A scalable and efficient approach for obtaining measurements in CAN-Based control systems

The availability of small inexpensive sensor elements enables the employment of large wired or wireless sensor networks for feeding control systems. Unfortunately, the need to transmit a large number of sensor measurements over a network negatively affects the timing parameters of the control loop. This paper presents a solution to this problem by representing sensor measurements with an approximate representation-an interpolation of sensor measurements as a function of space coordinates. A priority-based medium access control (MAC) protocol is used to select the sensor messages with high information content. Thus, the information from a large number of sensor measurements is conveyed within a few messages. This approach greatly reduces the time for obtaining a snapshot of the environment state and therefore supports the real-time requirements of feedback control loops.

Implementation details of the time division beacon scheduling approach for ZigBee cluster-tree networks

This technical report describes the implementation details of the Time Division Beacon Scheduling Approach in IEEE 802.15.4/ZigBee Cluster-Tree Networks. In this technical report we describe the implementation details, focusing on some aspects of the ZigBee Network Layer and the Time Division Beacon Scheduling mechanism. This report demonstrates the feasibility of our approach based on the evaluation of the experimental results. We also present an overview of the ZigBee address and tree-routing scheme.

Repeater vs. Bridge-based hybrid wired/wireless PROFIBUS networks: a comparative performance analysis

In the last years, several solutions have been proposed to extend PROFIBUS in order to support wired and wireless network stations in the same network. In this paper we compare two of those solutions, one in which the interconnection between wired and wireless stations is made by repeaters and another in which the interconnection is made by bridges. The comparison is both qualitative and numerical, based on simulation models of both architectures.

On the use of the ZigBee protocol for wireless sensor networks

This project was developed within the ART-WiSe framework of the IPP-HURRAY group (http://www.hurray.isep.ipp.pt), at the Polytechnic Institute of Porto (http://www.ipp.pt). The ART-WiSe – Architecture for Real-Time communications in Wireless Sensor networks – framework (http://www.hurray.isep.ipp.pt/art-wise) aims at providing new communication architectures and mechanisms to improve the timing performance of Wireless Sensor Networks (WSNs). The architecture is based on a two-tiered protocol structure, relying on existing standard communication protocols, namely IEEE 802.15.4 (Physical and Data Link Layers) and ZigBee (Network and Application Layers) for Tier 1 and IEEE 802.11 for Tier 2, which serves as a high-speed backbone for Tier 1 without energy consumption restrictions. Within this trend, an application test-bed is being developed with the objectives of implementing, assessing and validating the ART-WiSe architecture. Particularly for the ZigBee protocol case; even though there is a strong commercial lobby from the ZigBee Alliance (http://www.zigbee.org), there is neither an open source available to the community for this moment nor publications on its adequateness for larger-scale WSN applications. This project aims at fulfilling these gaps by providing: a deep analysis of the ZigBee Specification, mainly addressing the Network Layer and particularly its routing mechanisms; an identification of the ambiguities and open issues existent in the ZigBee protocol standard; the proposal of solutions to the previously referred problems; an implementation of a subset of the ZigBee Network Layer, namely the association procedure and the tree routing on our technological platform (MICAz motes, TinyOS operating system and nesC programming language) and an experimental evaluation of that routing mechanism for WSNs.

Web-based application programming interface to solve nonlinear optimization problems

Nonlinear Optimization Problems are usual in many engineering fields. Due to its characteristics the objective function of some problems might not be differentiable or its derivatives have complex expressions. There are even cases where an analytical expression of the objective function might not be possible to determine either due to its complexity or its cost (monetary, computational, time, ...). In these cases Nonlinear Optimization methods must be used. An API, including several methods and algorithms to solve constrained and unconstrained optimization problems was implemented. This API can be accessed not only as traditionally, by installing it on the developer and/or user computer, but it can also be accessed remotely using Web Services. As long as there is a network connection to the server where the API is installed, applications always access to the latest API version. Also an Web-based application, using the proposed API, was developed. This application is to be used by users that do not want to integrate methods in applications, and simply want to have a tool to solve Nonlinear Optimization Problems.

Modeling of the lung impedance using a fractional order ladder network with constant phase elements

The self similar branching arrangement of the airways makes the respiratory system an ideal candidate for the application of fractional calculus theory. The fractal geometry is typically characterized by a recurrent structure. This study investigates the identification of a model for the respiratory tree by means of its electrical equivalent based on intrinsic morphology. Measurements were obtained from seven volunteers, in terms of their respiratory impedance by means of its complex representation for frequencies below 5 Hz. A parametric modeling is then applied to the complex valued data points. Since at low-frequency range the inertance is negligible, each airway branch is modeled by using gamma cell resistance and capacitance, the latter having a fractional-order constant phase element (CPE), which is identified from measurements. In addition, the complex impedance is also approximated by means of a model consisting of a lumped series resistance and a lumped fractional-order capacitance. The results reveal that both models characterize the data well, whereas the averaged CPE values are supraunitary and subunitary for the ladder network and the lumped model, respectively.

