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

Design of a middleware for QoS-aware distribution transparent content delivery

Developers of distributed multimedia applications face a diversity of multimedia formats, streaming platforms and streaming protocols. Furthermore, support for end-to-end quality-of-service (QoS) is a crucial factor for the development of future distributed multimedia systems. This paper discusses the architecture, design and implementation of a QoS-aware middleware platform for content delivery. The platform supports the development of distributed multimedia applications and can deliver content with QoS guarantees. QoS support is offered by means of an agent infrastructure for QoS negotiation and enforcement. Properties of content are represented using a generic content representation model described using the OMG Meta Object Facility (MOF) model. A content delivery framework manages stream paths for content delivery despite differences in streaming protocols and content encoding. The integration of the QoS support, content representation and content delivery framework results in a QoS-aware middleware that enables representation transparent and location transparent delivery of content

Distributed sensor architecture for intelligent control that supports quality of control and quality of service

This paper is part of a study of intelligent architectures for distributed control and communications systems. The study focuses on optimizing control systems by evaluating the performance of middleware through quality of service (QoS) parameters and the optimization of control using Quality of Control (QoC) parameters. The main aim of this work is to study, design, develop, and evaluate a distributed control architecture based on the Data-Distribution Service for Real-Time Systems (DDS) communication standard as proposed by the Object Management Group (OMG). As a result of the study, an architecture called Frame-Sensor-Adapter to Control (FSACtrl) has been developed. FSACtrl provides a model to implement an intelligent distributed Event-Based Control (EBC) system with support to measure QoS and QoC parameters. The novelty consists of using, simultaneously, the measured QoS and QoC parameters to make decisions about the control action with a new method called Event Based Quality Integral Cycle. To validate the architecture, the first five Braitenberg vehicles have been implemented using the FSACtrl architecture. The experimental outcomes, demonstrate the convenience of using jointly QoS and QoC parameters in distributed control systems.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: DPI2011-28507-C02-01/02 and project "Real time distributed control systems" of the Support Program for Research and Development 2012 UPV (PAID-06-12).Poza-Lujan, J.; Posadas-Yagüe, J.; Simó Ten, JE.; Simarro Fernández, R.; Benet Gilabert, G. (2015). Distributed sensor architecture for intelligent control that supports quality of control and quality of service. Sensors. 15(3):4700-4733. https://doi.org/10.3390/s150304700S4700473315

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

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

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-

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

Time At Your Service: Schedulability Analysis of Real-Time and Distributed Services

The software today is distributed over several processing units. At a large scale this may span over the globe via the internet, or at the micro scale, a software may be distributed on several small processing units embedded in one device. Real-time distributed software and services need to be timely and respond to the requests in time. The Quality of Service of real time software depends on how it schedules its tasks to be executed. The state of the art in programming distributed software, like in Java, the scheduling is left to the underlying infrastructure and in particular the operating system, which is not anymore in the control of the applications. In this thesis, we introduce a software paradigm based on object orientation in which real-time concurrent objects are enabled to specify their own scheduling strategy. We developed high-level formal models for specifying distributed software based on this paradigm in which the quality of service requirements are specified as deadlines on performing and finishing tasks. At this level we developed techniques to verify that these requirements are satisfied. This research has opened the way to a new approach to modeling and analysis of a range of applications such as continuous planning in the context of logistics software in a dynamic environment as well as developing software for multi-core systems. Industrial companies (DEAL services) and research centers (the Uppsala Programming for Multicore Architectures Resrearch Center UPMARC) have already shown interest in the results of this thesis.LEI Universiteit LeidenFoundations of Software Technolog

Patterns for Providing Real-Time Guarantees in DOC Middleware - Doctoral Dissertation, May 2002

The advent of open and widely adopted standards such as Common Object Request Broker Architecture (CORBA) [47] has simplified and standardized the development of distributed applications. For applications with real-time constraints, including avionics, manufacturing, and defense systems, these standards are evolving to include Quality-of-Service (QoS) specifications. Operating systems such as Real-time Linux [60] have responded with interfaces and algorithms to guarantee real-time response; similarly, languages such as Real-time Java [59] include mechanisms for specifying real-time properties for threads. However, the middleware upon which large distributed applications are based has not yet addressed end-to-end guarantees of QoS specifications. Unless this challenge can be met, developers must resort to ad hoc solutions that may not scale or migrate well among different platforms. This thesis provides two contributions to the study of real-time Distributed Object Computing (DOC) middleware. First, it identifies potential bottlenecks and problems with respect to guaranteeing real-time performance in contemporary middleware. Experimental results illustrate how these problems lead to incorrect real-time behavior in contemporary middleware platforms. Second, this thesis presents designs and techniques for providing real-time QoS guarantees in DOC middleware in the context of TAO [6], an open-source and widely adopted implementation of real-time CORBA. Architectural solutions presented here are coupled with empirical evaluations of end-to-end real-time behavior. Analysis of the problems, forces, solutions, and consequences are presented in terms of patterns and frame-works, so that solutions obtained for TAO can be appropriately applied to other real-time systems