SimulatorBridgerDfT: A Real-Data Simulator for IoT-Osmotic Interactions

Urban traffic simulation is crucial for improving traffic management by analyzing and optimizing urban mobility. Traditional VANET simulation tools, using traffic data from simulators like SUMO, lack real-world data integration. SimulatorBridgerDfT addresses this by extending SimulatorBridger to incorporate real-world traffic data from the UK’s Department for Transport (DfT). It processes diverse data formats, particularly CSV from the DfT, for more accurate urban traffic simulations. The research examines how real-world traffic data affects vehicular network communication times. Experiments show that SimulatorBridgerDfT accurately mirrors real-world traffic and reveals the impact of increased IoT device loads on network performance, emphasizing the need for effective smart city network management.

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Publication Details

Published
2024-12-13
DOI
https://doi.org/10.1145/3718391.3718429
Citations
1
Primary Topic
Time Series Analysis and Forecasting
Type
article
Field-Weighted Citation Impact
0.35
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article

SimulatorBridgerDfT: A Real-Data Simulator for IoT-Osmotic Interactions

Giacomo Bergami, Reham Almutairi, Graham Morgan
1 citations
Time Series Analysis and Forecasting
0.35
article

SimulatorBridgerDfT: A Real-Data Simulator for IoT-Osmotic Interactions

Giacomo Bergami, Reham Almutairi, Graham Morgan
article en
1 citations

Abstract

Urban traffic simulation is crucial for improving traffic management by analyzing and optimizing urban mobility. Traditional VANET simulation tools, using traffic data from simulators like SUMO, lack real-world data integration. SimulatorBridgerDfT addresses this by extending SimulatorBridger to incorporate real-world traffic data from the UK’s Department for Transport (DfT). It processes diverse data formats, particularly CSV from the DfT, for more accurate urban traffic simulations. The research examines how real-world traffic data affects vehicular network communication times. Experiments show that SimulatorBridgerDfT accurately mirrors real-world traffic and reveals the impact of increased IoT device loads on network performance, emphasizing the need for effective smart city network management.

University of Hafr Al-Batin (SA), Newcastle University (GB)
Affordable and clean energy
Openalex Percentile: Top 37%
Time Series Analysis and Forecasting
0.35
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