FPGA-based weblab infrastructures guidelines and a prototype implementation example

Recent trends show an increasing number of weblabs, implemented at universities and schools, supporting practical training in technical courses and providing the ability to remotely conduct experiments. However, their implementation is typically based on individual architectures, unable of being reconfigured with different instruments/modules usually required by every experiment. In this paper, we discuss practical guidelines for implementing reconfigurable weblabs that support both local and remote control interfaces. The underlying infrastructure is based on reconfigurable, low-cost, FPGA-based boards supporting several peripherals that are used for the local interface. The remote interface is powered by a module capable of communicating with an Ethernet based network and that can either correspond to an internal core of the FPGA or an external device. These two approaches are discussed in the paper, followed by a practical implementation example.

Ferramenta de gestão de redes MESH

Mestrado em Engenharia Electrotécnica e de Computadores - Área de Especialização de Telecomunicações

Multi-agent system for personalization of location-based services

The current ubiquitous network access and increase in network bandwidth are driving the sales of mobile location-aware user devices and, consequently, the development of context-aware applications, namely location-based services. The goal of this project is to provide consumers of location-based services with a richer end-user experience by means of service composition, personalization, device adaptation and continuity of service. Our approach relies on a multi-agent system composed of proxy agents that act as mediators and providers of personalization meta-services, device adaptation and continuity of service for consumers of pre-existing location-based services. These proxy agents, which have Web services interfaces to ensure a high level of interoperability, perform service composition and take in consideration the preferences of the users, the limitations of the user devices, making the usage of different types of devices seamless for the end-user. To validate and evaluate the performance of this approach, use cases were defined, tests were conducted and results gathered which demonstrated that the initial goals were successfully fulfilled.

NoC contention analysis using a branch-and-prune algorithm

“Many-core” systems based on a Network-on-Chip (NoC) architecture offer various opportunities in terms of performance and computing capabilities, but at the same time they pose many challenges for the deployment of real-time systems, which must fulfill specific timing requirements at runtime. It is therefore essential to identify, at design time, the parameters that have an impact on the execution time of the tasks deployed on these systems and the upper bounds on the other key parameters. The focus of this work is to determine an upper bound on the traversal time of a packet when it is transmitted over the NoC infrastructure. Towards this aim, we first identify and explore some limitations in the existing recursive-calculus-based approaches to compute the Worst-Case Traversal Time (WCTT) of a packet. Then, we extend the existing model by integrating the characteristics of the tasks that generate the packets. For this extended model, we propose an algorithm called “Branch and Prune” (BP). Our proposed method provides tighter and safe estimates than the existing recursive-calculus-based approaches. Finally, we introduce a more general approach, namely “Branch, Prune and Collapse” (BPC) which offers a configurable parameter that provides a flexible trade-off between the computational complexity and the tightness of the computed estimate. The recursive-calculus methods and BP present two special cases of BPC when a trade-off parameter is 1 or ∞, respectively. Through simulations, we analyze this trade-off, reason about the implications of certain choices, and also provide some case studies to observe the impact of task parameters on the WCTT estimates.

Estudo e análise das redes centradas em conteúdos

A Internet, conforme a conhecemos, foi projetada com base na pilha de protocolos TCP/IP, que foi desenvolvida nos anos 60 e 70 utilizando um paradigma centrado nos endereços individuais de cada máquina (denominado host-centric). Este paradigma foi extremamente bem-sucedido em interligar máquinas através de encaminhamento baseado no endereço IP. Estudos recentes demonstram que, parte significativa do tráfego atual da Internet centra-se na transferência de conteúdos, em vez das tradicionais aplicações de rede, conforme foi originalmente concebido. Surgiram então novos modelos de comunicação, entre eles, protocolos de rede ponto-a-ponto, onde cada máquina da rede pode efetuar distribuição de conteúdo (denominadas de redes peer-to-peer), para melhorar a distribuição e a troca de conteúdos na Internet. Por conseguinte, nos últimos anos o paradigma host-centric começou a ser posto em causa e apareceu uma nova abordagem de Redes Centradas na Informação (ICN - information-centric networking). Tendo em conta que a Internet, hoje em dia, basicamente é uma rede de transferência de conteúdos e informações, porque não centrar a sua evolução neste sentido, ao invés de comunicações host-to-host? O paradigma de Rede Centrada no Conteúdo (CCN - Content Centric Networking) simplifica a solução de determinados problemas de segurança relacionados com a arquitetura TCP/IP e é uma das principais propostas da nova abordagem de Redes Centradas na Informação. Um dos principais problemas do modelo TCP/IP é a proteção do conteúdo. Atualmente, para garantirmos a autenticidade e a integridade dos dados partilhados na rede, é necessário garantir a segurança do repositório e do caminho que os dados devem percorrer até ao seu destino final. No entanto, a contínua ineficácia perante os ataques de negação de serviço praticados na Internet, sugere a necessidade de que seja a própria infraestrutura da rede a fornecer mecanismos para os mitigar. Um dos principais pilares do paradigma de comunicação da CCN é focalizar-se no próprio conteúdo e não na sua localização física. Desde o seu aparecimento em 2009 e como consequência da evolução e adaptação a sua designação mudou atualmente para Redes de Conteúdos com Nome (NNC – Named Network Content). Nesta dissertação, efetuaremos um estudo de uma visão geral da arquitetura CCN, apresentando as suas principais características, quais os componentes que a compõem e como os seus mecanismos mitigam os tradicionais problemas de comunicação e de segurança. Serão efetuadas experiências com o CCNx, que é um protótipo composto por um conjunto de funcionalidades e ferramentas, que possibilitam a implementação deste paradigma. O objetivo é analisar criticamente algumas das propostas existentes, determinar oportunidades, desafios e perspectivas para investigação futura.

