Event Management Proposal for Distribution Data Service Standard

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-00551-5_32This paper presents a proposal to extend the event management subsystem of the Distribution Data Service standard (DDS). The proposal allows user to optimize the use of DDS in networked control systems (NCS). DDS offers a simple event management system based on message filtering. The aim of the proposal is to improve the event management with three main elements: Events, Conditions and Actions. Actions are the new element proposed. Actions perform basic operations in the middleware, discharging the process load of control elements. The proposal is fully compatible with the standard and can be easily added to an existing system. Proposal has been tested in a distributed mobile robot navigation system with interesting results.The study described in this paper is a part of the coordinated project COBAMI: Mission-based Hierarchical Control. Education and Science Department, Spanish Government. CICYT: MICINN: DP1201 1-28507-C02-01/02.Poza-Lujan, J.; Posadas-Yagüe, J.; Simó Ten, JE. (2013). Event Management Proposal for Distribution Data Service Standard. En Distributed Computing and Artificial Intelligence. Springer. 259-266. https://doi.org/10.1007/978-3-319-00551-5_32S259266Sánchez, 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)Sandee, J.H., Heemels, W.P.M.H., van den Bosch, P.P.J.: Case Studies in Event-Driven Control. In: Bemporad, A., Bicchi, A., Buttazzo, G. (eds.) HSCC 2007. LNCS, vol. 4416, pp. 762–765. Springer, Heidelberg (2007)Hadim, S., Nader, M.: Middleware Challenges and Approaches for Wireless Sensor Networks. IEEE Distributed Systems Online 7(3) (2006)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)Object Management Group. Data Distribution Service for Real-time Systems Version 1.2 (2007), http://www.omg.org/Dorf, R.C., Bishop, R.H.: Modern Control Systems, 11th edn. Prentice Hall (2008)Poza-Luján, J., Posadas-Yagüe, J., Simó-Ten, J.: Quality of Service and Quality of Control Based Protocol to Distribute Agents. In: DCAI, pp. 73–80 (2010)Waldbusser, S.: RFC 2819 - Remote Network Monitoring Management Information Base. Network Working Group. Lucent Technologies (2000)Poza-Luján, J., Posadas-Yagüe, J., Simó-Ten, J.: Relationship between Quality of Control and Quality of Service in Mobile Robot Navigation. In: DCAI, pp. 557–564 (2012)K-Team Corporation. Khepera III robot, http://www.k-team.comBraitenberg, V.: Vehicles: Experiments on Synthetic Psychology. MIT Press, Cambridge (1984)Poza-Luján, J.: Propuesta de arquitectura distribuida de control inteligente basada en políticas de calidad de servicio. Universitat Politècnica de València Press (2012

A survey on quality of service support on middelware-based distributed messaging systems used in multi agent systems

