Allocation of Parallel Real-Time Tasks in Distributed Multi-core Architectures supported by an FTT-SE Network

Distributed real-time systems such as automotive applications are becoming larger and more complex, thus, requiring the use of more powerful hardware and software architectures. Furthermore, those distributed applications commonly have stringent real-time constraints. This implies that such applications would gain in flexibility if they were parallelized and distributed over the system. In this paper, we consider the problem of allocating fixed-priority fork-join Parallel/Distributed real-time tasks onto distributed multi-core nodes connected through a Flexible Time Triggered Switched Ethernet network. We analyze the system requirements and present a set of formulations based on a constraint programming approach. Constraint programming allows us to express the relations between variables in the form of constraints. Our approach is guaranteed to find a feasible solution, if one exists, in contrast to other approaches based on heuristics. Furthermore, approaches based on constraint programming have shown to obtain solutions for these type of formulations in reasonable time.

A framework for using real data with distributed low cost sensors

Currently, due to the widespread use of computers and the internet, students are trading libraries for the World Wide Web and laboratories with simulation programs. In most courses, simulators are made available to students and can be used to proof theoretical results or to test a developing hardware/product. Although this is an interesting solution: low cost, easy and fast way to perform some courses work, it has indeed major disadvantages. As everything is currently being done with/in a computer, the students are loosing the “feel” of the real values of the magnitudes. For instance in engineering studies, and mainly in the first years, students need to learn electronics, algorithmic, mathematics and physics. All of these areas can use numerical analysis software, simulation software or spreadsheets and in the majority of the cases data used is either simulated or random numbers, but real data could be used instead. For example, if a course uses numerical analysis software and needs a dataset, the students can learn to manipulate arrays. Also, when using the spreadsheets to build graphics, instead of using a random table, students could use a real dataset based, for instance, in the room temperature and its variation across the day. In this work we present a framework which uses a simple interface allowing it to be used by different courses where the computers are the teaching/learning process in order to give a more realistic feeling to students by using real data. A framework is proposed based on a set of low cost sensors for different physical magnitudes, e.g. temperature, light, wind speed, which are connected to a central server, that the students have access with an Ethernet protocol or are connected directly to the student computer/laptop. These sensors use the communication ports available such as: serial ports, parallel ports, Ethernet or Universal Serial Bus (USB). Since a central server is used, the students are encouraged to use sensor values results in their different courses and consequently in different types of software such as: numerical analysis tools, spreadsheets or simply inside any programming language when a dataset is needed. In order to do this, small pieces of hardware were developed containing at least one sensor using different types of computer communication. As long as the sensors are attached in a server connected to the internet, these tools can also be shared between different schools. This allows sensors that aren't available in a determined school to be used by getting the values from other places that are sharing them. Another remark is that students in the more advanced years and (theoretically) more know how, can use the courses that have some affinities with electronic development to build new sensor pieces and expand the framework further. The final solution provided is very interesting, low cost, simple to develop, allowing flexibility of resources by using the same materials in several courses bringing real world data into the students computer works.

Response Time Analysis for Fixed-Priority Tasks with Multiple Probabilistic Parameters

Demo presented in 12th Workshop on Models and Algorithms for Planning and Scheduling Problems (MAPSP 2015). 8 to 12, Jun, 2015. La Roche-en-Ardenne, Belgium. Extended abstract.

Task partitioning and priority assignment for distributed hard real-time systems

In this paper, we propose the Distributed using Optimal Priority Assignment (DOPA) heuristic that finds a feasible partitioning and priority assignment for distributed applications based on the linear transactional model. DOPA partitions the tasks and messages in the distributed system, and makes use of the Optimal Priority Assignment (OPA) algorithm known as Audsley’s algorithm, to find the priorities for that partition. The experimental results show how the use of the OPA algorithm increases in average the number of schedulable tasks and messages in a distributed system when compared to the use of Deadline Monotonic (DM) usually favoured in other works. Afterwards, we extend these results to the assignment of Parallel/Distributed applications and present a second heuristic named Parallel-DOPA (P-DOPA). In that case, we show how the partitioning process can be simplified by using the Distributed Stretch Transformation (DST), a parallel transaction transformation algorithm introduced in [1].

XDense: A Dense Grid Sensor Network for Distributed Feature Extraction

XXXIII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos (SBRC 2015), III Workshop de Comunicação em Sistemas Embarcados Críticos. Vitória, Brasil.

Fractional Dynamics and Control of Distributed Parameter Systems

Fractional Calculus (FC) goes back to the beginning of the theory of differential calculus. Nevertheless, the application of FC just emerged in the last two decades, due to the progress in the area of chaos that revealed subtle relationships with the FC concepts. In the field of dynamical systems theory some work has been carried out but the proposed models and algorithms are still in a preliminary stage of establishment. Having these ideas in mind, the paper discusses a FC perspective in the study of the dynamics and control of some distributed parameter systems.

