quantrs2_device/quantum_network/distributed_protocols/implementations/
load_balancers.rs

1//! Load balancer implementations for distributed quantum computation
2
3use super::super::types::*;
4use async_trait::async_trait;
5use std::collections::HashMap;
6use std::sync::{Arc, Mutex, RwLock};
7use std::time::Duration;
8use uuid::Uuid;
9
10#[async_trait]
11impl LoadBalancer for RoundRobinBalancer {
12    fn select_nodes(
13        &self,
14        partitions: &[CircuitPartition],
15        available_nodes: &HashMap<NodeId, NodeInfo>,
16        _requirements: &ExecutionRequirements,
17    ) -> Result<HashMap<Uuid, NodeId>> {
18        let mut assignments = HashMap::new();
19        let nodes: Vec<_> = available_nodes.keys().cloned().collect();
20
21        if nodes.is_empty() {
22            return Err(DistributedComputationError::ResourceAllocation(
23                "No available nodes".to_string(),
24            ));
25        }
26
27        for partition in partitions {
28            let mut index = self
29                .current_index
30                .lock()
31                .expect("Round-robin index mutex poisoned");
32            let selected_node = nodes[*index % nodes.len()].clone();
33            *index += 1;
34            assignments.insert(partition.partition_id, selected_node);
35        }
36
37        Ok(assignments)
38    }
39
40    fn rebalance_load(
41        &self,
42        _current_allocation: &HashMap<Uuid, NodeId>,
43        _nodes: &HashMap<NodeId, NodeInfo>,
44    ) -> Option<HashMap<Uuid, NodeId>> {
45        None // Round robin doesn't need rebalancing
46    }
47
48    fn predict_execution_time(&self, partition: &CircuitPartition, _node: &NodeInfo) -> Duration {
49        partition.estimated_execution_time
50    }
51
52    async fn select_node(
53        &self,
54        available_nodes: &[NodeInfo],
55        _requirements: &ResourceRequirements,
56    ) -> Result<NodeId> {
57        if available_nodes.is_empty() {
58            return Err(DistributedComputationError::ResourceAllocation(
59                "No available nodes".to_string(),
60            ));
61        }
62
63        let mut index = self
64            .current_index
65            .lock()
66            .expect("Round-robin index mutex poisoned");
67        let selected_node = available_nodes[*index % available_nodes.len()]
68            .node_id
69            .clone();
70        *index += 1;
71        Ok(selected_node)
72    }
73
74    async fn update_node_metrics(
75        &self,
76        _node_id: &NodeId,
77        _metrics: &PerformanceMetrics,
78    ) -> Result<()> {
79        Ok(()) // Round robin doesn't use metrics
80    }
81
82    fn get_balancer_metrics(&self) -> LoadBalancerMetrics {
83        LoadBalancerMetrics {
84            total_decisions: 0,
85            average_decision_time: Duration::from_millis(1),
86            prediction_accuracy: 1.0,
87            load_distribution_variance: 0.0,
88            total_requests: 0,
89            successful_allocations: 0,
90            failed_allocations: 0,
91            average_response_time: Duration::from_millis(0),
92            node_utilization: HashMap::new(),
93        }
94    }
95}
96
97impl Default for RoundRobinBalancer {
98    fn default() -> Self {
99        Self::new()
100    }
101}
102
103impl RoundRobinBalancer {
104    pub fn new() -> Self {
105        Self {
106            current_index: Arc::new(Mutex::new(0)),
107        }
108    }
109}
110
111/// Capability-based load balancer
112#[derive(Debug)]
113pub struct CapabilityBasedBalancer {
114    pub capability_weights: HashMap<String, f64>,
115    pub performance_history: Arc<RwLock<HashMap<NodeId, PerformanceHistory>>>,
116}
117
118/// ML-optimized load balancer
119#[derive(Debug)]
120pub struct MLOptimizedBalancer {
121    pub model_path: String,
122    pub feature_extractor: Arc<FeatureExtractor>,
123    pub prediction_cache: Arc<Mutex<HashMap<String, NodeId>>>,
