Self-Balancing Decentralized Distributed Platform for Urban Traffic Simulation
|Title:||Self-Balancing Decentralized Distributed Platform for Urban Traffic Simulation||Authors:||Bragard, Quentin
Murphy, Liam, B.E.
|Permanent link:||http://hdl.handle.net/10197/8494||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 simulation; Dynamic load-balancing; Time-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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