4 research outputs found

    Role of Ontology with Multi-Agent System in Cloud Computing

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    Information technology is playing a major role in revolutionizing how organizations operate, manage, as well as automate their processes. However, most of the systems today are not reusable because there is mixing the knowledge of the society and that of the processes. This is because the knowledge of societies is different from each other applications; hence, it is not reusable. This paper will address how dependent the applications are on societies, and it will separately define the processes of ontology, the knowledge of the agent, ontology of society, and the knowledge of the society [1]. This will be an introduction of ontology-based, process oriented, and an agent system that is independent of society that allows most if not all organizations to make use of it. This is by defining, as well as importing the ontology of the society and some process patterns, which may be instantiated from the ontology of the process into the system. This proposed system can be used on the platform of cloud computing. The evaluation is from two different perspectives: the quality of making use of the cohesion and the coupling measures. Coupling measures entails measuring the degree to which the system will focus on solving a problem in particular. Secondly, it focuses on the applicability, which is determined by evaluating how manageable and automobile the seven processes from three different societies are [2]

    Agreement technologies and their use in cloud computing environments

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    The final publication is available at Springer via http://dx.doi.org/10.1007/s13748-012-0031-9[EN] Nowadays, cloud computing is revolutionizing the services provided through the Internet to adapt itself in order to keep the quality of its services. Recent research foresees the advent of a new discipline of agent-based cloud computing systems that can make decisions about adaption in an uncertain environment. This paper discusses the role of argumentation in the next generation of agreement technologies and its use in cloud computing environments.This work is supported by the Spanish government (MICINN), project reference: TIN2012-36586-C03-01.Heras Barberá, SM.; De La Piedra, F.; Julian Inglada, VJ.; Rodríguez, S.; Botti Navarro, VJ.; Bajo, J.; Corchado, JM. (2012). Agreement technologies and their use in cloud computing environments. Progress in Artificial Intelligence. 1(4):277-290. https://doi.org/10.1007/s13748-012-0031-9S27729014European Comission: The Future of Cloud Computing. Technical report (2010)Barham, P., Dragovic, B., Fraser, K., Hand, S., Harris, T., Ho, A., Neugebauer, R., Pratt, I., Warfield, A.: Xen and the art of virtualization. In: SOSP03 Proceedings of the Nineteenth ACM Symposium on Operating Systems Principles, pp. 164–177. ACM, New York (2003)Wang, L., et. al.: Scientific cloud computing: early definition and experience. In: 10th IEEE International Conference on High Performance Computing and Communications (HPCC-08), pp. 825–830. IEEE Press (2008)Talia, D.: Clouds meet agents: toward intelligent cloud services. Internet Comput. IEEE 16(2), 78–81 (2012). doi: 10.1109/MIC.2012.28Heras, S.: Case-Based Argumentation Framework for Agent Societies. PhD thesis, Universitat Politècnica de València. http://hdl.handle.net/10251/12497 (2011)Ashton, K.: That ‘internet of things’ thing. RFID J. (2009). http://www.rfidjournal.com/article/view/4986Klusch, M.: Information agent technology for the Internet: a Survey. Data Knowl. Eng. 36, 337–372 (2001)Schaffer, H.E.: X as a Service. Cloud Computing, and the Need for Good Judgment IT Professional 11(5), 4–5 (2009). doi: 10.1109/MITP.2009.112Richardson, L., Ruby, S.: RESTful Web Services, Web services for the real world O’Reilly, Media, May, p. 454 (2007)GlusterFS Developers. The Gluster web site. http://www.gluster.org (2012)Chodorow, K., Dirolf, M.: The Definitive Guide. O’Reilly Media, MongoDB (2010)Fuentes-Fernandez, R., Hassan, S., Pavon, J., Galan, J.M., Lopez-Paredes, A.: Metamodels for role-driven agent-based modelling. Comput. Math. Organ. Theory 18(1), 91–112 (2012)Jordán, J., et al.: A customer support application using argumentation in multi-agent systems. In: 14th International Conference on, Information Fusion, pp. 772–778 (2011)Heras, S., Jordán, J., Botti, V., Julián, V.: Argue to agree: a case-based argumentation approach. Int. J. Approx. Reasoning (2012, in press)Walton, D., Reed, C., Macagno, F.: Argumentation Schemes. Cambridge University Press, Cambridge (2008)Bench-Capon, T., Sartor, G.: A model of legal reasoning with cases incorporating theories and values. Artif. Intell. 150(1–2), 97–143 (2003)Dignum, F., Weigand, H.: Communication and deontic logic. In: Information Systems Correctness and Reusability, pp. 242–260. World Scientific, Singapore (1995)Wooldridge, M., Jennings, N.R.: Intelligent agents: theory and practice. Knowl. Eng. Rev. 10(2), 115–152 (1995)Lopez-Rodriguez, I., Hernandez-Tejera, M.: Software agents as cloud computing services. In: 9th International Conference on Practical Applications of Agents and Multiagent Systems. Advances in Intelligent and Soft Computing, vol. 88, pp. 271–276. Springer, Berlin (2011)Sim, K.M.: Towards complex negotiation for cloud economy. In: 5th International Conference on Advances in Grid and Pervasive Computing. LNCS, vol. 6104, pp. 395–406. Springer, Berlin (2010)Aversa, R., et al.: Cloud agency: a mobile agent based cloud system. In: International Conference on Complex, Intelligent and Software Intensive Systems, pp. 132–137. IEEE Computer Society Press, Washington, DC (2010)Cao, B., et al.: A service-oriented qos-assured and multi-agent cloud computing architecture. In: 1st International Conference on Cloud Computing. LNCS, vol. 5931, pp. 644–649. Springer, Berlin (2009)Rahwan, I., Simari, G. (eds.): Argumentation in Artificial Intelligence. Springer, Berlin (2009

