_rules: vec![],
441            notification_channels: HashMap::new(),
442            alert_history: Arc::new(std::sync::RwLock::new(VecDeque::new())),
443        }
444    }
445}
446
447impl Default for ResourceAllocator {
448    fn default() -> Self {
449        Self::new()
450    }
451}
452
453impl ResourceAllocator {
454    pub fn new() -> Self {
455        Self {
456            allocation_strategies: HashMap::new(),
457            resource_monitor: Arc::new(ResourceMonitor::new()),
458            allocation_history: Arc::new(std::sync::RwLock::new(VecDeque::new())),
459        }
460    }
461
462    pub fn allocate_resources_for_partitions(
463        &self,
464        _partitions: &[CircuitPartition],
465        nodes: &HashMap<NodeId, NodeInfo>,
466    ) -> Result<AllocationPlan> {
467        let mut allocations = HashMap::new();
468
469        for node_id in nodes.keys() {
470            allocations.insert(
471                node_id.clone(),
472                super::fault_tolerance::ResourceAllocation {
473                    allocated_qubits: vec![],
474                    memory_allocated_mb: 100,
475                    cpu_allocated_percentage: 50.0,
476                    network_bandwidth_allocated_mbps: 100.0,
477                },
478            );
479        }
480
481        Ok(AllocationPlan {
482            plan_id: Uuid::new_v4(),
483            allocations,
484            estimated_cost: 100.0,
485            estimated_execution_time: Duration::from_secs(10),
486            allocation_timestamp: Utc::now(),
487        })
488    }
489}
490
491impl Default for ResourceMonitor {
492    fn default() -> Self {
493        Self::new()
494    }
495}
496
497impl ResourceMonitor {
498    pub fn new() -> Self {
499        Self {
500            monitoring_agents: HashMap::new(),
501            monitoring_interval: Duration::from_secs(1),
502            resource_predictions: Arc::new(ResourcePredictor::new()),
503        }
504    }
505}
506
507impl Default for ResourcePredictor {
508    fn default() -> Self {
509        Self::new()
510    }
511}
512
513impl ResourcePredictor {
514    pub fn new() -> Self {
515        Self {
516            prediction_models: HashMap::new(),
517            training_scheduler: Arc::new(TrainingScheduler::new()),
518            model_evaluator: Arc::new(ModelEvaluator::new()),
519        }
520    }
521}
522
523impl Default for TrainingScheduler {
524    fn default() -> Self {
525        Self::new()
526    }
527}
528
529impl TrainingScheduler {
530    pub fn new() -> Self {
531        Self {
532            training_schedule: HashMap::new(),
533            auto_retraining: true,
534            performance_threshold: 0.9,
535        }
536    }
537}
538
539impl Default for ModelEvaluator {
540    fn default() -> Self {
541        Self::new()
542    }
543}
544
545impl ModelEvaluator {
546    pub fn new() -> Self {
547        Self {
548            evaluation_metrics: vec![
549                "accuracy".to_string(),
550                "precision".to_string(),
551                "recall".to_string(),
552            ],
553            cross_validation_folds: 5,
554            benchmark_datasets: HashMap::new(),
555        }
556    }
557}
quantrs2_device/quantum_network/distributed_protocols/implementations/metrics.rs

quantrs2_device/quantum_network/distributed_protocols/implementations/
metrics.rs