Demand Response Programs Design and Use Considering Intensive Penetration of Distributed Generation

Further improvements in demand response programs implementation are needed in order to take full advantage of this resource, namely for the participation in energy and reserve market products, requiring adequate aggregation and remuneration of small size resources. The present paper focuses on SPIDER, a demand response simulation that has been improved in order to simulate demand response, including realistic power system simulation. For illustration of the simulator’s capabilities, the present paper is proposes a methodology focusing on the aggregation of consumers and generators, providing adequate tolls for the demand response program’s adoption by evolved players. The methodology proposed in the present paper focuses on a Virtual Power Player that manages and aggregates the available demand response and distributed generation resources in order to satisfy the required electrical energy demand and reserve. The aggregation of resources is addressed by the use of clustering algorithms, and operation costs for the VPP are minimized. The presented case study is based on a set of 32 consumers and 66 distributed generation units, running on 180 distinct operation scenarios.

Cost allocation model for distribution networks considering high penetration of distributed energy resources

The high penetration of distributed energy resources (DER) in distribution networks and the competitive environment of electricity markets impose the use of new approaches in several domains. The network cost allocation, traditionally used in transmission networks, should be adapted and used in the distribution networks considering the specifications of the connected resources. The main goal is to develop a fairer methodology trying to distribute the distribution network use costs to all players which are using the network in each period. In this paper, a model considering different type of costs (fixed, losses, and congestion costs) is proposed comprising the use of a large set of DER, namely distributed generation (DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehicles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). The proposed model includes three distinct phases of operation. The first phase of the model consists in an economic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen's and Bialek's tracing algorithms are used and compared to evaluate the impact of each resource in the network. Finally, the MW-mile method is used in the third phase of the proposed model. A distribution network of 33 buses with large penetration of DER is used to illustrate the application of the proposed model.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Influence of human t-cell lymphotropic virus type 1 (HTLV-1) Infection on laboratory parameters of patients with chronic hepatitis C virus

Hepatitis C virus (HCV) and human T-cell lymphotropic virus type 1 (HTLV-1) share routes of transmission and some individuals have dual infection. Although some studies point to a worse prognosis of hepatitis C virus in patients co-infected with HTLV-1, the interaction between these two infections is poorly understood. This study evaluated the influence of HTLV-1 infection on laboratory parameters in chronic HCV patients. Twelve HTLV-1/HCV-coinfected patients were compared to 23 patients infected only with HCV, in regard to demographic data, risk factors for viral acquisition, HCV genotype, presence of cirrhosis, T CD4+ and CD8+ cell counts and liver function tests. There was no difference in regard to age, gender, alcohol consumption, smoking habits, HCV genotype or presence of cirrhosis between the groups. Intravenous drug use was the most common risk factor among individuals co-infected with HTLV-1. These patients showed higher TCD8+ counts (p = 0.0159) and significantly lower median values of AST and ALT (p = 0.0437 and 0.0159, respectively). In conclusion, we have shown that HCV/HTLV-1 co-infected patients differs in laboratorial parameters involving both liver and immunological patterns. The meaning of these interactions in the natural history of these infections is a matter that deserves further studies.

Effect of bioactive compounds extracted from euphorbious plants on hematological and biochemical parameters of Channa punctatus

Channa punctatus was exposed to four different concentrations of Rutin, Taraxerol and Apigenin. Changes in some hematological parameters of Channa punctatus were assessed to determine the influence of these compounds on test fish. Fish were exposed to sublethal concentrations (80% of LC50 of 24h) of these compounds for one week. Control fish were also administered for one week. Thereafter, blood samples were obtained from the control and experimental fish. Blood was assayed for selected hematological parameters (hematocrit, hemoglobin, red blood cell count, white blood cell count total plasma protein and plasma glucose concentration). The derived hematological indices of mean corpuscular hemoglobin concentration (MCHC), mean corpuscular hemoglobin (MCH) and mean corpuscular volume (MCV) were calculated. Sublethal concentrations of these compounds caused a dose dependent decrease in hemoglobin values coupled with a decrease in hematocrit values and red blood cell counts are an obvious indication of anemia. The total white blood cell counts and the differential white blood cell counts were decreased except for the lymphocytes, where there was a slight increase. Plasma protein and glucose were also lower in exposed fish when compared with control. The hematological indices MCH, MCHC, MCV were also lowered. The result from this study reveals high mortality rate and deleterious consequences on the health of fish subjected to acute exposure of Rutin, Taraxerol and Apigenin and therefore, should not be used directly in aquaculture without having the proper knowledge.

Impact of Taraxerol in combination with extract of Euphorbia tirucalli plant on biological parameters of Lymnaea acuminata

The present work was carried out to evaluate the molluscicidal activity of active ingredient Taraxerol with the acetone extract of Euphorbia tirucalli against Lymnaea acuminata snail. The (fecundity, hatchability and survivability) of snail L. acuminata exposed to this extract was studied. The effects of the tested extracts on life-history traits of harmful snail L. acuminata have also been evaluated, and this study also expounds the inhibitory effects of these extracts singly as well as in binary combination (1:1 ratio). It concluded that these herbal products act as a potential source of molluscicides, and that they would also have the advantage of easy availability, low cost, biodegradability and greater acceptance amongst users than synthetic pesticide.