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-19934-9_10Messaging systems are widely used in distributed systems to hide the details of the communications mechanism to the multi agents systems. However, the Quality of Service is treated in different way depending on the messaging system used. This article presents a review and further analysis of the quality of service treatment in the mainly messaging systems used in distributed multi agent systems. The review covers the issues related to the purpose of the functions provided and the scope of the quality of service offered by every messaging system. We propose ontology for classifying and decide which parameters are relevant to the user. The results of the analysis and the ontology can be used to select the most suitable messaging system to distributed multi agent architecture and to establish the quality of service requirements in a distributed system.The study 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 European FEDER found. CICYT: MICINN: DPI2008-06737-C02-01/02.Poza-Lujan, J.; Posadas-Yagüe, J.; Simó Ten, JE. (2011). A survey on quality of service support on middelware-based distributed messaging systems used in multi agent systems. En International Symposium on Distributed Computing and Artificial Intelligence. Springer. 77-84. https://doi.org/10.1007/978-3-642-19934-9_10S7784Gaddah, A., Kunz, T.: A survey of middleware paradigms for mobile computing. Technical Report SCE-03-16. Carleton University Systems and Computing Engineering (2003)Foundation for Intelligent Physical Agents, http://www.fipa.org/Java Message Service Specification, http://java.sun.com/products/jms/docs.htmlCommon Object Request Broker Architecture, http://www.corba.org/Data Distribution Service, http://portals.omg.org/dds/Java Agent DEvelopment Framework, http://jade.tilab.com/Agent Oriented Software Pty Ltd., JACK Intelligent Agents: User Guide (1999)Nwana, H., Ndumu, D., Lee, L., Collis, J.: ZEUS: A tool-kit for building distributed multi-agent systems. Applied Artifical Intelligence Journal 13(1), 129–186 (1999)Perdikeas, M.K., Chatzipapadopoulos, F.G., Venieris, I.S., Marino, G.: Mobile Agent Standards and Available Platforms. Computer Networks Journal, Special Issue on ’Mobile Agents in Intelligent Networks and Mobile Communication Systems’ 31(10) (1999)Perrone, P.J., Chaganti, K.: J2EE Developer’s Handbook. Sam’s Publishing, Indianapolis (2003)Apache ActiveMQ, http://activemq.apache.org/IBM WebSphere MQSeries, http://mqseries.net/Object Management Group, http://www.omg.org/RTI Data Distribution Service. RTI corp., http://www.rti.com/OpenSplice DDS. PrismTech Ltd., http://www.prismtech.comVogel, A., Kerherve, B., von Bochmann, G., Gecsei, J.: Distributed Multimedia and QoS: A Survey. IEEE Multimedia 2(2), 10–19 (1995)Crawley, E., Nair, R., Rajagopalan, B.: RFC 2386: A Framework for QoS-based Routing in the Internet. IETF Internet Draft, 1–37 (1998)Foundation for Intelligent Physical Agents. FIPA Quality of Service Ontology Specification. Doc: SC00094A (2002)Sun Microsystems, Inc. Java(TM) Message Service Specification Final Release 1.1 (2002)Object Management Group (OMG). The Common Object Request Broker Architecture and Specification. CORBA 2.4.2 (2001

A Reinvented Education in Business and Accounting using a GBL Approach for soft skills

[EN] The vulnerable, dynamic and digitalizing working environments of the 2020s obviously propose new types of `newcomer¿ skills. The character of these `soft skills¿ is inherent, whereby their learning forms a challenge for educators. Researchers around the world are on the same question: how to make the learning tools and rebuilt the classroom (virtual and face-to-face) in order to cope with this digital generation? This change needs to incorporate new Skills; these skills, called Core Skills, are changing the way to teach and to learn. Motivation is the essential key to have in mind. Creating mind-sets under a strong cognitive engagement is education for the future of professionals. Gamification, Game-Based Learning (GBL), Simulations, Virtual classrooms, digital platforms with contents and many other methods are in use all around the world to change, with motivation, the perspective of students towards their own learning path. The VUCA (volatility, uncertainty, complexity and ambiguity) world brought Higher Education Institutions the discussion of the future for an education of excellence. This article intends to present a case study as a solution to combine Simulation and GBL to promote the Core Skills that students and teachers need to achieve success on the process of teaching and learning. The solution is innovative due to the main scope: the perfect connection of humanity and empathy through the use of Simulation-GBL in higher educational institutions.Part of this work was supported by the Erasmus+ program of the European Commission under Grant 2017-1-ES01-KA203- 038589 in the frame of the project CoSki21- Core Skills for 21th-century professionals. The authors would like to thank the people who have collaborated with the research answering the questionnaires.Bastos, S.; Silva, M.; Poza-Lujan, J.; Schleutker, K. (2020). A Reinvented Education in Business and Accounting using a GBL Approach for soft skills. Academic Conferences International Limited Reading, UK. 55-66. https://doi.org/10.34190/GBL.20.047S556

Relationship between quality of control and quality of service in mobile robot navigation

