2013
Autores
Santos, G; Praca, I; Pinto, T; Ramos, S; Vale, Z;
Publicação
2013 IEEE SYMPOSIUM ON INTELLIGENT AGENT (IA)
Abstract
This document presents a tool able to automatically gather data provided by real energy markets and to generate scenarios, capture and improve market players' profiles and strategies by using knowledge discovery processes in databases supported by artificial intelligence techniques, data mining algorithms and machine learning methods. It provides the means for generating scenarios with different dimensions and characteristics, ensuring the representation of real and adapted markets, and their participating entities. The scenarios generator module enhances the MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) simulator, endowing a more effective tool for decision support. The achievements from the implementation of the proposed module enables researchers and electricity markets' participating entities to analyze data, create real scenarios and make experiments with them. On the other hand, applying knowledge discovery techniques to real data also allows the improvement of MASCEM agents' profiles and strategies resulting in a better representation of real market players' behavior. This work aims to improve the comprehension of electricity markets and the interactions among the involved entities through adequate multi-agent simulation.
2013
Autores
Ferreira, LL; Albano, M; Pinho, LM;
Publicação
IEEE International Conference on Emerging Technologies and Factory Automation, ETFA
Abstract
In this paper we analyze some of the existing solutions for Message-Oriented Middleware (MOM), which can be used on industrial environments, and that are, at the same time, capable of handling large quantities of data and of providing adequate Quality-of-Service (QoS) levels for its supported applications. We also make a proposal for the generic structure of a middleware layer supported on a MOM. © 2013 IEEE.
2013
Autores
Garibay Martinez, R; Ferreira, LL; Maia, C; Pinho, LM;
Publicação
2018 8TH IEEE INTERNATIONAL SYMPOSIUM ON INDUSTRIAL EMBEDDED SYSTEMS (SIES)
Abstract
An increasing number of real-time embedded applications present high computation requirements which need to be realized within strict time constraints. Simultaneously, architectures are becoming more and more heterogeneous, programming models are having difficulty in scaling or stepping outside of a particular domain, and programming such solutions requires detailed knowledge of the system and the skills of an experienced programmer. In this context, this paper advocates the transparent integration of a parallel and distributed execution framework, capable of meeting real-time constraints, based on OpenMP programming model, and using MPI as the distribution mechanism. The paper also introduces our modified implementation of GCC compiler, enabled to support such parallel and distributed computations, which is evaluated through a real implementation. This evaluation gives important hints, towards the development of the parallel/distributed fork-join framework for supporting real-time embedded applications.
2013
Autores
Albano, M; Ferreira, L; Le Guilly, T; Ramiro, M; Faria, JE; Duenas, LP; Ferreira, R; Gaylard, E; Cubas, DJ; Roarke, E; Lux, D; Scalari, S; Sorensen, SM; Gangolells, M; Pinho, LM; Skou, A;
Publicação
2013 IEEE EUROCON
Abstract
The ENCOURAGE project tionalizing energy usage in building by implementing a smart energy grid based on intelligent scheduling of energy consuming appliances, renewable energy production, and inter-building energy trading. This paper presents the reference architecture proposed in the context of the ENCOURAGE project, and relates it with the goals of its research efforts.
2013
Autores
Barros, A; Pinho, LM;
Publicação
ACM SIGAda Ada Letters
Abstract
2013
Autores
Abdel Aziz Ali, HIAA; Pinho, LM; Akesson, B;
Publicação
2013 IEEE 19TH INTERNATIONAL CONFERENCE ON EMBEDDED AND REAL-TIME COMPUTING SYSTEMS AND APPLICATIONS (RTCSA)
Abstract
Designing cost-efficient multi-core real-time systems requires efficient techniques to allocate applications to cores while satisfying their timing constraints. However, existing approaches typically allocate using a First-Fit algorithm, which does not consider the execution time and potential parallelism of paths in the applications, resulting in over-dimensioned systems. This work addresses this problem by proposing a new heuristic algorithm, Critical-Path-First, for the allocation of real-time streaming applications modeled as dataflow graphs on 2D mesh multi-core processors. The main criteria of the algorithm is to allocate paths that have the highest impact on the execution time of the application first. It is also able to exploit parallelism in the application by allocating parallel paths on different cores. Experimental evaluation shows that the proposed heuristic improves the resource utilization by allocating up to 7% more applications and it minimizes the average end-to-end worst-case response time of the allocated applications by up to 31%.
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