Logo PTI
Polish Information Processing Society
Logo FedCSIS

Annals of Computer Science and Information Systems, Volume 5

Proceedings of the 2015 Federated Conference on Computer Science and Information Systems

Simulation as a Service: A Design Approach for large-scale Energy Network Simulations

Thomas Preisler, Tim Dethlefs, Wolfgang Renz

DOI: http://dx.doi.org/10.15439/2015F116

Citation: Proceedings of the 2015 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 5, pages 1765–1772 (2015)

Full text

Abstract. In the ongoing GEWISS project it is planned to implement a geographical heat information and simulation system. It shall provide a planning and simulation tool for the interlinking of urban development and district heat network development to support the political decision making process in the City of Hamburg. The system shall combine macroscopic and microscopic simulations to a co-simulation system. The simulation as a service approach is presented as a loosely- coupled scalable solution to realize large-scale energy network simulations. It is based on cloud computing technologies for the optimal utilization of computing resources in heterogeneous simulation-infrastructures. This approach can be used to realize simulation systems integrating Multi-Agent System (MAS) based simulations and other simulation technologies. For practical evaluation, two implementation approaches based on a MAS platform as a service-oriented solution will be presented and compared to an approach involving standard web-service technologies.

References

  1. T. Logenthiran, D. Srinivasan, and T. Z. Shun, “Demand side management in smart grid using heuristic optimization,” Smart Grid, IEEE Transactions on, vol. 3, no. 3, pp. 1244–1252, Sept 2012. http://dx.doi.org/10.1109/TSG.2012.2195686
  2. D. Rivola, A. Giusti, M. Salani, A. Rizzoli, R. Rudel, and L. Gambardella, “A decentralized approach to demand side load management: The swiss2grid project,” in Industrial Electronics Society, IECON 2013 - 39th Annual Conference of the IEEE, Nov 2013. http://dx.doi.org/10.1109/IECON.2013.6699895. ISSN 1553-572X pp. 4704–4709.
  3. T. Preisler, G. Balthasar, T. Dethlefs, and W. Renz, “Servicekomponenten-basierte architektur für mikroskopische und makroskopische simulation der städtischen energieversorgung,” in Proceedings of the German VDE-Congress, ser. Smart Cities, 2014.
  4. B. Sosinsky, Cloud computing bible. John Wiley & Sons, 2010.
  5. L. Braubach, A. Pokahr, and K. Jander, “Jadexcloud - an infrastructure for enterprise cloud applications,” in Multiagent System Technologies, ser. Lecture Notes in Computer Science, F. Klügl and S. Ossowski, Eds. Springer Berlin Heidelberg, 2011, vol. 6973, pp. 3–15. ISBN 978-3-642-24602-9. [Online]. Available: http://dx.doi.org/10.1007/978-3-642-24603-6_3
  6. B. Hindman, A. Konwinski, M. Zaharia, A. Ghodsi, A. D. Joseph, R. Katz, S. Shenker, and I. Stoica, “Mesos: A platform for fine-grained resource sharing in the data center,” in Proceedings of the 8th USENIX Conference on Networked Systems Design and Implementation, ser. NSDI’11. Berkeley, CA, USA: USENIX Association, 2011, pp. 295– 308. [Online]. Available: http://dl.acm.org/citation.cfm?id=1972457.1972488
  7. A. Abouzeid, K. Bajda-Pawlikowski, D. Abadi, A. Silberschatz, and A. Rasin, “Hadoopdb: An architectural hybrid of mapreduce and dbms technologies for analytical workloads,” Proceedings of the VLDB Endowment, vol. 2, no. 1, pp. 922–933, Aug. 2009.[Online]. Available: http://dx.doi.org/10.14778/1687627.1687731
  8. W. Gropp, E. Lusk, and A. Skjellum, Using MPI: portable parallel programming with the message-passing interface. MIT press, 1999, vol. 1.
  9. L. Braubach, K. Jander, and A. Pokahr, “A middleware for managing non-functional requirements in cloud paas,” in Cloud and Autonomic Computing (ICCAC), 2014 International Conference on, Sept 2014. http://dx.doi.org/10.1109/ICCAC.2014.32 pp. 83–92.
  10. S. Guo, F. Bai, and X. Hu, “Simulation software as a service and service-oriented simulation experiment,” in Information Reuse and Inte- gration (IRI), 2011 IEEE International Conference on, Aug 2011. http://dx.doi.org/10.1109/IRI.2011.6009531 pp. 113–116.
  11. E. Cayirci, “Modeling and simulation as a cloud service: A sur- vey,” in Simulation Conference (WSC), 2013 Winter, Dec 2013. http://dx.doi.org/10.1109/WSC.2013.6721436 pp. 389–400.
  12. T. Bitterman, P. Calyam, A. Berryman, D. E. Hudak, L. Li, A. Chalker, S. Gordon, D. Zhang, D. Cai, C. Lee et al., “Simulation as a service (smaas): a cloud-based framework to support the educational use of scientific software,” International Journal of Cloud Computing, vol. 3, no. 2, pp. 177–190, 2014.