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-28765-7_67This article presents the experimental work developed to test the viability and to measure the efficiency of an intelligent control distributed architecture. To do this, a simulated navigation scenario of Braitenberg vehicles has been developed. To test the efficiency, the architecture uses the performance as QoS parameter. The measuring of the quality of the navigation is done through the ITAE QoC parameter. Tested scenarios are: an environment without QoS and QoC man-aging, an environment with a relevant message filtering and an environment with a predictive filtering by the type of control. The results obtained show that some of the processing performed in the control nodes can be moved to the middleware to optimize the robot navigation.The work described in this article is a part of the coordinated project SIDIRELI: (Distributed Systems with Limited Resources) and COBAMI (Mission-Based Control) Education and Science Department, Spanish Government and European FEDER found. MICINN CICYT: SIDIRELI: DPI2008-06737-C02-01/02, COBAMI: DPI2011-28507-C02-02.Poza-Lujan, J.; Posadas-Yagüe, J.; Simó Ten, JE. (2012). Relationship between quality of control and quality of service in mobile robot navigation. En Distributed Computing and Artificial Intelligence: 9th International Conference. Springer. 557-564. https://doi.org/10.1007/978-3-642-28765-7_67S557564Vogel, A., Kerherve, B., von Bochmann, G., Gecsei, J.: Distributed Multimedia and QoS: A Survey. IEEE Multimedia 2(2), 10–19 (1995)Crawley, E., Nair, R., Rajagopalan, B.: RFC 2386: A Framework for QoS-based Routing in the Internet. IETF Internet Draft, 1–37 (1998)Bradner, S.: RFC 2026: The Internet Standards Process. IETF Internet Draft, sec.10 (1996)Object Management Group (OMG): Data Distribution Service for Real-Time Systems, v1.1. Document formal (April 12, 2005)Poza, J.L., Posadas, J.L., Simó, J.E.: QoS-based middleware architecture for distributed control systems. In: International Symposium on Distributed Computing and Artificial Intelligence. DCAI, Salamanca, Spain (2008)Poza, J.L., Posadas, J.L., Simó, J.E.: A Survey on Quality of Service Support on Middleware-Based Distributed Messaging Systems Used in Multi Agent Systems. In: 9th International Conference on Practical Applications of Agents and Multi-Agent Systems. DCAI, Salamanca, Spain (2011)Dorf, R.C., Bishop, R.H.: Modern Control Systems, 11th edn. Prentice Hall (2008)Soucek, S., Sauter, T.: Quality of Service Concerns in IPBased Control Systems. IEEE Transactions on Industrial Electronics 51(6) (December 2004)Poza, J.L., Posadas, J.L., Simó, J.E.: Multi-Agent Architecture with Support to Quality of Service and Quality of Control. In: 11th International Conference on Intelligent Data Engineering and Automated Learning, Paisley, UK (2010)Braitenberg, V.: Vehicles: Experiments on Synthetic Psychology. MIT Press, Cambridge (1984)Gabel, O., Litz, L.: QoS-adaptive Control in NCS with Variable Delays and Packet Losses – A Heuristic Approach. In: 43rd IEEE Conference on Decision and Control (2004)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

A Game-Theory method to design job rotation schedules to prevent musculoskeletal disorders Based on workers preferences and competencies

