A behavior priority driven approach for resource reservation scheduling

In this paper a behavioral distinction of soft real-time tasks is introduced. The distinction is based on the behavior of the previous instance of each task and it is used to propose a scheduling algorithm. The algorithm, called BIDS, uses well-known server mechanisms with an extension to handle two priority queues within each server. The priority of a server is managed accordingly to the result that is associated task produce. Along with the formal presentation of the algorithm and the proofs of its properties some performance evaluations based on simulations are included.Fil: Ordinez, Leonardo Damian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages". Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages"; ArgentinaFil: Donari, David. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages". Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages"; ArgentinaFil: Santos, Rodrigo Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages". Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages"; ArgentinaSAC '17: Proceedings of the Symposium on Applied ComputingFortalezaBrasilAssociation for Computing Machiner

A novel Approach for sEMG Gesture Recognition using Resource-constrained Hardware Platforms

Classifying human gestures using surface electromyografic sensors (sEMG) is a challenging task. Wearable sensors have proven to be extremely useful in this context, but their performance is limited by several factors (signal noise, computing resources, battery consumption, etc.). In particular, computing resources impose a limitation in many application scenarios, in which lightweight classification approaches are desirable. Recent research has shown that machine learning techniques are useful for human gesture classification once their salient features have been determined. This paper presents a novel approach for human gesture classification in which two different strategies are combined: a) a technique based on autoencoders is used to perform feature extraction; b) two alternative machine learning algorithms (namely J48 and K*) are then used for the classification stage. Empirical results are provided, showing that for limited computing power platforms our approach outperforms other alternative methodologies.Fil: Micheletto, Matías Javier. Universidad Nacional de la Patagonia Austral. Centro de Investigaciones y Transferencia Golfo San Jorge. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Transferencia Golfo San Jorge. Universidad Nacional de la Patagonia "San Juan Bosco". Centro de Investigaciones y Transferencia Golfo San Jorge; ArgentinaFil: Chesñevar, Carlos Iván. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Santos, Rodrigo Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentin

Scheduling Mandatory-Optional Real-Time Tasks in Homogeneous Multi-Core Systems with Energy Constraints Using Bio-Inspired Meta-Heuristics

In this paper we present meta-heuristics to solve the energy aware reward based scheduling of real-time tasks with mandatory and optional parts in homogeneous multi-core processors. The problem is NP-Hard. An objective function to maximize the performance of the system considering the execution of optional parts, the benefits of slowing down the processor and a penalty for changing the operation power-mode is introduced together with a set of constraints that guarantee the real-time performance of the system. The meta-heuristics are the bio-inspired methods Particle Swarm Optimization and Genetic Algorithm. Experiments are made to evaluate the proposed algorithms using a set of synthetic systems of tasks. As these have been used previously with an Integer Lineal Programming approach, the results are compared and show that the solutions obtained with bio-inspired methods are within the Pareto frontier and obtained in less time. Finally, precedence related tasks systems are analyzed and the meta-heuristics proposed are extended to solve also this kind of systems. The evaluation is made by solving a traditional example of the real-time precedence related tasks systems on multiprocessors. The solutions obtained through the methods proposed in this paper are good and show that the methods are competitive. In all cases, the solutions are similar to the ones provided by other methods but obtained in less time and with fewer iterations.Fil: Micheletto, Matías Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; ArgentinaFil: Santos, Rodrigo Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; ArgentinaFil: Orozco, Javier Dario. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; Argentin

Methods and Applications of 3D Ground Crop Analysis Using LiDAR Technology: A Survey