124    pub training_data_collector: Arc<TrainingDataCollector>,
125}
126
127/// Training data collector for ML models
128#[derive(Debug)]
129pub struct TrainingDataCollector {
130    pub data_buffer: Arc<Mutex<std::collections::VecDeque<TrainingDataPoint>>>,
131    pub collection_interval: Duration,
132    pub max_buffer_size: usize,
133}
134
135impl Default for CapabilityBasedBalancer {
136    fn default() -> Self {
137        Self::new()
138    }
139}
140
141impl CapabilityBasedBalancer {
142    pub fn new() -> Self {
143        let mut capability_weights = HashMap::new();
144        capability_weights.insert("qubit_count".to_string(), 0.3);
145        capability_weights.insert("gate_fidelity".to_string(), 0.4);
146        capability_weights.insert("connectivity".to_string(), 0.3);
147
148        Self {
149            capability_weights,
150            performance_history: Arc::new(RwLock::new(HashMap::new())),
151        }
152    }
153}
154
155#[async_trait]
156impl LoadBalancer for CapabilityBasedBalancer {
157    fn select_nodes(
158        &self,
159        partitions: &[CircuitPartition],
160        available_nodes: &HashMap<NodeId, NodeInfo>,
161        _requirements: &ExecutionRequirements,
162    ) -> Result<HashMap<Uuid, NodeId>> {
163        let mut allocation = HashMap::new();
164
165        for partition in partitions {
166            if let Some((node_id, _)) = available_nodes.iter().next() {
167                allocation.insert(partition.partition_id, node_id.clone());
168            }
169        }
170
171        Ok(allocation)
172    }
173
174    fn rebalance_load(
175        &self,
176        _current_allocation: &HashMap<Uuid, NodeId>,
177        _nodes: &HashMap<NodeId, NodeInfo>,
178    ) -> Option<HashMap<Uuid, NodeId>> {
179        None // No rebalancing needed in simplified implementation
180    }
181
182    fn predict_execution_time(&self, partition: &CircuitPartition, _node: &NodeInfo) -> Duration {
183        Duration::from_millis(partition.gates.len() as u64 * 10)
184    }
185
186    async fn select_node(
187        &self,
188        available_nodes: &[NodeInfo],
189        requirements: &ResourceRequirements,
190    ) -> Result<NodeId> {
191        // Select the first available node that meets requirements
192        available_nodes
193            .iter()
194            .find(|node| {
195                node.capabilities.max_qubits >= requirements.qubits_needed
196                    && node
197                        .capabilities
198                        .gate_fidelities
199                        .values()
200                        .all(|&fidelity| fidelity >= 0.999) // Default threshold (equivalent to error rate <= 0.001)
201            })
202            .map(|node| node.node_id.clone())
203            .ok_or_else(|| {
204                DistributedComputationError::NodeSelectionFailed(
205                    "No suitable node found".to_string(),
206                )
207            })
208    }
209
210    async fn update_node_metrics(
211        &self,
212        _node_id: &NodeId,
213        _metrics: &PerformanceMetrics,
214    ) -> Result<()> {
215        // Update metrics for the specified node
216        // In a real implementation, this would update internal state
217        Ok(())
218    }
219
220    fn get_balancer_metrics(&self) -> LoadBalancerMetrics {
221        LoadBalancerMetrics {
222            total_decisions: 0,
223            average_decision_time: Duration::from_millis(1),
224            prediction_accuracy: 1.0,
225            load_distribution_variance: 0.0,
226            total_requests: 0,
227            successful_allocations: 0,
228            failed_allocations: 0,
229            average_response_time: Duration::from_millis(0),
230            node_utilization: HashMap::new(),
231        }
232    }
233}
quantrs2_device/quantum_network/distributed_protocols/implementations/load_balancers.rs

quantrs2_device/quantum_network/distributed_protocols/implementations/
load_balancers.rs