  13. S. Schütte, S. Scherfke, and M. Sonnenschein, “Mosaik - smart grid simulation API - toward a semantic based standard for interchanging smart grid simulations,” in SMARTGREENS 2012 - Proceedings of the 1st International Conference on Smart Grids and Green IT Systems, Porto, Portugal, 19 - 20 April, 2012, B. Donnellan, J. A. P. Lopes, J. F. Martins, and J. Filipe, Eds. SciTePress, 2012. ISBN 978-989-8565-09-9 pp. 14–24.
  14. R. R. van Lon and T. Holvoet, “Rinsim: a simulator for collective adaptive systems in transportation and logistics,” in 2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems. IEEE, September 2012. http://dx.doi.org/10.1109/SASO.2012.41 pp. 231–232. [Online]. Available: lirias.kuleuven.be/handle/123456789/361419
  15. L. Braubach and A. Pokahr, “The jadex project: Simulation,” in Multiagent Systems and Applications, ser. Intelligent Systems Reference Library, M. Ganzha and L. C. Jain, Eds. Springer Berlin Heidelberg, 2013, vol. 45, pp. 107–128. ISBN 978-3-642-33322-4. [Online]. Available: http://dx.doi.org/10.1007/978-3-642-33323-1_5
  16. T. Preisler, G. Balthasar, T. Dethlefs, and W. Renz, “Scalable integration of 4gl-models and algorithms for massive smart grid simulations and applications,” in 28th International Conference on Informatics for Environmental Protection: ICT for Energy Effieciency, EnviroInfo 2014, Oldenburg, Germany, September 10-12, 2014., J. M. Gómez, M. Sonnenschein, U. Vogel, A. Winter, B. Rapp, and N. Giesen, Eds. BIS-Verlag, 2014. ISBN 978-3-8142-2317-9 pp. 341–348. [Online]. Available: http://www.enviroinfo2014.org/
  17. T. Preisler and W. Renz, “Scalability and robustness analysis of a multi-agent based self-healing resource-flow system,” in Federated Conference on Computer Science and Information Systems - FedCSIS 2012, Wroclaw, Poland, 9-12 September 2012, Proceedings, M. Ganzha, L. A. Maciaszek, and M. Paprzycki, Eds., 2012. ISBN 978-83-60810-51- 4 pp. 1261–1268. [Online]. Available: https://fedcsis.org/proceedings/2012/pliks/194.pdf
  18. S. I. S. Committee et al., “of the ieee computer society. ieee standard for modeling and simulation (m&s) high level architecture (hla)-ieee std 1516-2000, 1516.1-2000, 1516.2-2000. new york: Institute of electrical and electronics engineers,” Inc., New York, 2000.
  19. C. A. Boer, A. de Bruin, and A. Verbraeck, “Distributed simulation in industry-a survey part 3-the hla standard in industry,” in Simulation Conference, 2008. WSC 2008. Winter. IEEE, 2008, pp. 1094–1102.
  20. R. Nouvel, C. Schulte, U. Eicker, D. Pietruschka, and V. Coors, “Citygml-based 3d city model for energy diagnostics and urban energy policy support,” in Proceedings of the 13th conference of international Building Performance Simulation Association, 2013, pp. 218–25.
  21. R. Nouvel, M. Zirak, H. Dastageeri, V. Coors, and U. Eicker, “Urban energy analysis based on 3d city model for national scale applications,” in Presented at the IBPSA Germany Conference, vol. 8, 2014.
  22. G. Gröger, T. H. Kolbe, A. Czerwinski, and C. Nagel, “Opengis R city geography markup language (citygml) encoding standard. version: 1.0. 0, ogc 08-007r1,” 2012.
  23. S. Sicklinger, V. Belsky, B. Engelmann, H. Elmqvist, H. Olsson, R. Wüchner, and K.-U. Bletzinger, “Interface jacobian-based co-simulation,” International Journal for Numerical Methods in Engineering, vol. 98, no. 6, pp. 418–444, 2014. Available: http://dx.doi.org/10.1002/nme.4637
  24. A. Garro and A. Tundis, “On the reliability analysis of sys- tems and sos: The ramsas method and related extensions,” Sys- tems Journal, IEEE, vol. 9, no. 1, pp. 232–241, March 2015. http://dx.doi.org/10.1109/JSYST.2014.2321617
  25. J. Martin, Application Development Without Programmers. Upper Saddle River, NJ, USA: Prentice Hall PTR, 1982. ISBN 0130389439
  26. S. Beydeda, M. Bock, and V. Gruhn, Model-Driven Software Develop- ment. Springer Berlin Heidelberg, 2006. ISBN 978-3-540-25613-7
  27. J. Braunagel, P. Vuthi, W. Renz, H. Schäfers, H. Zarif, and H. Wiech- mann, “Determination of load schedules and load shifting potentials of a high number of electrical consumers using mass simulation,” in Electricity Distribution (CIRED 2013), 22nd International Conference and Exhibition on, June 2013. http://dx.doi.org/10.1049/cp.2013.1240 pp. 1–4.
  28. S. Moss and P. Davidsson, Multi-Agent-Based Simulation: Second International Workshop, MABS 2000, Boston, MA, USA, July 2000; Revised and Additional Papers, ser. Lecture Notes in Artificial Intelligence. Springer, 2001. ISBN 9783540415220