Add more code explanation, p execution details, paper reference, support for virtual environment, and errors are fixed.

Author: yangtaodeng

README.md

@@ -1,6 +1,9 @@
 #!/usr/bin/python
 # -*- coding: UTF-8 -*-
 
+# In this code, we assume the malicious terminals are positioned in certain regions
+# as described in Section IV.A
+
 import numpy as np
 import math
 import json

skyfall/aggregated_deployment_circle.py

@@ -1,6 +1,9 @@
 #!/usr/bin/python
 # -*- coding: UTF-8 -*-
 
+# In this code, we assume the malicious terminals are positioned in certain regions
+# as described in Section IV.A
+
 import numpy as np
 import math
 import json

skyfall/aggregated_deployment_grid.py

@@ -1,3 +1,6 @@
+# In this code, the vital GSes are ranked based on the three metrics from the paper ()
+# as described in the Analysis Stage (Section IV.C)
+
 import json
 import heapq
 import sys

skyfall/bottleneck_GS_rank.py

@@ -1,11 +1,13 @@
+# At a specific moment, analyze the traffic throughput of each link (ISLs and GSLs) under the network topology and traffic conditions.
+# Network Topology: User blocks connect to a satellite, and satellites forms Circles.
+# Traffic: Based on the Starlink traffic of each block from CloudFlare, flows probabilistically increasing by 0.5M each sampling time (ISL capacity 20Gbps; GSL Uplink/Downlink: 4Gbps).
+# as described in the experimental setting (Section V.A)
+
 import math
 import sys
 import numpy as np
 import random, json
 import os
-# At a specific moment, analyze the traffic throughput of each link (ISLs and GSLs) under the network topology and traffic conditions.
-# Network Topology: User blocks connect to a satellite, and satellites forms Circles.
-# Traffic: Based on the Starlink traffic of each block from CloudFlare, flows probabilistically increasing by 0.5M each sampling time (ISL capacity 20Gbps; GSL Uplink/Downlink: 4Gbps).
 
 # Constants
 RADIUS = 6371

skyfall/generate_flow_circle.py

@@ -1,11 +1,13 @@
+# At a specific moment, analyze the traffic throughput of each link (ISLs and GSLs) under the network topology and traffic conditions.
+# Network Topology: User blocks connect to a satellite, and satellites forms +Grid.
+# Traffic: Based on the Starlink traffic of each block from CloudFlare, flows probabilistically increasing by 0.5M each sampling time (ISL capacity 20Gbps; GSL Uplink/Downlink: 4Gbps).
+# as described in the experimental setting (Section V.A)
+
 import math
 import sys
 import numpy as np
 import random, json
 import os
-# At a specific moment, analyze the traffic throughput of each link (ISLs and GSLs) under the network topology and traffic conditions.
-# Network Topology: User blocks connect to a satellite, and satellites forms +Grid.
-# Traffic: Based on the Starlink traffic of each block from CloudFlare, flows probabilistically increasing by 0.5M each sampling time (ISL capacity 20Gbps; GSL Uplink/Downlink: 4Gbps).
 
 # Constants
 RADIUS = 6371

skyfall/generate_flow_grid.py

@@ -1,3 +1,6 @@
+# In this code, latitude, longitude and altitude of each satellite is generated for each time slot
+# as described in the experimental setting (Section V.A)
+
 from skyfield.api import load, wgs84, EarthSatellite
 from datetime import datetime
 from sgp4.api import Satrec, WGS84

skyfall/generate_lla.py

@@ -1,6 +1,9 @@
 #!/usr/bin/python
 # -*- coding: UTF-8 -*-
 
+# In this code, we analyze the risks and the variabilities, as described in the Analysis Stage (Section IV.C)
+# Specifically, the worst case under the Circular Structure is analyzed in this code.
+
 import numpy as np
 import math
 import os

skyfall/time_slot_analysis_circle.py

@@ -1,6 +1,9 @@
 #!/usr/bin/python
 # -*- coding: UTF-8 -*-
 
+# In this code, we analyze the risks and the variabilities, as described in the Analysis Stage (Section IV.C)
+# Specifically, the comparison under the Circular Structure is analyzed in this code.
+
 import numpy as np
 import math
 import os

skyfall/time_slot_analysis_circle_comparison.py

@@ -1,6 +1,9 @@
 #!/usr/bin/python
 # -*- coding: UTF-8 -*-
 
+# In this code, we analyze the risks and the variabilities, as described in the Analysis Stage (Section IV.C)
+# Specifically, the worst case under the +Grid Structure is analyzed in this code.
+
 import numpy as np
 import math
 import os