Light Detection and Ranging (LiDAR) technology is positioning itself as one of the most effective non-destructive methods to collect accurate information on ground crop fields, as the analysis of the three-dimensional models that can be generated with it allows for quickly measuring several key parameters (such as yield estimations, aboveground biomass, vegetation indexes estimation, perform plant phenotyping, and automatic control of agriculture robots or machinery, among others). In this survey, we systematically analyze 53 research papers published between 2005 and 2022 that involve significant use of the LiDAR technology applied to the three-dimensional analysis of ground crops. Different dimensions are identified for classifying the surveyed papers (including application areas, crop species under study, LiDAR scanner technologies, mounting platform technologies, and the use of additional instrumentation and software tools). From our survey, we draw relevant conclusions about the use of LiDAR technologies, such as identifying a hierarchy of different scanning platforms and their frequency of use as well as establishing the trade-off between the economic costs of deploying LiDAR and the agronomically relevant information that effectively can be acquired. We also conclude that none of the approaches under analysis tackles the problem associated with working with multiple species with the same setup and configuration, which shows the need for instrument calibration and algorithmic fine tuning for an effective application of this technology.Fil: Micheletto, Matías Javier. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro de Investigaciones y Transferencia Golfo San Jorge. Centro de Investigaciones y Transferencia Golfo San Jorge: Sede Caleta Olivia - Santa Cruz | Universidad Nacional de la Patagonia Austral. Centro de Investigaciones y Transferencia Golfo San Jorge. Centro de Investigaciones y Transferencia Golfo San Jorge: Sede Caleta Olivia - Santa Cruz | Universidad Nacional de la Patagonia "san Juan Bosco". Centro de Investigaciones y Transferencia Golfo San Jorge. Centro de Investigaciones y Transferencia Golfo San Jorge: Sede Caleta Olivia - Santa Cruz; ArgentinaFil: Chesñevar, Carlos Iván. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Santos, Rodrigo Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; Argentin

Using UML for learning how to design and model cyber-physical systems

In this paper a methodology for teaching and learn-ing the modeling of embedded systems and, in a more genericvision cyber-physical systems (CPS) is presented. To this end, asubset of tools from UML is used in an intuitive and orderedway starting with an informal description of the system untilimplementation details are obtained. However, the codificationof the system is left out as the programming language dependson the hardware platform to be used. The method has beenused in grade courses for several years now with an importantaccumulated experience that shows how students are able toadopt it and learn to elicit the different types of requirements,actors and functions.Fil: Ordinez, Leonardo Damian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages". Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages"; ArgentinaFil: Eggly, Gabriel Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; ArgentinaFil: Micheletto, Matías Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages". Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages"; ArgentinaFil: Santos, Rodrigo Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages". Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages"; Argentin

Energy-Aware Topology Control Strategy for Human-Centric Wireless Sensor Networks

The adoption of mobile and ubiquitous solutions that involve participatory or opportunistic sensing increases every day. This situation has highlighted the relevance of optimizing the energy consumption of these solutions, because their operation depends on the devices’ battery lifetimes. This article presents a study that intends to understand how the prediction of topology control messages in human-centric wireless sensor networks can be used to help reduce the energy consumption of the participating devices. In order to do that, five research questions have been defined and a study based on simulations was conducted to answer these questions. The obtained results help identify suitable mobile computing scenarios where the prediction of topology control messages can be used to save energy of the network nodes. These results also allow estimating the percentage of energy saving that can be expected, according to the features of the work scenario and the participants behavior. Designers of mobile collaborative applications that involve participatory or opportunistic sensing, can take advantage of these findings to increase the autonomy of their solutions.Fil: Meseguer, Roc . Universidad Politecnica de Catalunya; EspañaFil: Molina, Carlos. Universitat Rovira I Virgili; EspañaFil: Ochoa, Sergio F.. Universidad de Chile; ChileFil: Santos, Rodrigo Martin. Universidad Nacional del Sur. Departamento de Ingenieria Electrica y de Computadoras. Laboratorio de Sistemas Digitales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación en Ingeniería Eléctrica; Argentin

Flow Scheduling in Data Center Networks with Time and Energy Constraints: A Software-Defined Network Approach

Flow scheduling in Data Center Networks (DCN) is a hot topic as cloud computing and virtualization are becoming the dominant paradigm in the increasing demand of digital services. Within the cost of the DCN, the energy demands associated with the network infrastructure represent an important portion. When flows have temporal restrictions, the scheduling with path selection to reduce the number of active switching devices is a NP-hard problem as proven in the literature. In this paper, an heuristic approach to schedule real-time flows in data-centers is proposed, optimizing the temporal requirements while reducing the energy consumption in the network infrastructure via a proper selection of the paths. The experiments show good performance of the solutions found in relation to exact solution approximations based on an integer linear programming model. The possibility of programming the network switches allows the dynamic schedule of paths of flows under the software-defined network management.Fil: Fraga, Martin. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; ArgentinaFil: Micheletto, Matías Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Llinas, Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Santos, Rodrigo Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Zabala, Paula Lorena. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Modeling IoT-Based Solutions Using Human-Centric Wireless Sensor Networks