[EN] Job rotation is an organizational strategy based on the systematic exchange of workers between jobs in a planned manner according to specific criteria. This study presents the GS-Rot method, a method based on Game Theory, in order to design job rotation schedules by considering not only workers' job preferences, but also the competencies required for different jobs. With this approach, we promote workers' active participation in the design of the rotation plan. It also let us deal with restrictions in assigning workers to job positions according to their disabilities (temporal or permanent). The GS-Rot method has been implemented online and applied to a case in a work environment characterized by the presence of a high repetition of movements, which is a significant risk factor associated with work-related musculoskeletal disorders (WMSDs). A total of 17 workstations and 17 workers were involved in the rotation, four of them with physical/psychological limitations. Feasible job rotation schedules were obtained in a short time (average time 27.4 milliseconds). The results indicate that in the rotations driven by preference priorities, almost all the workers (94.11%) were assigned to one of their top five preferences. Likewise, 48.52% of job positions were assigned to workers in their top five of their competence lists. When jobs were assigned according to competence, 58.82% of workers got an assignment among their top five competence lists. Furthermore, 55.87% of the workers achieved jobs in their top five preferences. In both rotation scenarios, the workers varied performed jobs, and fatigue accumulation was balanced among them. The GS-Rot method achieved feasible and uniform solutions regarding the workers' exposure to job repetitiveness.This research was funded by the Erasmus+ program of the European Commission under Grant 2017-1-ES01-KA203-038589 in the frame of the project CoSki21-Core Skills for 21th-century professionals.Asensio-Cuesta, S.; Garcia-Gomez, JM.; Poza-Lujan, J.; Conejero, JA. (2019). A Game-Theory method to design job rotation schedules to prevent musculoskeletal disorders Based on workers preferences and competencies. International Journal of Environmental research and Public Health. 16(23):1-16. https://doi.org/10.3390/ijerph16234666S1161623Aptel, M., Cail, F., Gerling, A., & Louis, O. (2008). Proposal of parameters to implement a workstation rotation system to protect against MSDs. International Journal of Industrial Ergonomics, 38(11-12), 900-909. doi:10.1016/j.ergon.2008.02.006Jeon, I. S., Jeong, B. Y., & Jeong, J. H. (2016). Preferred 11 different job rotation types in automotive company and their effects on productivity, quality and musculoskeletal disorders: comparison between subjective and actual scores by workers’ age. Ergonomics, 59(10), 1318-1326. doi:10.1080/00140139.2016.1140816Botti, L., Mora, C., & Calzavara, M. (2017). Design of job rotation schedules managing the exposure to age-related risk factors. IFAC-PapersOnLine, 50(1), 13993-13997. doi:10.1016/j.ifacol.2017.08.2420Sixth European Working Conditions Survey-6th EWCS-Spainhttps://www.eurofound.europa.eu/surveys/european-working-conditions-surveys/sixth-european-working-conditions-survey-2015/ewcs-2015-methodologyAsensio-Cuesta, S., Diego-Mas, J. A., Canós-Darós, L., & Andrés-Romano, C. (2011). A genetic algorithm for the design of job rotation schedules considering ergonomic and competence criteria. The International Journal of Advanced Manufacturing Technology, 60(9-12), 1161-1174. doi:10.1007/s00170-011-3672-0Yoon, S.-Y., Ko, J., & Jung, M.-C. (2016). A model for developing job rotation schedules that eliminate sequential high workloads and minimize between-worker variability in cumulative daily workloads: Application to automotive assembly lines. Applied Ergonomics, 55, 8-15. doi:10.1016/j.apergo.2016.01.011Otto, A., & Scholl, A. (2012). Reducing ergonomic risks by job rotation scheduling. OR Spectrum, 35(3), 711-733. doi:10.1007/s00291-012-0291-6Carnahan, B. J., Redfern, M. S., & Norman, B. (2000). Designing safe job rotation schedules using optimization and heuristic search. Ergonomics, 43(4), 543-560. doi:10.1080/001401300184404Song, J., Lee, C., Lee, W., Bahn, S., Jung, C., & Yun, M. H. (2016). Development of a job rotation scheduling algorithm for minimizing accumulated work load per body parts. Work, 53(3), 511-521. doi:10.3233/wor-152232Boenzi, F., Digiesi, S., Facchini, F., & Mummolo, G. (2016). Ergonomic improvement through job rotations in repetitive manual tasks in case of limited specialization and differentiated ergonomic requirements. IFAC-PapersOnLine, 49(12), 1667-1672. doi:10.1016/j.ifacol.2016.07.820Sana, S. S., Ospina-Mateus, H., Arrieta, F. G., & Chedid, J. A. (2018). Application of genetic algorithm to job scheduling under ergonomic constraints in manufacturing industry. Journal of Ambient Intelligence and Humanized Computing, 10(5), 2063-2090. doi:10.1007/s12652-018-0814-3Burgess-Limerick, R. (2018). Participatory ergonomics: Evidence and implementation lessons. Applied Ergonomics, 68, 289-293. doi:10.1016/j.apergo.2017.12.009Bhuiyan, B. A. (2018). An Overview of Game Theory and Some Applications. Philosophy and Progress, 111-128. doi:10.3329/pp.v59i1-2.36683Gale, D., & Shapley, L. S. (1962). College Admissions and the Stability of Marriage. The American Mathematical Monthly, 69(1), 9-15. doi:10.1080/00029890.1962.11989827Roth, A. E. (2008). What Have We Learned from Market Design? The Economic Journal, 118(527), 285-310. doi:10.1111/j.1468-0297.2007.02121.xRoth, A. E., & Sotomayor, M. (1992). Chapter 16 Two-sided matching. Handbook of Game Theory with Economic Applications, 485-541. doi:10.1016/s1574-0005(05)80019-0Renna, P. (2017). Decision-making method of reconfigurable manufacturing systems’ reconfiguration by a Gale-Shapley model. Journal of Manufacturing Systems, 45, 149-158. doi:10.1016/j.jmsy.2017.09.005Butkovič, P., & Lewis, S. (2007). On the job rotation problem. Discrete Optimization, 4(2), 163-174. doi:10.1016/j.disopt.2006.11.00

