Self-Balancing Decentralized Distributed Platform for Urban Traffic Simulation

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Title: Self-Balancing Decentralized Distributed Platform for Urban Traffic Simulation
Authors: Bragard, Quentin
Ventresque, Anthony
Murphy, Liam, B.E.
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Date: May-2017
Abstract: Microscopic traffic simulation is the most accurate tool for predictive analytics in urban environments. However, the amount of workload (i.e., cars simulated simultaneously) can be challenging for classical systems, particularly for scenarios requiring faster than real-time processing (e.g., for emergency units having to make quick decisions on traffic management). This challenge can be tackled with distributed simulations by sharing the load between simulation engines running on different computing nodes, hence balancing the processing power required. This paper studies the performance of dSUMO, i.e., a distributed microscopic traffic simulator. dSUMO is fully decentralized and can dynamically balance the workload between its computing nodes, hence showing important improvements against classical, centralized and not dynamic, solutions.
Funding Details: Science Foundation Ireland
Type of material: Journal Article
Publisher: IEEE
Copyright (published version): 2016 IEEE
Keywords: Distributed simulationDynamic load-balancingTime-stepped simulation
DOI: 10.1109/TITS.2016.2603171
Language: en
Status of Item: Peer reviewed
Appears in Collections:Computer Science Research Collection
PEL Research Collection

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