The Internet of Things (IoT) has inspired solutions that are already available for addressing problems in various application scenarios, such as healthcare, security, emergency support and tourism. However, there is no clear approach to modeling these systems and envisioning their capabilities at the design time. Therefore, the process of designing these systems is ad hoc and its real impact is evaluated once the solution is already implemented, which is risky and expensive. This paper proposes a modeling approach that uses  human-centric wireless sensor networks to specify and evaluate models of IoT-based systems at the time of design, avoiding the need to spend time and effort on early implementations of immature designs. It allows designers to focus on the system design, leaving the implementation decisions for a next phase. The article illustrates the usefulness of this proposal through a running example, showing the design of an IoT-based solution to support the first responses during medium-sized or large urban incidents. The case study used in the proposal evaluation is based on a real train crash. The proposed modeling approach can be used to design IoT-based systems for other application scenarios, e.g., to support security operatives or monitor chronic patients in their homes.Fil: Monares, Álvaro . Universidad de Chile; ChileFil: Ochoa, Sergio F.. Universidad de Chile; ChileFil: Santos, Rodrigo Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación en Ingeniería Eléctrica; Argentina. Universidad Nacional del Sur. Departamento de Ingenieria Electrica y de Computadoras; ArgentinaFil: Orozco, Javier Dario. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación en Ingeniería Eléctrica; Argentina. Universidad Nacional del Sur. Departamento de Ingenieria Electrica y de Computadoras; ArgentinaFil: Meseguer, Roc . Universidad Politecnica de Catalunya; Españ

Predicting topology propagation messages in mobile ad hoc networks: The value of history

The mobile ad hoc communication in highly dynamic scenarios, like urban evacuations or search-and-rescue processes, plays a key role in coordinating the activities performed by the participants. Particularly, counting on message routing enhances the communication capability among these actors. Given the high dynamism of these networks and their low bandwidth, having mechanisms to predict the network topology offers several potential advantages; e.g., to reduce the number of topology propagation messages delivered through the network, the consumption of resources in the nodes and the amount of redundant retransmissions. Most strategies reported in the literature to perform these predictions are limited to support high mobility, consume a large amount of resources or require training. In order to contribute towards addressing that challenge, this paper presents a history-based predictor (HBP), which is a prediction strategy based on the assumption that some topological changes in these networks have happened before in the past, therefore, the predictor can take advantage of these patterns following a simple and low-cost approach. The article extends a previous proposal of the authors and evaluates its impact in highly mobile scenarios through the implementation of a real predictor for the optimized link state routing (OLSR) protocol. The use of this predictor, named OLSR-HBP, shows a reduction of 40–55% of topology propagation messages compared to the regular OLSR protocol. Moreover, the use of this predictor has a low cost in terms of CPU and memory consumption, and it can also be used with other routing protocols.Fil: Millán, Pere. Universitat Rovira I Virgili; EspañaFil: Aliagas, Carles. Universitat Rovira I Virgili; EspañaFil: Molina, Carlos. Universitat Rovira I Virgili; EspañaFil: Meseguer, Roc. Universidad Politécnica de Catalunya; EspañaFil: Ochoa, Sergio F.. Universidad de Chile; ChileFil: Santos, Rodrigo Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; Argentin

A clinically assisted collaborative system architecture for preventing falls in elderly people

Falls in older adults are not only frequent but also potentially disabling for them. Detecting and preventing these falls have an important impact in the life of the elderly people. This paper presents the architecture of a pervasive system designed to perform early detection of older adults in risk of falling or fell down. The system notifies the appropriate people or healthcare organizations in case of detecting a fall of the monitored person. This monitoring process produces minimum disruption in the life style of the elderly.Fil: Orozco, Javier Dario. Universidad Nacional del Sur. Departamento de Ingenieria Electrica y de Computadoras. Laboratorio de Sistemas Digitales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación en Ingeniería Eléctrica; ArgentinaFil: Santos, Rodrigo Martin. Universidad Nacional del Sur. Departamento de Ingenieria Electrica y de Computadoras. Laboratorio de Sistemas Digitales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación en Ingeniería Eléctrica; ArgentinaFil: Ochoa, Sergio F. . Universidad de Chile; ChileFil: Ordinez, Leonardo Damian. Universidad Nacional del Sur. Departamento de Ingenieria Electrica y de Computadoras. Laboratorio de Sistemas Digitales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación en Ingeniería Eléctrica; ArgentinaFil: Meseguer, Roc . Universidad Politecnica de Catalunya; EspañaFil: Baloian, Nelson. Universidad de Chile; Chil