Optimizations on semantic environment management: an application for humanoid robot home assistance

© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This article introduces some optimization mechanisms focused on environment management, object recognition, and environment interaction. Although the generality of the presented system, this work will be focused on its application on home assistance humanoid robots. For this purpose, a generic environment formalization procedure for semantic scenery description is introduced. As the main contribution of this work, some techniques for a more efficient use of the environment knowledge are proposed. That way, the application of an areabased discrimination mechanism will avoid to process large amounts of data, useless in the current context, improving the object recognition, and characterizing the available interactions in the current area. Finally, the formalized description, and the optimization procedure, will be tested and verified on a specific home scenario using a humanoid robotThis work has been supported by the Spanish Science and Innovation Ministry MICINN under the CICYT project COBAMI: DPI2011-28507-C02-01/02. The responsibility for the content remains with the authors.Munera Sánchez, E.; Posadas-Yagüe, J.; Poza-Lujan, J.; Blanes Noguera, F.; Simó Ten, JE. (2014). Optimizations on semantic environment management: an application for humanoid robot home assistance. En 2014 IEEE-RAS International Conference on Humanoid Robots. IEEE. 720-725. doi:10.1109/HUMANOIDS.2014.7041442S72072

Integrating Smart Resources in ROS-based systems to distribute services

[EN] Mobile robots execute complexes tasks that involve the management of several embedded sensors and actuators. Therefore, in many cases, a robot is characterized as an intelligent distributed system formed with a central unit, which manages the on-board embedded devices and distributes the tasks execution. Embedded devices are also evolving to more complex systems. These systems are developed not only for executing simple tasks but also for offering some advanced mechanisms. Thus, complex data processing, adaptive execution, or fault-tolerance routines are some common system features. The Smart Resource topology has been developed in order to manage these embedded systems. This topology offers high-level routines that rely on a certain physical hardware execution. Therefore, Smart Resources are defined as distributed services providers, which operates within some context and quality requirements. Provided services can adapt its execution in order accomplish the set requirements and maximize the system performance. How to improve the versatility of the Smart Resources by making their services compatibles with the Robot Operating System (ROS) is addressed along this work. This solution integrates all the execution mechanisms provided by ROS with the service distribution, adaptive execution, and fault-tolerance routines offered by the Smart Resources. This integration is tested through a set of experiments using the Turtlebot robot platform and a simulated version of it. In both approaches ROS mechanisms are used to access the Smart Resource Services. Finally, obtained results are used to characterize the performance of this proposal.Work supported by the Spanish Science and Innovation Ministry MICINN: CICYT project M2C2: "Codiseno de sistemas de control con criticidad mixta basado en misiones" TIN2014-56158-C4-4-P and PAID (Polytechnic University of Valencia): UPV-PAID-FPI-2013.Munera-Sánchez, E.; Poza-Lujan, J.; Posadas-Yagüe, J.; Simó Ten, JE.; Blanes Noguera, F. (2017). Integrating Smart Resources in ROS-based systems to distribute services. Advances in Distributed Computing and Artificial Intelligence Journal. 6(1):13-19. https://doi.org/10.14201/ADCAIJ2017611319S13196