    Sistemas organizativos para la asignación dinámica de recursos computacionales en entornos distribuidos

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    [ES]Cloud Computing, el conocido paradigma computacional, está emergiendo en los últimos años con gran fuerza. Este paradigma incluye un novedoso modelo de comercialización basado en el pago por uso que ha cambiado radicalmente el modelo de negocio en Internet, lo que ha permitido que las empresas y usuarios individuales puedan alquilar los recursos computacionales que necesitan en cada momento. Este nuevo modelo computacional también ha derivado en que el modelo de producción de estos recursos computacionales evolucione hasta una aproximación cercana al modelo de producción just-in-time, en el que sólo se consumen los recursos necesarios para la producción de los servicios en función de la demanda existente en cada momento, hablándose dentro de este ámbito de elasticidad en los servicios ofertados. Para que esto sea posible, no cabe duda, que una gran cantidad de tecnologías subyacentes han tenido que madurar para dar como resultado un nicho tecnológico con la capacidad para variar los recursos asociados a cada servicio en función de la demanda. Sin embargo, pese a los indudables avances que se han producido a nivel tecnológico, todavía hoy existe una gran capacidad de mejora de estos sistemas. En este sentido, en el marco de esta tesis doctoral se propone el uso de los sistemas multiagente y, especialmente, aquellos basados en modelos organizativos para el control y monitorización de un sistema Cloud Computing. Gracias a esta aproximación, una de las primeras en este campo de investigación, será posible incluir en las plataformas Cloud de nueva generación características derivadas de la Inteligencia Artificial, como son la autonomía, la proactividad y, también, la capacidad de aprendizaje. Para ello se propone un modelo único en su concepción, que permite dotar a la organización de agentes inteligentes con capacidades auto-adaptativas en tiempo de ejecución para entornos abiertos, altamente dinámicos en los que, además, existe un cierto grado de incertidumbre. Así gracias a este modelo, el sistema es capaz de variar los recursos computacionales asociados a cada servicio producido en función de la demanda existe por parte de los usuarios, mediante la auto-adaptación dinámica del propio sistema en su conjunto
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