一个具备科研可验证性的 LoRa 多跳算法评估基线。

sim/main.py

@@ -27,6 +27,7 @@ def deploy_nodes(
     num_nodes: int = None,
     area_size: float = None,
     metrics_collector: MetricsCollector = None,
+    routing_type: str = "gradient",
 ) -> list:
     """
     Deploy nodes randomly in the area.
@@ -37,6 +38,7 @@ def deploy_nodes(
         num_nodes: Number of nodes (default from config)
         area_size: Area size (default from config)
         metrics_collector: Metrics collector for observability
+        routing_type: Type of routing ("gradient", "flooding", "random")
 
     Returns:
         List of Node objects
@@ -60,6 +62,7 @@ def deploy_nodes(
         channel=channel,
         is_sink=True,
         metrics_collector=metrics_collector,
+        routing_type=routing_type,
     )
     nodes.append(sink)
 
@@ -75,6 +78,7 @@ def deploy_nodes(
             y=y,
             channel=channel,
             metrics_collector=metrics_collector,
+            routing_type=routing_type,
         )
         nodes.append(node)
 
@@ -105,6 +109,7 @@ def run_simulation(
     area_size: float = None,
     sim_time: float = None,
     seed: int = None,
+    routing_type: str = "gradient",
 ) -> dict:
     """
     Run the LoRa network simulation.
@@ -114,6 +119,7 @@ def run_simulation(
         area_size: Area size in meters
         sim_time: Simulation time in seconds
         seed: Random seed for reproducibility
+        routing_type: Type of routing ("gradient", "flooding", "random")
 
     Returns:
         Simulation results including metrics
@@ -140,7 +146,7 @@ def run_simulation(
     if sim_time is None:
         sim_time = config.SIM_TIME
 
-    nodes = deploy_nodes(env, channel, num_nodes, area_size, metrics)
+    nodes = deploy_nodes(env, channel, num_nodes, area_size, metrics, routing_type)
 
     # Setup receive callbacks
     setup_receive_callback(nodes, channel)
@@ -175,6 +181,21 @@ def run_simulation(
 
     metrics.add_collision(channel.collision_count - initial_collisions)
 
+    # Get efficiency metrics from channel
+    efficiency = channel.get_efficiency_metrics()
+
+    # Calculate derived efficiency metrics
+    total_tx = efficiency["total_transmissions"]
+    total_received = len(metrics.metrics.received_packet_ids)
+
+    # TX cost: transmissions per successful delivery
+    tx_per_success = total_tx / total_received if total_received > 0 else float("inf")
+
+    # Airtime usage: percentage of simulation time
+    airtime_usage = (
+        (efficiency["total_airtime"] / sim_time * 100) if sim_time > 0 else 0
+    )
+
     # Get results
     results = {
         "config": {
@@ -182,8 +203,20 @@ def run_simulation(
             "area_size": area_size,
             "sim_time": sim_time,
             "seed": seed,
+            "routing_type": routing_type,
         },
         "metrics": metrics.get_metrics().get_summary(),
+        "efficiency": {
+            "total_transmissions": total_tx,
+            "total_airtime": round(efficiency["total_airtime"], 3),
+            "airtime_usage_percent": round(airtime_usage, 2),
+            "tx_per_success": round(tx_per_success, 2)
+            if tx_per_success != float("inf")
+            else -1,
+            "hello_transmissions": efficiency["hello_transmissions"],
+            "data_transmissions": efficiency["data_transmissions"],
+            "ack_transmissions": efficiency["ack_transmissions"],
+        },
         "topology": [],
     }
 
@@ -219,6 +252,7 @@ def main():
         f"Area: {results['config']['area_size']}m x {results['config']['area_size']}m"
     )
     print(f"Simulation time: {results['config']['sim_time']}s")
+    print(f"Routing: {results['config']['routing_type']}")
 
     print("\n--- Metrics ---")
     metrics = results["metrics"]
@@ -226,10 +260,16 @@ def main():
     print(f"Total received: {metrics['total_received']}")
     print(f"Packet Delivery Ratio: {metrics['pdr']}%")
     print(f"Average hops: {metrics['avg_hop']}")
-    print(f"Average retries: {metrics['avg_retries']}")
     print(f"Convergence time: {metrics['convergence_time']}s")
     print(f"Collisions: {metrics['collisions']}")
 
+    print("\n--- Efficiency Metrics ---")
+    eff = results["efficiency"]
+    print(f"Total transmissions: {eff['total_transmissions']}")
+    print(f"Total airtime: {eff['total_airtime']:.3f}s")
+    print(f"Airtime usage: {eff['airtime_usage_percent']:.2f}%")
+    print(f"TX per success: {eff['tx_per_success']}")
+
     print("\n--- Topology ---")
     for node_info in results["topology"]:
         parent_str = (