Projeto de Sistemas Integrados de Propósito Geral Baseados em Redes em Chip Expandindo as Funcionalidades dos Roteadores para Execução de Operações: A plataforma IPNoSys

It bet on the next generation of computers as architecture with multiple processors and/or multicore processors. In this sense there are challenges related to features interconnection, operating frequency, the area on chip, power dissipation, performance and programmability. The mechanism of interconnection and communication it was considered ideal for this type of architecture are the networks-on-chip, due its scalability, reusability and intrinsic parallelism. The networks-on-chip communication is accomplished by transmitting packets that carry data and instructions that represent requests and responses between the processing elements interconnected by the network. The transmission of packets is accomplished as in a pipeline between the routers in the network, from source to destination of the communication, even allowing simultaneous communications between pairs of different sources and destinations. From this fact, it is proposed to transform the entire infrastructure communication of network-on-chip, using the routing mechanisms, arbitration and storage, in a parallel processing system for high performance. In this proposal, the packages are formed by instructions and data that represent the applications, which are executed on routers as well as they are transmitted, using the pipeline and parallel communication transmissions. In contrast, traditional processors are not used, but only single cores that control the access to memory. An implementation of this idea is called IPNoSys (Integrated Processing NoC System), which has an own programming model and a routing algorithm that guarantees the execution of all instructions in the packets, preventing situations of deadlock, livelock and starvation. This architecture provides mechanisms for input and output, interruption and operating system support. As proof of concept was developed a programming environment and a simulator for this architecture in SystemC, which allows configuration of various parameters and to obtain several results to evaluate it

New developmental stages for common marmosets (Callithrix jacchus) using mass and age variables obtained by K-means algorithm and self-organizing maps (SOM)

LEÃO, Adriano de Castro; DÓRIA NETO, Adrião Duarte; SOUSA, Maria Bernardete Cordeiro de. New developmental stages for common marmosets (Callithrix jacchus) using mass and age variables obtained by K-means algorithm and self-organizing maps (SOM). Computers in Biology and Medicine, v. 39, p. 853-859, 2009

Parallel Cyclostationarity-Exploiting Algorithm for Energy-Efficient Spectrum Sensing

The evolution of wireless communication systems leads to Dynamic Spectrum Allocation for Cognitive Radio, which requires reliable spectrum sensing techniques. Among the spectrum sensing methods proposed in the literature, those that exploit cyclostationary characteristics of radio signals are particularly suitable for communication environments with low signal-to-noise ratios, or with non-stationary noise. However, such methods have high computational complexity that directly raises the power consumption of devices which often have very stringent low-power requirements. We propose a strategy for cyclostationary spectrum sensing with reduced energy consumption. This strategy is based on the principle that p processors working at slower frequencies consume less power than a single processor for the same execution time. We devise a strict relation between the energy savings and common parallel system metrics. The results of simulations show that our strategy promises very significant savings in actual devices.

Um algoritmo híbrido para o problema de roteamento de veículos com frotas heterogêneas

This paper aims to propose a hybrid meta-heuristics for the Heterogeneous Fleet Vehicle Routing Problem (HVRP), which is a combinatorial optimization problem NP-hard, and is characterized by the use of a limited fleet consists of different vehicles with different capacities. The hybrid method developed makes use of a memetic algorithm associated with the component optimizer Vocabulary Building. The resulting hybrid meta-heuristic was implemented in the programming language C + + and computational experiments generated good results in relation to meta-heuristic applied in isolation, proving the efficiency of the proposed method.

Desenvolvimento de um modelo computacional para a ampliação do atendimento do Programa de Acessibilidade Especial Porta a Porta - PRAE

Worldwide, the demand for transportation services for persons with disabilities, the elderly, and persons with reduced mobility have increased in recent years. The population is aging, governments need to adapt to this reality, and this fact could mean business opportunities for companies. Within this context is inserted the Programa de Acessibilidade Especial porta a porta PRAE, a door to door public transportation service from the city of Natal-RN in Brazil. The research presented in this dissertation seeks to develop a programming model which can assist the process of decision making of managers of the shuttle. To that end, it was created an algorithm based on methods of generating approximate solutions known as heuristics. The purpose of the model is to increase the number of people served by the PRAE, given the available fleet, generating optimized schedules routes. The PRAE is a problem of vehicle routing and scheduling of dial-a-ride - DARP, the most complex type among the routing problems. The validation of the method of resolution was made by comparing the results derived by the model and the currently programming method. It is expected that the model is able to increase the current capacity of the service requests of transport

Roteamento em Redes de Sensores Sem Fios Com Base Em Aprendizagem Por Reforço

The use of wireless sensor and actuator networks in industry has been increasing past few years, bringing multiple benefits compared to wired systems, like network flexibility and manageability. Such networks consists of a possibly large number of small and autonomous sensor and actuator devices with wireless communication capabilities. The data collected by sensors are sent directly or through intermediary nodes along the network to a base station called sink node. The data routing in this environment is an essential matter since it is strictly bounded to the energy efficiency, thus the network lifetime. This work investigates the application of a routing technique based on Reinforcement Learning s Q-Learning algorithm to a wireless sensor network by using an NS-2 simulated environment. Several metrics like energy consumption, data packet delivery rates and delays are used to validate de proposal comparing it with another solutions existing in the literature

Um estudo algorítmico da programação da intervenção de sondas de produção

This work approaches the Scheduling Workover Rigs Problem (SWRP) to maintain the wells of an oil field, although difficult to resolve, is extremely important economical, technical and environmental. A mathematical formulation of this problem is presented, where an algorithmic approach was developed. The problem can be considered to find the best scheduling service to the wells by the workover rigs, taking into account the minimization of the composition related to the costs of the workover rigs and the total loss of oil suffered by the wells. This problem is similar to the Vehicle Routing Problem (VRP), which is classified as belonging to the NP-hard class. The goal of this research is to develop an algorithmic approach to solve the SWRP, using the fundamentals of metaheuristics like Memetic Algorithm and GRASP. Instances are generated for the tests to analyze the computational performance of the approaches mentioned above, using data that are close to reality. Thereafter, is performed a comparison of performance and quality of the results obtained by each one of techniques used

Um estudo algorítmico de problemas logísticos na indústria de petróleo e gás natural

This work consists on the study of two important problems arising from the operations of petroleum and natural gas industries. The first problem the pipe dimensioning problem on constrained gas distribution networks consists in finding the least cost combination of diameters from a discrete set of commercially available ones for the pipes of a given gas network, such that it respects minimum pressure requirements at each demand node and upstream pipe conditions. On its turn, the second problem the piston pump unit routing problem comes from the need of defining the piston pump unit routes for visiting a number of non-emergent wells in on-shore fields, i.e., wells which don t have enough pressure to make the oil emerge to surface. The periodic version of this problem takes into account the wells re-filling equation to provide a more accurate planning in the long term. Besides the mathematical formulation of both problems, an exact algorithm and a taboo search were developed for the solution of the first problem and a theoretical limit and a ProtoGene transgenetic algorithm were developed for the solution of the second problem. The main concepts of the metaheuristics are presented along with the details of their application to the cited problems. The obtained results for both applications are promising when compared to theoretical limits and alternate solutions, either relative to the quality of the solutions or to associated running time