Multi-Agent Architecture with Support to Quality of Service and Quality of Control

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-15381-5_17Multi Agent Systems (MAS) are one of the most suitable frameworks for the implementation of intelligent distributed control system. Agents provide suitable flexibility to give support to implied heterogeneity in cyber-physical systems. Quality of Service (QoS) and Quality of Control (QoC) parameters are commonly utilized to evaluate the efficiency of the communications and the control loop. Agents can use the quality measures to take a wide range of decisions, like suitable placement on the control node or to change the workload to save energy. This article describes the architecture of a multi agent system that provides support to QoS and QoC parameters to optimize de system. The architecture uses a Publish-Subscriber model, based on Data Distribution Service (DDS) to send the control messages. Due to the nature of the Publish-Subscribe model, the architecture is suitable to implement event-based control (EBC) systems. The architecture has been called FSACtrlThe architecture described in this article is a part of the coordinated project SIDIRELI: Distributed Systems with Limited Resources. Control Kernel and Coordination. Education and Science Department, Spanish Government and FEDER funds.Poza-Lujan, J.; Posadas-Yagüe, J.; Simó Ten, JE. (2010). Multi-Agent Architecture with Support to Quality of Service and Quality of Control. En Intelligent Data Engineering and Automated Learning – IDEAL 2010. Springer Verlag (Germany). 137-144. doi:10.1007/978-3-642-15381-5_17S137144Lee, E.A.: Cyber Physical Systems: Design Challenges. In: 11th IEEE Symposium on Object Oriented Real-Time Distributed Computing, pp. 363–369 (2008)Siegel, J.: CORBA 3: Fundamentals and Programming. OMG (2000)FIPA. FIPA-QoS (2002), http://www.fipa.org/specs/fipa00094Object Management Group (OMG): Data Distribution Service for Real-Time Systems, v1.1. Document formal (2005-12-04)Posadas, J.L., Poza, J.L., Simó, J.E., Benet, G., Blanes, F.: Agent Based Distributed Architecture for Mobile Robot Control. Engineering Applications of Artificial Intelligence 21(6), 805–823 (2008)Aurrecoechea, C., Campbell, A.T., Hauw, L.: A Survey of QoS Architectures. Multimedia Systems Journal, Special Issue on QoS Architecture 6(3), 138–151 (1998)Pardo-Castellote, G.: OMG Data-Distribution Service: architectural overview. In: Proceedings of 23rd International Conference on Distributed Computing Systems Workshops, Providence, USA, vol. 19(22), pp. 200–206 (2003)International Telecommunication Union (ITU). Terms and Definitions Related to Quality of Service and Network Performance Including Dependability. ITU-T Recommendation E.800 (0894) (1994)Sánchez, J., Guarnes, M.Á., Dormido, S.: On the Application of Different Event-Based Sampling Strategies to the Control of a Simple Industrial Process. Sensors 9, 6795–6818 (2009)Dorf, R.C., Bishop, R.H.: Modern Control Systems, 11th edn. Prentice Hall, Englewood Cliffs (2008)Poza, J.L., Posadas, J.L., Simó, J.E.: Middleware with QoS Support to Control Intelligent Systems. In: 2th International Conference on Advanced Engineering Computing and Applications in Sciences, ADVCOMP, pp. 211–216 (2008)Poza, J.L., Posadas, J.L., Simó, J.E.: From the Queue to the Quality of Service Policy: A Middleware Implementation. In: Omatu, S., Rocha, M.P., Bravo, J., Fernández, F., Corchado, E., Bustillo, A., Corchado, J.M. (eds.) IWANN 2009. LNCS, vol. 5518, pp. 432–437. Springer, Heidelberg (2009

