Digital Twin of 5G Network
Getting Started
Getting Started
Installation Guide
Use Cases
Normal Surfing
Video Streaming
Periodic Keep-Alive
Short Burst Sessions
Load Registration Anomaly
Authentication Failure Alert
Models
LSTM Model with Attention
LSTM BathNorm Model
LSTM Base Model
LSTM Robust Model
Classify the real data using LSTM
Data & Preprocessing
Exploratory Data Analysis
Label Real Dataset
Preprocess data for LSTM
Infrastructure
Simulate a running network
Main orchestrator
LINKS
💻 Source code
🐞 Report an issue
💬 Discussions
🏢 FIIT STU
Digital Twin of 5G Network
Index
Index
A
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B
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C
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E
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I
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L
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M
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N
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P
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R
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S
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T
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U
A
add_current_uc
module
apply_uc() (in module add_current_uc)
AttentionLayer (class in lstm_attention_model)
(class in lstm_results_real_data)
(class in network_watcher)
B
build() (lstm_attention_model.AttentionLayer method)
(lstm_results_real_data.AttentionLayer method)
(network_watcher.AttentionLayer method)
build_attention_model() (in module lstm_attention_model)
build_base_model() (in module lstm_base_model)
build_robust_model() (in module lstm_robust_model)
C
call() (lstm_attention_model.AttentionLayer method)
(lstm_results_real_data.AttentionLayer method)
(network_watcher.AttentionLayer method)
clean_old_models() (in module network_watcher)
compare_intervals() (in module add_current_uc)
compute_class_weights() (in module eda)
compute_output_shape() (lstm_attention_model.AttentionLayer method)
(lstm_results_real_data.AttentionLayer method)
(network_watcher.AttentionLayer method)
create_sequences() (in module lstm_preprocessing)
(in module lstm_results_real_data)
E
eda
module
evaluate_model() (in module lstm_results_real_data)
I
init_log() (in module running_network)
L
label_realnetwork_csv() (in module add_current_uc)
load_and_preprocess_data() (in module lstm_results_real_data)
load_data() (in module lstm_preprocessing)
load_dataset() (in module eda)
load_last_sequence() (in module network_watcher)
load_maps() (in module eda)
lstm_attention_model
module
lstm_base_model
module
lstm_bathnorm_model
module
lstm_preprocessing
module
lstm_results_real_data
module
lstm_robust_model
module
M
main_loop() (in module network_watcher)
module
add_current_uc
eda
lstm_attention_model
lstm_base_model
lstm_bathnorm_model
lstm_preprocessing
lstm_results_real_data
lstm_robust_model
network_watcher
running_network
uc1
uc2
uc3
uc4
uc5
uc6
N
network_watcher
module
P
parse_amf() (in module network_watcher)
permutation_importance_stable() (in module eda)
predict_current_uc() (in module network_watcher)
preprocess_data() (in module eda)
R
random_forest_importance() (in module eda)
remove_offset() (in module network_watcher)
rfe_selection() (in module eda)
rfecv_selection() (in module eda)
run_evaluation_and_finetuning() (in module lstm_results_real_data)
run_main_notebook_with_backup() (in module network_watcher)
run_notebook_in_thread() (in module network_watcher)
run_simulation() (in module running_network)
run_uc1() (in module uc1)
run_uc2() (in module uc2)
run_uc3() (in module uc3)
run_uc4() (in module uc4)
run_uc5() (in module uc5)
run_uc6() (in module uc6)
running_network
module
S
save_model_with_date() (in module network_watcher)
sfs_selection() (in module eda)
split_and_save_data() (in module lstm_preprocessing)
T
train_attention_model() (in module lstm_attention_model)
train_batchnorm_model() (in module lstm_bathnorm_model)
truncate_running_data() (in module network_watcher)
U
uc1
module
uc2
module
uc3
module
uc4
module
uc5
module
uc6
module