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This article presents the experimental work developed to test the viability and to measure the efficiency of the intelligent control distributed architectures. To do this, a simulated navigation scenario of Braitenberg vehicles has been developed. To control the vehicles, system uses a distributed control architecture that provides support to QoS and QoC parameters to optimize de system. The architecture uses a Publish-Subscribe model, based on Data Distribution Service to send the control messages. Due to the nature of the Publish-Subscribe model, the architecture is suitable to implement event-based control systems. The architecture has been called FSACtrl. To test the efficiency, the architecture provides a set of Quality of Service parameters. In the experiment described in this paper, the performance is used as a reference. The measuring of the quality of the navigation is done through the Integrated Time Average Error as Quality of Control parameter. Tested scenarios are: an environment without quality parameter managing, an environment with a relevant message filtering and an environment with a predictive filtering determined by the type of scenario used. Results obtained show that some of the processing performed in the control nodes can be moved to the middleware to optimize the robot navigation.

In 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.

Quality of service policies in communications is one of the current trends in distributed systems based on middleware technology. To implement the QoS policies it is necessary to define some common parameters. The aim of the QoS policies is to optimize the user defined QoS parameters. This article describes how to obtain the common QoS parameters using message queues for the communications and control components of communication. The paper introduces the Queue-based Quality of Service Cycle concept for each middleware component. The QoS parameters are obtained directly from the queue parameters, and Quality of Service Policies controls directly the message queues to obtain the user-defined parameters values., The middleware 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.