ABSTRACT
This paper introduces a novel distributed computing environment designed as a simulation tool for the analysis of large and disaggregated data flows. Our research is based on a mapping between a large scale system, in which the interest of study is the modelling of disaggregated data flows, and a distributed computing environment, both being modelled as a graph. This distributed computing environment is a middleware that supports management and migration of computing objects. Its dynamic properties replicate the behaviour of large data flows, i.e., entities travelling between the different nodes of a graph. It also supports distribution and processing of objects at the appropriate level of granularity: the nodes of the computing graph. Such a property gives a high level of flexibility and scalability to the system, computing objects being distributed and processed at the local middleware level. The potential of our middleware is illustrated by a case study that simulates large passenger flows between the halls of an airport terminal.
- A. Bargiela. Strategic directions in simulation and modelling. Unpublished technical report, The Nottingham Trent University, January 2000. UK Computing Research Strategy Meeting.Google Scholar
- M. Batty, Y. Xie, and Z. Sun. Modelling urban dynamics through gis-based cellular automata. Computers Environment and Urban Systems, 23(1):205--233, 1999.Google ScholarCross Ref
- L. Bic, M. Fukuda, and M. Dillencourt. Distributed computing using autonomous objects. Computer, 29(8):55--61, 1996. Google ScholarDigital Library
- Y. Cheng. A rule-based reactive model for the simulation of aircraft on airport gates. Knowledge-Based Systems, 10(4):225--236, 1998.Google ScholarDigital Library
- M. Clarke and E. Holm. Microsimulation methods in spatial analysis and planning. Geogra ska Annaler, 69B:145--164, 1987.Google Scholar
- K. Erol, R. Levy, and J. Wentworth. Application of agent technology to traffic simulation. Unpublished technical report, U.S. Department of Transportation, McLean, Virginia, USA, 1999.Google Scholar
- J. Ferber. Multi-agents systems - an introduction to distributed artifcial intelligence. Reading, MA, Addison-Wesley, 1999. Google ScholarDigital Library
- M. Gatersleben and S. van der Wiej. Analysis and simulation of passenger ows in an airport terminal. In P. Farrington, H. Nembhand, J. Sturrock, and G. Evans, editors, Proc. of the Winter Simulation conference, pages 1226--1231, 1999. Google ScholarDigital Library
- M. Goodchild. Geographical information systems and disaggregate transportation modelling. Geographical Systems, 5(1-2):19--44, 1998.Google Scholar
- R. Guerraoui and S. Vinoski. Guest editorial. Distributed Systems Engineering, 4(3):129--130, 1997.Google ScholarCross Ref
- W. Maniatty, B. Szymanski, and T. Caraco. Implementation and performance of parallel ecological simulations. In Proc. of IFIP WG10.3 International Conference, Amsterdam, The Netherlands, 1993. Elsevier Science Publication. Google ScholarDigital Library
- T. Maxwell. An open geographic modeling environment. Simulation Journal, 68(3):175--185, 1997. Google ScholarDigital Library
- F. Merchant, L. Bic, P. Borst, M. Corbin, M. Dillencourt, M. Fukuda, and P. Sapaty. Simulating autonomous objects in a spatial database. In Proc. of the 9th European Simulation Multiconference, pages 768--773, Prague, Czech Republic, June 1995.Google Scholar
- E. Miller. Emerging themes and research frontiers in GIS and activity-based travel demand forecasting. Geographical Systems, 5:189--198, 1998.Google Scholar
- M. Nuttall. Survey of systems providing process or object migration. Technical Report 94/10, Imperial College London, May 1994.Google Scholar
- M. Pursula. Simulations of traffc systems: an overview. In Proc. of the 10th European Symposium in Simulation Systems, pages 20--24, Nottingham, UK, 1998. Society of Computer Simulation pub.Google Scholar
- C. Ray. Round Trip Bus: A protocol for migrating groups of objects. In 11th Ph.D. Workshop on Object Oriented System, 16th European Conference on Object-Oriented Programming (ECOOP 2001), 2001.Google Scholar
- C. Ray and C. Claramunt. Atlas: A novel distributed computing system for the simulation of disaggregated data ows. Technical report, IRENav - French Naval Academy, 2002.Google Scholar
- J. Setti. Passenger-terminal simulation model. Journal of Transportation Engineering, 20(4):517--534, 1994.Google ScholarCross Ref
- J. Stillwell, J. Geertman, and S. Openshaw. Geograhical information and planning. Advances in Spatial Science. Springer-Verlag, Heidelberg, Germany, 1999.Google Scholar
- A. Tanenbaum. Distributed systems anno 1992: What we have learned so far. Distributed Systems Engineering, 1(1):3--10, 1992.Google ScholarCross Ref
- D. Teretsch. Scheduling ights at hub airports. Transportation Research Part B, 27(2):133{150, 1993.Google Scholar
- M. Thériault, C. Claramunt, A.-M. Séguin, and P. Villeneuve. A spatio-temporal model for lifelines analysis. In Proc. of the Xth International Symposium on Spatial Data Handling, volume to appear. Springer-Verlag, 2002.Google Scholar
- C. Tunasar, G. Bender, and H. Young. Modelling curbside vehicular traffic at airports. In D. Medeiros, E. Watson, and M. Manivannan, editors, Proc. of the 1998 Winter Simulation Conference, pages 1113{1117, Piscataway, NJ, USA, 1998. IEEE. Google ScholarDigital Library
- A. Voisard and H. Schweppe. Abstraction and decomposition in interoperable GIS. Intl. Journal of Geographic Information Science (IJGIS), 12(4), 1998.Google Scholar
- B. Zeigler. Theory of modeling and simulation. Wiley and Sons, New York, 1976. Google ScholarDigital Library
Index Terms
- Atlas: a distributed system for the simulation of large-scale systems
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