A quality of service framework for adaptive and dependable large scale system-of-systems

There is growing recognition within industry that for system growth to be sustainable, the way in which existing assets are used must be improved. Future systems are being developed with a desire for dynamic behaviour and a requirement for dependability at mission critical and safety critical levels. These levels of criticality require predictable performance and as such have traditionally not been associated with adaptive systems. The software architecture proposed for such systems is based around a publish/subscribe model, an approach that, while adaptive, does not typically support critical levels of performance. There is, however, the scope for dependability within such architectures through the use of Quality of Service (QoS) methods. QoS is used in systems where the distribution of resources cannot be decided at design time. A QoS based framework is proposed for providing adaptive and dependable behaviour for future large-scale system-of-systems. Initial simulation results are presented to demonstrate the benefits of QoS

QoS-enabled middleware for smart grids

Emerging smart grid systems must be able to react quickly and predictably, adapting their operation to changing energy supply and demand, by controlling energy consuming and energy storage devices. An intrinsic problem with smart grids is that energy produced from in-house renewable sources is affected by fluctuating weather factors. The applications driving smart grids operation must rely on a solid communication network that is secure, highly scalable, and always available. Thus, any communication infrastructure for smart grids should support its potential of producing high quantities of real-time data, with the goal of reacting to state changes by actuating on devices in real-time, while providing Quality of Service (QoS)

Open communication protocols for integration of embedded systems within Industry 4

This article deals with Industry 4 as a new paradigm for manufacturing of the future. Internet of Things and new communication approach can lead to next generation of automated solutions as next step from currently isolated automation systems to Cyber-Physical Systems. Article tries to create model for DDS protocol considering real time requirements with QoS feature

Security and Performance Trade-offs for Data Distribution Service in Flying Ad-Hoc Networks

This paper focuses on the data distribution service(DDS) middleware and its publish/subscribe logic - a topic thathas recently regained popularity in both academia as well asindustry. DDS is a well-known approach based on publish-subscribe logic. Therefore, only brief introduction of the issueis given followed by practical evaluation of current, availableand real implementations from the security and performancepoint of view. The analysis and evaluation is performed toaid comparison of competing DDS implementation, and thuscould serve well as an input to decision-making about whichof these solutions is best suited for a given situation. Finally,the practical performance evaluation is performed via severaldifferent scenarios to effectively compare the currently most-usedDDS implementations

A quality of service framework for adaptive and dependable large scale system-of-systems

There is growing recognition within industry that for system growth to be sustainable, the way in which existing assets are used must be improved. Future systems are being developed with a desire for dynamic behaviour and a requirement for dependability at mission critical and safety critical levels. These levels of criticality require predictable performance and as such have traditionally not been associated with adaptive systems. The software architecture proposed for such systems is based around a publish/subscribe model, an approach that, while adaptive, does not typically support critical levels of performance. There is, however, the scope for dependability within such architectures through the use of Quality of Service (QoS) methods. QoS is used in systems where the distribution of resources cannot be decided at design time. A QoS based framework is proposed for providing adaptive and dependable behaviour for future large-scale system-of-systems. Initial simulation results are presented to demonstrate the benefits of QoS

Adding an ontology to a standardized QoS-based MAS middleware

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-02481-8_12In a Multi-Agent system, middleware is one of the components used to isolate control and communications. The use of standards in the implementation of an intelligent distributed system is always advantageous. This paper presents a middleware that provides support to a multi-agent system. Middleware is based on the standard Data Distribution Services (DDS), proposed by Object Management Group (OGM). Middleware organizes information by tree based ontology and provides a set of quality of service policies that agents can use to increase efficiency. DDS provides a set of quality of service policy. Joining quality of service policy and the ontology allows getting many advantages, among others the possibility of to conceal some details of the communications system to agents, the correct location of the agents in the distributed system, or the monitoring agents in terms of quality of service. For modeling the middleware architecture it has used UML class diagrams. As an example it has presented the implementation of a mobile robot navigation system through agents that model behaviors.The MAS 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. (2009). Adding an ontology to a standardized QoS-based MAS middleware. En Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living. Springer. 83-90. doi:10.1007/978-3-642-02481-8_12S8390Coulouris, G., Dollimore, J., Kindberg, T.: Distributed systems, concepts and design, 3rd edn. Addison Wesley, Reading (2001)Hapner, M., Sharma, R., Fialli, J., Stout, K.: JMS specification, vol. 1.1. Sun Microsystems Inc., Santa Clara (2002)Lewis, R.: Advanced Messaging Applications with MSMQ and MQ Series. Que Publishing (1999)OMG. Real-Time Corba Specification version 1.1. Document formal /02-08-02 (2002)FIPA. Specfication. Part 2, Agent Communication Language. Foundation for Intelligent Physical Agents (1997)Vogel, A., Kerherve, B., von Bochmann, G., Gecsei, J.: Distributed Multimedia and QoS: A Survey. IEEE Multimedia 2(2), 10–19 (1995)Smith, B.: Beyond concepts, or: Ontology as reality representation. In: Formal Ontology in Information Systems (FOIS 2004), pp. 73–84 (2004)Gruber, T.R.: Toward Principles for the Design of Ontologies Used for Knowledge Sharing. International Journal Human-Computer Studies 43(5-6), 907–928 (1995)Pardo-Castellote, G.: OMG Data-Distribution Service: architectural overview. In: Proceedings of 23rd International Conference on Distributed Computing Systems Workshops, Providence, USA, vols. 19-22, pp. 200–206 (2003)Object Management Group (OMG). Unified Modeling Language Specification, v1.4.2, ISO/IEC 19501 (2001)Poza, J.L., Posadas, J.I., Simó, J.E.: Distributed agent specification to an Intelligent Control Architecture. In: 6th International Workshop on Practical Applications of Agents and Multiagent Systems, Salamanca (2007)Poza, J.L., Posadas, J.l., Simó, J.E.: QoS-based middleware archi-tecture for distributed control systems. In: International Symposium on Distributed Computing and Artificial Intelligence, Salamanca (2008

An investigation into some security issues in the DDS messaging protocol

The convergence of Operational Technology and Information Technology is driving integration of the Internet of Things and Industrial Control Systems to form the Industrial Internet of Things. Due to the influence of Information Technology, security has become a high priority particularly when implementations expand into critical infrastructure. At present there appears to be minimal research addressing security considerations for industrial systems which implement application layer IoT messaging protocols such as Data Distribution Services (DDS). Simulated IoT devices in a virtual environment using the DDSI-RTPS protocol were used to demonstrate that enumeration of devices is possible by a non-authenticated client in both active and passive mode. Further, modified sequence numbers were found to be a potential denial of service attack, and malicious heartbeat messages were fashioned to be effective at denying receipt of legitimate messages

Experimental Evaluation of the Real-Time Performance of Publish-Subscribe Middlewares

REACTION 2013. 2nd International Workshop on Real-time and distributed computing in emerging applications. December 3rd, 2013, Vancouver, Canada.The integration of the complex network of modules composing a modern distributed embedded systems calls for a middleware solution striking a good tradeoff between conflicting needs such as: modularity, architecture independence, re-use, easy access to the limited hardware resources and ability to respect real–time constraints. Several middleware architectures proposed in the last years offer reliable and easy to use abstractions and intuitive publish-subscribe mechanism that can simplify system development to a good degree. However, a complete compliance with the different requirements of assistive robotics application (first and foremost real–time constraints) remains to be investigated. This paper evaluates the performance of these solutions in terms of latency and scalability

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