Short-term Load Forecasting Based on Load Profiling

Load forecasting has gradually becoming a major field of research in electricity industry. Therefore, Load forecasting is extremely important for the electric sector under deregulated environment as it provides a useful support to the power system management. Accurate power load forecasting models are required to the operation and planning of a utility company, and they have received increasing attention from researches of this field study. Many mathematical methods have been developed for load forecasting. This work aims to develop and implement a load forecasting method for short-term load forecasting (STLF), based on Holt-Winters exponential smoothing and an artificial neural network (ANN). One of the main contributions of this paper is the application of Holt-Winters exponential smoothing approach to the forecasting problem and, as an evaluation of the past forecasting work, data mining techniques are also applied to short-term Load forecasting. Both ANN and Holt-Winters exponential smoothing approaches are compared and evaluated.

Multi-Agent Based Smart Grid Management and Simulation: Situation Awareness and Learning in a Test Bed with Simulated and Real Installations and Players

The rising usage of distributed energy resources has been creating several problems in power systems operation. Virtual Power Players arise as a solution for the management of such resources. Additionally, approaching the main network as a series of subsystems gives birth to the concepts of smart grid and micro grid. Simulation, particularly based on multi-agent technology is suitable to model all these new and evolving concepts. MASGriP (Multi-Agent Smart Grid simulation Platform) is a system that was developed to allow deep studies of the mentioned concepts. This paper focuses on a laboratorial test bed which represents a house managed by a MASGriP player. This player is able to control a real installation, responding to requests sent by the system operators and reacting to observed events depending on the context.

Reinforcement Learning Based on the Bayesian Theorem for Electricity Markets Decision Support

This paper presents the applicability of a reinforcement learning algorithm based on the application of the Bayesian theorem of probability. The proposed reinforcement learning algorithm is an advantageous and indispensable tool for ALBidS (Adaptive Learning strategic Bidding System), a multi-agent system that has the purpose of providing decision support to electricity market negotiating players. ALBidS uses a set of different strategies for providing decision support to market players. These strategies are used accordingly to their probability of success for each different context. The approach proposed in this paper uses a Bayesian network for deciding the most probably successful action at each time, depending on past events. The performance of the proposed methodology is tested using electricity market simulations in MASCEM (Multi-Agent Simulator of Competitive Electricity Markets). MASCEM provides the means for simulating a real electricity market environment, based on real data from real electricity market operators.

Incentive-based demand response programs designed by asset-light retailers for day-ahead market

Following the deregulation experience of retail electricity markets in most countries, the majority of the new entrants of the liberalized retail market were pure REP (retail electricity providers). These entities were subject to financial risks because of the unexpected price variations, price spikes, volatile loads and the potential for market power exertion by GENCO (generation companies). A REP can manage the market risks by employing the DR (demand response) programs and using its' generation and storage assets at the distribution network to serve the customers. The proposed model suggests how a REP with light physical assets, such as DG (distributed generation) units and ESS (energy storage systems), can survive in a competitive retail market. The paper discusses the effective risk management strategies for the REPs to deal with the uncertainties of the DAM (day-ahead market) and how to hedge the financial losses in the market. A two-stage stochastic programming problem is formulated. It aims to establish the financial incentive-based DR programs and the optimal dispatch of the DG units and ESSs. The uncertainty of the forecasted day-ahead load demand and electricity price is also taken into account with a scenario-based approach. The principal advantage of this model for REPs is reducing the risk of financial losses in DAMs, and the main benefit for the whole system is market power mitigation by virtually increasing the price elasticity of demand and reducing the peak demand.