Abstract
Large cities around the world face numerous challenges to guarantee the quality of life of its citizens. A promising approach to cope with these problems is the concept of Smart Cities, of which the main idea is the use of Information and Communication Technologies to improve city services. Being able to simulate the execution of Smart Cities scenarios would be extremely beneficial for the advancement of the field. Such a simulator, like many others, would need to represent a large number of various agents (e.g. cars, hospitals, and gas pipelines). One possible approach for doing this in a computer system is to use the actor model as a programming paradigm so that each agent corresponds to an actor. The Erlang programming language is based on the actor model and is the most commonly used implementation of it. In this paper, we present the first version of InterSCSimulator, an open-source, extensible, large-scale Traffic Simulator for Smart Cities developed in Erlang, capable of simulating millions of agents using a real map of a large city. Future versions will be extended to address other Smart City domains.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
Open Street Maps—http://www.openstreetmap.org.
- 2.
Google Maps—http://maps.google.com.
- 3.
OD Matrix—https://goo.gl/DNM8in.
- 4.
OMNET++ - https://omnetpp.org.
- 5.
SUMO—http://sumo.dlr.de.
- 6.
Mesoscopic Traffic Models simulate each vehicle in transit, but with fewer details than a microscopic model. They often use a density function to determine the vehicle’s speed in a street.
- 7.
Celluloid—https://celluloid.io/.
- 8.
Reactors.io—http://reactors.io/.
- 9.
Ericsson—https://www.ericsson.com/.
- 10.
WhatsApp—https://goo.gl/If6k3d.
- 11.
- 12.
Erlang Digraph API—http://erlang.org/doc/man/digraph.html.
- 13.
- 14.
Origin-Destination Survey—https://goo.gl/DNM8in.
References
Caragliu, A., Del Bo, C., Nijkamp, P.: Smart cities in Europe. J. Urban Technol. 18, 65–82 (2011)
Sanchez, L., Muñoz, L., Galache, J.A., Sotres, P., Santana, J.R., Gutierrez, V., Pfisterer, D.: SmartSantander: IoT experimentation over a smart city testbed. Comput. Netw. 61, 217–238 (2014)
Zanella, A., Bui, N., Castellani, A., Vangelista, L., Zorzi, M.: Internet of things for smart cities. IEEE Internet Things J. 1, 22–32 (2014)
Grimaldi, D., Fernandez, V.: The alignment of University curricula with the building of a Smart City: a case study from Barcelona. Technol. Forecast. Soc. Change 123, 298–306 (2016)
Horni, A., Nagel, K., Axhausen, K.W.: The Multi-Agent Transport Simulation MATSim. Ubiquity, London (2016)
Burghout, W., Koutsopoulos, H.N., Andreasson, I.: A discrete-event mesoscopic traffic simulation model for hybrid traffic simulation. In: IEEE Intelligent Transportation Systems Conference (2006)
Picone, M., Amoretti, M., Zanichelli, F.: Simulating smart cities with DEUS. In: International ICST Conference on Simulation Tools and Techniques (2012)
Darus, M.Y., Bakar, K.A.: Congestion control algorithm in VANETs. World Appl. Sci. J. 21, 1057–1061 (2013)
Nazário, D.C., Tromel, I.V.B., Dantas, M.A.R., Todesco, J.L.: Toward assessing quality of context parameters in a ubiquitous assisted environment. In: IEEE Symposium on Computers and Communication (ISCC), June 2014
Balmer, M., Meister, K., Nagel, K.: Agent-Based Simulation of Travel Demand: Structure and Computational Performance of MATSim-T. ETH Zürich IVT Institut für Verkehrsplanung und Transportsysteme, Zürich (2008)
Toscano, L., D’Angelo, G., Marzolla, M.: Parallel discrete event simulation with Erlang. In: ACM SIGPLAN Workshop on Functional High-Performance Computing (2012)
Song, T., Kaleshi, D., Zhou, R., Boudeville, O., Ma, J.X., Pelletier, A., Haddadi, I.: Performance evaluation of integrated smart energy solutions through large-scale simulations. In: Smart Grid Communications (2011)
Anderson, J.C., Lehnardt, J., Slater, N.: CouchDB: The Definitive Guide. O’Reilly Media Inc., Sebastopol (2010)
Di Stefano, A., Santoro, C.: eXAT: an experimental tool for programming multi-agent systems in Erlang. In: WOA (2003)
Varela, C., Abalde, C., Castro, L. Gulias, J.: On modeling agent systems with Erlang. In: ACM SIGPLAN Workshop on Erlang (2004)
Krzywicki, D., Stypka, J., Anielski, P., Turek, W., Byrski, A., Kisiel-Dorohinicki, M.: Generation-free agent-based evolutionary computing. Proc. Comput. Sci. 29, 1068–1077 (2014)
McCabe, S., Brearcliffe, D., Froncek, P., Hansen, M., Kane, V., Taghawi-Nejad, D., Axtell, R.: A comparison of languages and frameworks for the parallelization of a simple agent model. In: Workshop, Multi-Agent-Based Simulation (MABS) (2016)
Tasharofi, S., Dinges, P., Johnson, R.E.: Why do scala developers mix the actor model with other concurrency models? In: Castagna, G. (ed.) ECOOP 2013. LNCS, vol. 7920, pp. 302–326. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-39038-8_13
Song, X., Xie, Z., Xu, Y., Tan, G., Tang, W., Bi, J., Li, X.: Supporting real-world network-oriented mesoscopic traffic simulation on GPU. Simul. Model. Pract. Theory 74, 46–63 (2017)
Agha, G.A.: Actors: A Model of Concurrent Computation in Distributed Systems. Massachusetts Institute of Technology, Cambridge (1985)
Xuesong, Z., Jeffrey, T.: DTALite: a queue-based mesoscopic traffic simulator for fast model evaluation and calibration. Cogent Eng. (2014)
Chenfeng, X., Xuesong, Z., Lei, Z.: AgBM-DTALite: an integrated modelling system of agent-based travel behaviour and transportation network dynamics. Travel Behav. Soc. (2017)
Acknowledgments
This research is part of the INCT of the Future Internet for Smart Cities funded by CNPq, proc. 465446/2014-0, CAPES proc. 88887.136422/2017-00, and FAPESP, proc. 2014/50937-1 and was partially funded by Hewlett Packard Enterprise (HPE).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Santana, E.F.Z., Lago, N., Kon, F., Milojicic, D.S. (2018). InterSCSimulator: Large-Scale Traffic Simulation in Smart Cities Using Erlang. In: Dimuro, G., Antunes, L. (eds) Multi-Agent Based Simulation XVIII. MABS 2017. Lecture Notes in Computer Science(), vol 10798. Springer, Cham. https://doi.org/10.1007/978-3-319-91587-6_15
Download citation
DOI: https://doi.org/10.1007/978-3-319-91587-6_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-91586-9
Online ISBN: 978-3-319-91587-6
eBook Packages: Computer ScienceComputer Science (R0)