Traffic Modeling and Classification Using Packet Train Length and Packet Train Size

2006 ◽  
pp. 1-12 ◽  
Author(s):  
Dinil Mon Divakaran ◽  
Hema A. Murthy ◽  
Timothy A. Gonsalves
Keyword(s):  
Traffic Modeling ◽  
Packet Train ◽  
Train Length

Urban Traffic Modeling and Simulation: Moroccan Capital Case Study

2018 ◽  
Author(s):  
Aboutaib Brahim ◽  
Bahili Lahoucine ◽  
Fonlupt Cyril ◽  
Virginie Marion ◽  
Sebastiaan Verelst
Keyword(s):  
Modeling And Simulation ◽  
Urban Traffic ◽  
Traffic Modeling ◽  
Capital Case

scholarly journals IoT Traffic: Modeling and Measurement Experiments

IoT ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 140-162
Author(s):  
Hung Nguyen-An ◽  
Thomas Silverston ◽  
Taku Yamazaki ◽  
Takumi Miyoshi
Keyword(s):  
Smart Home ◽  
Large Scale ◽  
Traffic Modeling ◽  
The Novel ◽  
Network Behavior ◽  
Performance Accuracy ◽  
Traffic Generator ◽  
Multiple Devices ◽  
Iot Devices ◽  
The Internet Of Things

We now use the Internet of things (IoT) in our everyday lives. The novel IoT devices collect cyber–physical data and provide information on the environment. Hence, IoT traffic will count for a major part of Internet traffic; however, its impact on the network is still widely unknown. IoT devices are prone to cyberattacks because of constrained resources or misconfigurations. It is essential to characterize IoT traffic and identify each device to monitor the IoT network and discriminate among legitimate and anomalous IoT traffic. In this study, we deployed a smart-home testbed comprising several IoT devices to study IoT traffic. We performed extensive measurement experiments using a novel IoT traffic generator tool called IoTTGen. This tool can generate traffic from multiple devices, emulating large-scale scenarios with different devices under different network conditions. We analyzed the IoT traffic properties by computing the entropy value of traffic parameters and visually observing the traffic on behavior shape graphs. We propose a new method for identifying traffic entropy-based devices, computing the entropy values of traffic features. The method relies on machine learning to classify the traffic. The proposed method succeeded in identifying devices with a performance accuracy up to 94% and is robust with unpredictable network behavior with traffic anomalies spreading in the network.

Relative train length and the infrastructure required to mitigate delays from operating combinations of normal and over-length freight trains on single-track railway lines in North America

2018 ◽  
Vol 233 (7) ◽  
pp. 731-742 ◽  
Author(s):  
C Tyler Dick ◽  
Ivan Atanassov ◽  
F Bradford Kippen ◽  
Darkhan Mussanov
Keyword(s):  
North America ◽  
Simulation Software ◽  
Single Track ◽  
Delay Performance ◽  
Expansion Strategy ◽  
Train Operation ◽  
Heavy Haul ◽  
Directional Preference ◽  
Directional Distributions ◽  
Train Length

Distributed power locomotives have facilitated longer heavy-haul freight trains that improve the efficiency of railway operations. In North America, where the majority of mainlines are single track, the potential operational and economic advantages of long trains are limited by the inadequate length of many existing passing sidings (passing loops). To alleviate the challenge of operating trains that exceed the length of passing sidings, railways preserve the mainline capacity by extending passing sidings. However, industry practitioners rarely optimize the extent of infrastructure investment for the volume of over-length train traffic on a particular route. This paper investigates how different combinations of normal and over-length trains, and their relative lengths, relate to the number of siding extensions necessary to mitigate the delay performance of over-length train operation on a single-track rail corridor. The experiments used Rail Traffic Controller simulation software to determine train delay for various combinations of short and long train lengths under different directional distributions of a given daily railcar throughput volume. Simulation results suggest a relationship between the ratio of train lengths and the infrastructure expansion required to eliminate the delay introduced by operating over-length trains on the initial route. Over-length trains exhibit delay benefits from siding extensions while short trains are relatively insensitive to the expanded infrastructure. Assigning directional preference to over-length trains improves the overall average long-train delay at the expense of delay to short trains. These results will allow railway practitioners to make more informed decisions on the optimal incremental capital expansion strategy for the operation of over-length trains.

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