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International Journal of Distributed Sensor Networks
Volume 2012 (2012), Article ID 193864, 15 pages
Research Article

A Mobile Computing Framework for Pervasive Adaptive Platforms

1LIRMM UMR 5506, Université Montpellier 2, CNRS, 161 Rue ADA, 34095 Montpellier Cedex 5, France
2Département des Systèmes d'Information, Faculté des Hautes Études Commerciales, Université de Lausanne, 1015 Lausanne, Switzerland
3LEAD-UMR 5022, Université de Bourgogne, CNRS, Pôle AAFE, Esplanade ERASME, BP 26513, 21065 Dijon Cedex, France

Received 15 June 2011; Accepted 16 September 2011

Academic Editor: Yuhang Yang

Copyright © 2012 Olivier Brousse et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. Perplexus, Pervasive computing platform for modeling complex virtually-unbounded systems, 2009, http://www.perplexus.org/.
  2. J. Peňa, O. Jorand, H. Volken, and A. Pèrez-Uribe, “A connectionist, embodied and situated agent-based approach for studying the dissemination of culture,” CESABM, UNIL.
  3. O. Chibirova, J. Iglesias, V. Shaposhnyk, and A. E. P. Villa, “Dynamics of firing patterns in evolvable hierarchically organized neural networks,” Lecture Notes in Computer Science, vol. 5216, pp. 296–307, 2008. View at Publisher · View at Google Scholar · View at Scopus
  4. Intel corp., “Intel xscale microarchitecture,” Tech. Rep., 2000. View at Google Scholar
  5. Y. Thoma and A. Upegui, “Specification of bio-inspired features to be supported by the device,” hEIG-VD, Yverdon, Switzerland, Internal Report, 2006.
  6. A. Upegui, Y. Thoma, E. Sanchez, A. Perez-Uribe, J. M. Moreno, and J. Madrenas, “The perplexus bio-inspired chip,” in Proceedings of the 2nd NASA/ESA Conference on Adaptive Hardware and Systems(AHS '07), IEEE Computer Society, 2007.
  7. J. M. Moreno, “Specification of the ubicell,” Tech. Rep., Barcelona, Spain, UPC, Internal Report, 2006.
  8. IETFMANET work group, “Mobile Ad-Hoc networks (MANET),” April 2009, http://www.ietf.org/html.charters/manet-charter.html.
  9. C. E. Perkins and E. M. Royer, “Ad-Hoc on-demande distance vector,” December 1998.
  10. D. Johnson and D. Maltz, “The dynamic source routing protocol (dsr) for mobile ad hoc networks for ipv4,” February 2007.
  11. P. Jacquet, P. Mühlethaler, T. Clausen, A. Laouiti, A. Qayyum, and L. Viennot, Optimized Link State Routing Protocol for Ad-Hoc Networks, INRIA Roquencourt, HiPERCOM project, 2001.
  12. T. Clausen, P. Jacquet, and L. Viennot, Comparative study of CBR and TCP performance of MANET routing protocols, Workshop MESAINRIA Roquencourt, HiPERCOM project.
  13. A. Huhtonen, “Comparing AODV and OLSR routing protocols,” Seminar on Internetworking.
  14. A. TØnnesen, Impementing and extending the optimized link state routing protocol, Tech. Rep., M.S. thesis, UniK University Graduate Center University of Oslo, 2004.
  15. F. de Rango, M. Fotino, and S. Marano, “Ee-olsr: energy efficient olsr routing protocol for mobile ad-hoc networks,” in Proceedings of the Military Communications Conference (MILCOM '08), San Diego, Calif, USA, November 2008. View at Publisher · View at Google Scholar · View at Scopus
  16. F. D. Rango, J. C. Cano, M. Fotino, C. Calafate, P. Manzoni, and S. Marano, “OLSR vs DSR: a comparative analysis of proactive and reactive mechanisms from an energetic point of view in wireless ad hoc networks,” Computer Communications, vol. 31, no. 16, pp. 3843–3854, 2008. View at Publisher · View at Google Scholar · View at Scopus
  17. C. Taddia, A. Giovanardi, and G. Mazzini, “Energy efficiency in OLSR protocol,” in Proceedings of the 3rd Annual IEEE Communications Society on Sensor and Ad Hoc Communications and Networks (SECON '06), pp. 792–796, Reston, Va, USA, September 2006. View at Publisher · View at Google Scholar · View at Scopus
  18. Y. Shoham, “Agent-oriented programming,” Journal of Artificial Intelligence, vol. 60, no. 1, pp. 123–129, 1996. View at Google Scholar
  19. L. Gong, “Jxta: a network programming environment,” Internet Computing Online, vol. 5, pp. 88–95, 2002. View at Google Scholar
  20. The XLattice Project, “Kademlia: a design specification,” Tech. Rep., The XLattice Project, 2003, http://xlattice.sourceforge.net/components/protocol/kademlia/specs.html. View at Google Scholar
  21. F. L. Bellifemine, G. Caire, and D. Greenwood, Developing Multi-Agent Systems with JADE, Wiley Series in Agent Technology, Wiley, 2007.
  22. FIPA-OS project, FIPA-OS Agent Toolkit, FIPA-OS project , 2007, http://sourceforge.net/projects/fipa-os.
  23. F. Strauss, J. Schönwälder, and S. Mertens, Jax—a java agent x subagent toolkit, July 2000.
  24. G. Nguyen, T. Dang, L. Hluchy, M. Laclavik, Z. Balogh, and I. Budinska, “Agent platform evaluation and comparison,” Slovak Academy of Sciences, Institute of Informatics, Pellucid 5FP IST-2001-34519, 2002.
  25. Wikipedia, Xscale, http://en.wikipedia.org/wiki/XScale#PXA27x.
  26. J. Lawrence, LEAP into Ad-Hoc Networks, ACM Workshop on Agents in Ubiquitous and Wearable Computing, AAMAS.
  27. M. Schoeberl, Evaluation of a Java Processor, Vienna University of Technology.
  28. D. Hardin, “aj-100: a low-power java processor,” Embedded Processor Forum.
  29. ARM, “Jazelle—arm architecture extention for java applications,” white paper, 2002.
  30. J. Maassen, T. Kielmann, and H. E. Bal, “Parallel application experience with replicated method invocation,” Concurrency Computation Practice and Experience, vol. 13, no. 8-9, pp. 681–712, 2001. View at Google Scholar
  31. T. Brecht, H. S., M. Shan, and J. Talbot, “Paraweb: towards world-wide supercomputing,” in Proceedings of the European Symposium on Operating System Principles, pp. 181–186, 1996.
  32. GNU.org, “The gnu operating system,” June 2009, http://www.gnu.org/software/bison/.
  33. M. Hauptvogel, J. Madrenas, and J. M. Moreno, “Spindek: an integrated design tool for the multiprocessor emulation of complex bioinspired spiking neural networks, submitted to congress on evolutionary computation,” IEEE CEC, 2009.
  34. L. P. Kaelbling, M. L. Littman, and A. W. Moore, “Reinforcement learning: a survey,” Journal of Artificial Intelligence Research, vol. 4, pp. 237–285, 1996. View at Google Scholar · View at Scopus