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A model driven engineering process of platform neutral agents for ambient intelligence devices

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Abstract

Ambient intelligence (AmI) systems are now considered a promising approach to assist people in their daily life. AmI proposes the development of context aware systems equipped with devices that can recognize your context and act accordingly. Agents provide an effective way to develop such systems since agents are reactive, proactive and exhibit an intelligent and autonomous behavior. However, current agent approaches do not adequately fulfill the requirements posed by AmI systems. From a modeling point of view, the aim should be to help in the design by providing adequate tools that assist in the development of important properties of AmI systems, such as context-awareness; and from an implementation point of view, agent technologies must be adapted to the diversity of AmI devices and communication technologies. As a solution to these issues we propose a Model driven engineering process, which supports the automatic generation of agent-based AmI systems. The source metamodel is PIM4Agents, a general purpose agent metamodel that we have adapted to support the explicit modeling of context aware systems, and the target metamodel is Malaca, an aspect-oriented agent architecture. Aspect-orientation makes Malaca platform-neutral for FIPA compliant agent platforms, simplifying the model driven process. The solution generates MalacaTiny agents, an implementation of Malaca that is able to run in AmI devices. We have evaluated the convenience of applying a model driven approach by measuring the degree of automation of our process and we have evaluated MalacaTiny for mobile phones by assessing different parameters, related to the scarcity of resources in AmI systems. All the results obtained are satisfactory.

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Notes

  1. Aspect Oriented Software Development, see http://www.aosd.net/

  2. http://www.eclipse.org/modeling/emf/?project=emf

  3. http://www.eclipse.org/atl/

  4. http://www.eclipse.org/gmt/mofscript/

  5. http://www.sunspotworld.com/

  6. http://www.android.com/

  7. http://symbian.nokia.com/

  8. http://en.wikipedia.org/wiki/Infrared_Data_Association

  9. http://en.wikipedia.org/wiki/Near_Field_Communication

  10. http://en.wikipedia.org/wiki/Wi-Fi_Direct

  11. http://www.fipa.org/

  12. http://www.htc.com/es/product/desire/specification.html

  13. http://www.samsung.com/global/microsite/galaxys/specification/spec.html?ver=high

  14. http://www.fipa.org/specs/fipa00027/

  15. http://www.fipa.org/specs/fipa00029/

  16. http://www.libelium.com.

References

  1. Agüero, J., Rebollo, M., Carrascosa, C., & Julián, V. (2010). Model-driven development for ubiquitous mas. In J. Augusto, J. Corchado, P. Novais, & C. Analide (Eds.), Ambient intelligence and future trends-international symposium on ambient intelligence (ISAmI 2010), advances in intelligent and soft computing (Vol. 72, pp. 87–95). Heidelberg: Springer.

  2. Aiello, F., Fortino, G., Gravina, R., & Guerrieri, A. (2011). A java-based agent platform for programming wireless sensor networks. The Computer Journal, 54(3), 439–454.

    Article  Google Scholar 

  3. Amor, M., & Fuentes, L. (2009). Malaca: A component and aspect-oriented agent architecture. Information and Software Technology, 51, 1052–1065.

    Article  Google Scholar 

  4. Augusto, J., & Nugent, C. (2004). The use of temporal reasoning and management of complex events in smart homes. In ECAI (Vol. 16, p. 778).

  5. Ayala, I., Amor, M., & Fuentes, L. (2010). A model driven development of platform-neutral agents. In J. Dix, & C. Witteveen (Eds.), Multiagent system technologies: 8th German conference, MATES 2010, Leipzig, Germany, September 27–29. Proceedings. Lecture notes in computer science (pp. 3–14) Heidelberg: Springer.

  6. Ayala, I., Amor, M., & Fuentes, L. (2010). Towards the automatic derivation of malaca agents using mde. In W. van der Haek et al. (Eds.), The eleventh international workshop on agent oriented software engineering. AOSE 2010. Toronto, Canada, 10 of May 2010 (pp. 61–72).

  7. Ayala, I., Amor, M., & Fuentes, L. (2012). ITMAS: An agent platform for self-configuring agents in the internet of things. In Third international workshop on infrastructures and tools for multiagent systems. (pp. 65–78).

  8. Ayala, I., Amor, M., & Fuentes, L. (2012) Self-management of ambient intelligence systems: a pure agent-based approach. In Proceedings of the 11th international conference on autonomous agents and multiagent systems–Vol. 3, AAMAS ’12 (pp. 1427–1428). Richland, SC: International Foundation for Autonomous Agents and Multiagent Systems.

