Juan-Luis Posadas-Yagüe

Dynamic Reconfiguration of a RGBD Sensor Based on QoS and QoC Requirements in Distributed Systems

The inclusion of embedded sensors into a networked system provides useful information for many applications. A Distributed Control System (DCS) is one of the clearest examples where processing and communications are constrained by the client’s requirements and the capacity of the system. An embedded sensor with advanced processing and communications capabilities supplies high level information, abstracting from the data acquisition process and objects recognition mechanisms. The implementation of an embedded sensor/actuator as a Smart Resource permits clients to access sensor information through distributed network services. Smart resources can offer sensor services as well as computing, communications and peripheral access by implementing a self-aware based adaptation mechanism which adapts the execution profile to the context. On the other hand, information integrity must be ensured when computing processes are dynamically adapted. Therefore, the processing must be adapted to perform tasks in a certain lapse of time but always ensuring a minimum process quality. In the same way, communications must try to reduce the data traffic without excluding relevant information. The main objective of the paper is to present a dynamic configuration mechanism to adapt the sensor processing and communication to the client’s requirements in the DCS. This paper describes an implementation of a smart resource based on a Red, Green, Blue, and Depth (RGBD) sensor in order to test the dynamic configuration mechanism presented.

Assessing the Impact of Continuous Evaluation Strategies: Tradeoff Between Student Performance and Instructor Effort

Current opinion on undergraduate studies has led to a reformulation of teaching methodologies to base them not just on learning, but also on skills and competencies. In this approach, the teaching/learning process should accomplish both knowledge assimilation and skill development. Previous works demonstrated that a strategy that uses continuous evaluation is able to meet both objectives. However, those studies did not evaluate and quantify the additional effort required to implement such strategies. This paper evaluates the additional instructor effort required when implementing continuous evaluation in a first-year Computer Fundamentals course in the Computer Engineering degree program at the Technical University of Valencia, Spain. The experiment quantifies how instructor workload increases under different continuous evaluation strategies and how this affects the overall student grade. Both the “standard” continuous evaluation method and the intensive continuous evaluation method are analyzed, the latter being a proposal that builds upon the standard method by increasing the number of tests and examinations. The results obtained reveal that continuous evaluation improves student grades but that intensive continuous evaluation is liable to generate an excessive instructor overload without having a significant impact on student scores.

A Survey on Quality of Service Support on Middleware-Based Distributed Messaging Systems Used in Multi Agent Systems

Messaging 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.

Extending MAM5 Meta-Model and JaCalIV E Framework to Integrate Smart Devices from Real Environments

This paper presents the extension of a meta-model (MAM5) and a framework based on the model (JaCalIVE) for developing intelligent virtual environments. The goal of this extension is to develop augmented mirror worlds that represent a real and virtual world coupled, so that the virtual world not only reflects the real one, but also complements it. A new component called a smart resource artifact, that enables modelling and developing devices to access the real physical world, and a human in the loop agent to place a human in the system have been included in the meta-model and framework. The proposed extension of MAM5 has been tested by simulating a light control system where agents can access both virtual and real sensor/actuators through the smart resources developed. The results show that the use of real environment interactive elements (smart resource artifacts) in agent-based simulations allows to minimize the error between simulated and real system.

Performance and Results of the Triple Buffering Built-In in a Raspberry PI to Optimize the Distribution of Information from a Smart Sensor

Currently, 3D sensors can be considered an evolution of cameras by providing the image with its depth information. These sensors have a generic function and the programmer has to process the received information in order to be adapted and used in a specific environment. In robots navigation, the 3D information can be useful for basic behaviours such as “obstacles avoidance” or even more complex behaviours such as “maps generation”. In this article an image management system provided by the xTion intelligent sensor is presented. The xTion sensor provides a VGA image and a 3D depth, which allows it to be used for several purposes. In order to distribute the data, it is acquired, processed and sent to several clients with a triple buffer system modified to serve the most recent image to the client. The system is programmed in C for Linux and built-in in a Raspberry PI. The article exposes the performance and results from monitoring the frame’s delay comparing it with a simple and a double buffer system widely used in this kind of systems.

Multi-agent architecture with support to quality of service and quality of control

Multi 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 FSACtrl.

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.

Smart device definition and application on embedded system: performance and optimi-zation on a RGBD sensor

Embedded control systems usually are characterized by its limitations in terms of computational power and memory. Although this systems must deal with perpection and actuation signal adaptation and calculate control actions ensuring its reliability and providing a certain degree of fault tolerance. The allocation of these tasks between some different embedded nodes conforming a distributed control system allows to solve many of these issues. For that reason is proposed the application of smart devices aims to perform the data processing tasks related with the perception and actuation and offer a simple interface to be configured by other nodes in order to share processed information and raise QoS based alarms. In this work is introduced the procedure of implementing a smart device as a sensor as an embedded node in a distributed control system. In order to analyze its benefits an application based on a RGBD sensor implemented as an smart device is proposed.

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

This 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 managing, 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.

Control kernel in smart factory environments: Smart resources integration

The evolution of the definition of industry into the Smart factories has provide a big improvements in terms of production efficiency and promoted new ways to implement interfaces between humans and machines. A factory plan, which is achieved by means of a set of missions, implies a set of control missions. In this work is introduced how to achieve these control missions into a smart factory through distributed services. These services are provided by integrating smart resources. Smart resources will rely its execution on the control kernel which provides real-time support and reliability to the execution of control tasks. As a conclusions, we introduce a scalable and reusable hierarchy to perform factory plans based on distributed services.