Robot Behavior Architecture Based on Smart Resource Service Execution

[EN] Robot behavior definition aims to classify and specify the robot tasks execution. Behavior architecture design is crucial for proper robot operation performance. According to this, this work aims to establish a robot behavior architecture based on distributed intelligent services. Therefore, behavior definition is set in a high-level delegating the task execution to distributed services provided by network abstractions characterized as Smart Resources. In order to provide a mechanism to measure the performance of this architecture, an evaluation mechanisms based on a service performance composition is introduced. In order to test this proposal it is designed a real use case implementing the proposed robot behavior architecture on a real navigation task.Work supported by the Spanish Science and Innovation Ministry MICINN: CICYT 866 project M2C2: Codiseño de sistemas de control con criticidad mixta basado en 867 misiones TIN2014-56158-C4-4-P and PAID (Polytechnic University of Valencia): 868 UPV-PAID-FPI-2013.Munera-Sánchez, E.; Poza-Lujan, J.; Posadas-Yagüe, J.; Simó Ten, JE.; Blanes Noguera, F. (2017). Robot Behavior Architecture Based on Smart Resource Service Execution. International Journal of Soft Computing And Artificial Intelligence (Online). 5(1):55-60. http://hdl.handle.net/10251/152272S55605

Digital-distance-education: a step back?

In recent years, educational research has focused on implementing digitalization in education. However, the imposed practice of distance learning due to COVID 19 has shown that distance teaching still has a long path to follow to evolve. The digital platforms and methodologies available for use are still far from promoting real interaction and a way to manage emotions at a distance - the essence of face-to-face teaching. Based on the last months' challenging experience of distance teaching, it is clear that HEIs have to rethink their actions in this field and plan ahead. To help build an answer, we have developed a study to assess the impact that this time of digital distance learning has had on the lives of students and teachers and the results it has brought to academic and social life. The study was developed using questionnaires and interviews with students who, in the last months, have experienced distance learning with synchronous classes and whose evaluation was almost exclusively carried out at distance.info:eu-repo/semantics/publishedVersio

The Role of Mixed Criticality Technology in Industry 4.0

[EN] Embedded systems used in critical systems, such as aeronautics, have undergone continuous evolution in recent years. In this evolution, many of the functionalities offered by these systems have been adapted through the introduction of network services that achieve high levels of interconnectivity. The high availability of access to communications networks has enabled the development of new applications that introduce control functions with higher levels of intelligence and adaptation. In these applications, it is necessary to manage different components of an application according to their levels of criticality. The concept of "Industry 4.0" has recently emerged to describe high levels of automation and flexibility in production. The digitization and extensive use of information technologies has become the key to industrial systems. Due to their growing importance and social impact, industrial systems have become part of the systems that are considered critical. This evolution of industrial systems forces the appearance of new technical requirements for software architectures that enable the consolidation of multiple applications in common hardware platforms-including those of different criticality levels. These enabling technologies, together with use of reference models and standardization facilitate the effective transition to this approach. This article analyses the structure of Industry 4.0 systems providing a comprehensive review of existing techniques. The levels and mechanisms of interaction between components are analyzed while considering the impact that the handling of multiple levels of criticality has on the architecture itself-and on the functionalities of the support middleware. Finally, this paper outcomes some of the challenges from a technological and research point of view that the authors identify as crucial for the successful development of these technologies.This research was funded by the Spanish Science and Innovation Ministry MICINN: CICYT project PRECON-I4: "Predictable and dependable computer systems for Industry 4.0" TIN201786520-C3-1-R.Simó Ten, JE.; Balbastre, P.; Blanes Noguera, F.; Poza-Lujan, J.; Guasque Ortega, A. (2021). The Role of Mixed Criticality Technology in Industry 4.0. Electronics. 10(3):1-16. https://doi.org/10.3390/electronics1003022611610