  9. Bellifemine, F., Caire, G., Poggi, A., Rimassa, G. & Jade, A. (2008). A software framework for developing multi-agent applications. Lessons learned. Information and Software Technology, 50(1–2), 10–21.

    Google Scholar 

  10. Bergenti, F., & Poggi, A. (2002). Leap A fipa platform for handheld and mobile devices. In J. J. Meyer & M. Tambe (Eds.), Intelligent agents VIII. Lecture notes in computer science (Vol. 2333, pp. 436–446). Berlin: Springer.

    Google Scholar 

  11. Bromuri, S., Schumacher, M., & Stathis, K. (2010). Towards distributed agent environments for pervasive healthcare. In J. Dix & C. Witteveen (Eds.), Multiagent system technologies. Lecture notes in computer science (Vol. 6251, pp. 125–137). Berlin: Springer.

    Google Scholar 

  12. Brossard, A., Abed, M., & Kolski, C. (2011). Taking context into account in conceptual models using a model driven engineering approach. Information and Software Technology, 53(12), 1349–1369.

    Article  Google Scholar 

  13. Chen, B., & Cheng, H. (2010). A review of the applications of agent technology in traffic and transportation systems. IEEE Transactions on Intelligent Transportation Systems, 11(2), 485–497.

    Article  Google Scholar 

  14. Cook, D., Youngblood, M., & Das, S. (2006). A multi-agent approach to controlling a smart environment. In J. Augusto & C. Nugent (Eds.), Designing smart homes. Lecture notes in computer science (Vol. 4008, pp. 165–182). Heidelberg: Springer.

  15. Cook, D. J., Augusto, J. C., & Jakkula, V. R. (2009). Ambient intelligence: Technologies, applications, and opportunities. Pervasive and Mobile Computing, 5(4), 277–298.

    Article  Google Scholar 

  16. Cozza, R. (2010). Forecast: Mobile communications devices by open operating system, 2007–2014. http://www.gartner.com/resId=1428830

  17. Gascueña, J. M., Navarro, E., & Fernández-Caballero, A. (2012). Model-driven engineering techniques for the development of multi-agent systems. Engineering Applications of Artificial Intelligence, 25(1), 159–173.

    Article  Google Scholar 

  18. Giorgini, P., Mylopoulos, J., Perini, A., & Susi, A. (2005). The tropos metamodel and its use. Informatica, An International Journal of Computing and Informatics, 29(4), 251–273.

    Google Scholar 

  19. Hackborn, D. (2010). Service api changes starting with android 2.0. http://android-developers.blogspot.com/2010/02/service-api-changes-starting-with.html

  20. Hahn, C., Madrigal-Mora, C., & Fischer, K. (2009). A platform-independent metamodel for multiagent systems. Autonomous Agents and Multi-Agent Systems, 18, 239–266.

    Article  Google Scholar 

  21. Haigh, K. Z., Kiff, L. M., Myers, J., Guralnik, V., Geib, C. W., Phelps, J., & Wagner, T. (2004). The independent lifestyle assistant (i.l.s.a.): Ai lessons learned. In Proceedings of the 16th conference on innovative applications of artifical intelligence, IAAI’04 (pp. 852–857). AAAI Press.

  22. Harrington, A., & Cahill, V. (2011). Model-driven engineering of planning and optimisation algorithms for pervasive computing environments. Mobile & Pervasive Computing, 7(6), 705–726.

    Article  Google Scholar 

  23. Howden, N., Rönnquist, R., Hodgson, A., & Lucas, A. (2001). Intelligent agents—summary of an agent infrastructure. In 5th International conference on autonomous agents.

  24. Keegan, S., O’Hare, G., & O’Grady, M. (2008). Easishop: Ambient intelligence assists everyday shopping. Information Sciences, 178(3), 588–611.

    Article  Google Scholar 

  25. Koch, F., Meyer, J. J., Dignum, F., & Rahwan, I. (2006). Programming deliberative agents for mobile services: The 3apl-m platform. In R. Bordini, M. Dastani, J. Dix, & A. Fallah Seghrouchni (Eds.), Programming multi-agent systems. Lecture notes in computer science (Vol. 3862, pp. 222–235). Berlin: Springer.

  26. Lech, T. C., & Wienhofen, L. W. M. (2005). Ambieagents: A scalable infrastructure for mobile and context-aware information services. Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems, AAMAS ’05 (pp. 625–631). New York, NY: ACM.

  27. Lopes, R., Assis, F., & Montez, C. (2011). Maspot: A mobile agent system for sun spot. In 10th international symposium on autonomous decentralized systems (ISADS 2011) (pp. 25–31).