Quality of service and quality of control based protocol to distribute agents

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-14883-5_10This paper describes an agent s movement protocol. Additionally, a distributed architecture to implement such protocol is presented. The architecture allows the agents to move in accordance with their requirements. The protocol is based on division and fusion of the agents in their basic components called Logical Sensors. The movement of the agents is based on the quality of services (QoS) and quality of control (QoC) parameters that the system can provides. The protocol is used to know the impact that the movement of the agents may have on the system and obtain the equilibrium points where the impact is minimal.The architecture described in this article is a part of the coordinated project SIDIRELI: Distributed Systems with Limited Resources. Control Kernel and Coordination. Education and Science Department, Spanish Government. CICYT: MICINN: DPI2008-06737-C02-01/02.Poza-Lujan, J.; Posadas-Yagüe, J.; Simó Ten, JE. (2010). Quality of service and quality of control based protocol to distribute agents. En Distributed Computing and Artificial Intelligence: 7th International Symposium. Springer. 73-80. doi:10.1007/978-3-642-14883-5_10S7380Posadas, J.L., Poza, J.L., Simó, J.E., Benet, G., Blanes, F.: Agent Based Distributed Architecture for Mobile Robot Control. In: Engineering Applications of Artificial Intelligence, vol. 21(6), pp. 805–823. Pergamon Press Ltd., Oxford (2008)Object Management Group (OMG): Data Distribution Service for Real-Time Systems, v1.1. Document formal / 2005-12-04 (2005)Odum, E.P.: Fundamentals of Ecology, 3rd edn. W.B. Saunders Company, Philadelphia (1971)Aurrecoechea, C., Campbell, A.T., Hauw, L.: A Survey of QoS Architectures. ACM/Springer Verlag Multimedia Systems Journal, Special Issue on QoS Architecture 6(3), 138–151 (1998)Pardo-Castellote, G.O.: Data-Distribution Service: architectural overview. In: Proceedings of 23rd International Conference on Distributed Computing Systems Workshops, vol. 19-22, pp. 200–206 (2003)International Telecommunication Union (ITU). Terms and Definitions Related to Quality of Service and Network Performance Including Dependability. ITU-T Recommendation E.800 (0894) (1994)Foundation for Intelligent Physical Agents. FIPA Quality of Service Ontology Specification, Experimental Doc: XC00094 (2002)Dorf, R.C., Bishop, R.H.: Modern Control Systems, 11th edn. Prentice Hall, Englewood Cliffs (2008)Poza, J.L., Posadas, J.L., Simó, J.E.: Middleware with QoS Support to Control Intelligent Systems. In: 2nd International Conference on Advanced Engineering Computing and Applications in Sciences, ADVCOMP, pp. 211–216 (2008)Bellifemine, F., Poggi, A., Rimassa, G.: Jade: A FIPA-compliant agent framework. In: Proceedings of PAAM 1999, pp. 97–108 (1999)Poza, J.L., Posadas, J.L., Simó, J.E.: From the Queue to the Quality of Service Policy: A Middleware Implementation. In: Omatu, S., Rocha, M.P., Bravo, J., Fernández, F., Corchado, E., Bustillo, A., Corchado, J.M. (eds.) IWANN 2009. Part II. LNCS, vol. 5518, pp. 432–437. Springer, Heidelberg (2009)Foundation for Intelligent Physical Agents. FIPA Agent Management Specification, Doc: FIPA00023 (2000)Jeong, B., Cho, H., Kulvatunyou, B., Jones, A.: A Multi-Criteria Web Services Composition Problem. In: Proceedings of the IEEE International Conference on Information Reuse and Integration, 2007 (IRI 2007), pp. 379–384. IEEE, Los Alamitos (2007)Poza, J.L., Posadas, J.L., Simó, J.E., Benet, G.: Distributed Agent Specification for an Intelligent control Architecture. In: 6th International Workshop on Practical Applications of Agents and Multiagent Systems. IWPAAMS (2007) ISBN 978-84-611-8858-

Technology Ventures. Management dell'imprenditorialità e dell'innovazione.

Alla stregua degli imprenditori, che sovente innovano ricombinando idee e conoscenze consolidate, ci si è posti l’obiettivo di trattare in modo differente temi classici affrontati dalle principali teorie manageriali sulla creazione e gestione delle iniziative d’impresa. In particolare, gli argomenti vengono sviluppati utilizzando un approccio metodologico che integra senza soluzione di continuità la presentazione di modelli e concetti generali con il riferimento ad esempi e applicazioni a realtà aziendali più o meno conosciute, utili per chiarire e arricchire la trattazione con contenuti e contestualizzazioni pratiche, maturate con l’esperienza diretta e coraggiosa di imprenditori e manager “in prima linea” in ambiti settoriali diversificati. I materiali contenuti nel libro propongono anche strumenti e metodiche tecniche immediatamente “spendibili” per avviare e sviluppare con maggiore consapevolezza e fiducia “avventure” imprenditoriali ad alto rischio di insuccesso come quelle che appartengono alla “grande famiglia” delle iniziative ad elevato contenuto di innovazione tecnologica. Con l’ausilio di casi ed esemplificazioni pratiche si è dato il necessario risalto alla differenze fra genialità scientifica e creatività imprenditoriale, tra talento visionario e capacità manageriale, tra speranza e realtà, attingendo ad un bagaglio di testimonianze emblematiche di elevata notorietà ed assoluto valore, che sono riuscite ad affermarsi e a crescere consolidando equilibri strutturali ed economico-finanziari soddisfacenti per tutti gli stakeholder interessati alle attività aziendali