  28. Muñoz, M. A., Rodríguez, M., Favela, J., Martinez-Garcia, A. I., & González, V. M. (2003). Context-aware mobile communication in hospitals. Computer, 36(9), 38–46.

    Article  Google Scholar 

  29. Muldoon, C., O’Hare, G., Collier, R., & O’Grady, M. (2006). Agent factory micro edition: A framework for ambient applications. In V. Alexandrov, G. van Albada, P. Sloot, & J. Dongarra (Eds.), Computational science ICCS 2006, lecture notes in computer science (Vol. 3993, pp. 727–734). Heidelberg: Springer.

  30. Muldoon, C., O’Hare, G., O’Grady, M., & Tynan, R. (2008). Agent migration and communication in wsns. In Ninth international conference on parallel and distributed computing, applications and technologies, 2008 (pp. 425–430).

  31. Pavón, J., Gómez-Sanz, J., & Fuentes, R. (2006). Model driven development of multi-agent systems. In A. Rensink & J. Warmer (Eds.), Model driven architecture foundations and applications. Lecture notes in computer science (Vol. 4066, pp. 284–298). Heidelberg: Springer.

    Chapter  Google Scholar 

  32. Penserini, L., Bresciani, P., Kuflik, T., & Busetta, P. (2005). Using tropos to model agent based architectures for adaptive systems: A case study in ambient intelligence. In Proceedings of IEEE international conference on software–Science, technology and engineering (pp. 37–46).

  33. Ramos, C., Augusto, J. C., & Shapiro, D. (2008). Ambient intelligence the next step for artificial intelligence. IEEE Intelligent Systems, 23(2), 15–18.

    Article  Google Scholar 

  34. Sadri, F. (2011). Ambient intelligence: A survey. ACM Computing Surveys, 43(4), 1–36.

    Article  Google Scholar 

  35. Sánchez-Pi, N., Carbó, J., & Molina, J. (2008). Jade/leap agents in an aml domain. In E. Corchado, A. Abraham, & W. Pedrycz (Eds.), Hybrid artificial intelligence systems, lecture notes in computer science (Vol. 5271, pp. 62–69). Heidelberg: Springer.

    Chapter  Google Scholar 

  36. Sánchez-Pi, N., Mangina, E., Carbó, J., & Molina, J. (2010). Trends in practical applications of agents and multiagent systems advances in intelligent and soft computing. In Y. Demazeau, F. Dignum, J. Corchado, J. Bajo, R. Corchuelo, E. Corchado, F. Fernández-Riverola, V. Julián, P. Pawlewski, & A. Campbell (Eds.), Multi-agent system (mas) applications in ambient intelligence (ami) environments (Vol. 71, pp. 493–500). Berlin: Springer.

    Google Scholar 

  37. Schmidt, D. C. (2006). Guest editor’s introduction: Model-driven engineering. Computer, 39, 25–31.

    Article  Google Scholar 

  38. Spanoudakis, N., & Moraitis, P. (2010). Modular jade agents design and implementation using aseme. In IEEE/WIC/ACM international conference on web intelligence and intelligent agent technology (Vol. 2, pp. 221–228).

  39. Stock, O., Zancanaro, M., Busetta, P., Callaway, C., Krger, A., Kruppa, M., et al. (2007). Adaptive, intelligent presentation of information for the museum visitor in peach. User Modeling and User-Adapted Interaction, 17, 257–304.

    Article  Google Scholar 

  40. Tapia, D., Abraham, A., Corchado, J., & Alonso, R. (2010). Agents and ambient intelligence: case studies. Journal of Ambient Intelligence and Humanized Computing, 1, 85–93.

    Article  Google Scholar 

  41. Tarkoma, S., & Laukkanen, M. (2002). Supporting software agents on small devices. Proceedings of the first international joint conference on Autonomous agents and multiagent systems: Part 2, AAMAS’02 (pp. 565–566). New York, NY: ACM.

  42. Vinyals, M., Rodriguez-Aguilar, J. A., & Cerquides, J. (2011). A survey on sensor networks from a multiagent perspective. Computer Journal, 54(3), 455–470.

    Article  Google Scholar 

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Acknowledgments

This work has been funded by the Spanish Ministry Project RAP TIN2008-01942 and the regional project FamWare P09-TIC-5231.

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Correspondence to Inmaculada Ayala.

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Ayala, I., Amor, M. & Fuentes, L. A model driven engineering process of platform neutral agents for ambient intelligence devices. Auton Agent Multi-Agent Syst 28, 214–255 (2014). https://doi.org/10.1007/s10458-013-9223-3

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