Performance Of Developed Model Research Articles

A scalable fine-grained analytic model for container cloud data centres

Although cloud service providers have deployed numerous large-scale cloud data centres world-wide, research in performance modelling for cloud data centres are still in its infancy. A precise model of a cloud data centre can help the service providers improve their service quality, capacity planning, load balance and reduce operation costs. Most studies in literature focused on modelling hypervisor based cloud, typically IaaS. With the growing popularity of containers in cloud service providers; there is a need to develop performance models specifically for these systems. In this paper, a novel cloud analytic model (CAM) for container-based cloud data centre was proposed. The interactive stochastic models are used to analyse the performance of the system in terms of mean job delay and probability of job rejection. Finally, a container emulation framework, ConSim, was developed and tested against the analytic model. Experimental development using real data were compared with theoretical calculation.

A Study on the Development of Performance Model for International Education Cooperative Projects based on Online Learning Community

Educational cooperative activities between countries for human capacity building are expanding in accordance with the international stream of modern globalization and information. A variety of models on exchange activities are also appearing based on this stream. These trends made many changes in the field of traditional education through online-based activities which anyone can access to beyond spatiotemporal barriers. This study aimed at developing the performance model to support the activities of members who carry out cooperative projects under online learning community, applying it to actual performance case, analyzing the results, and deriving improvements. The developed performance model consists of three components. The first component is the core principle for management and implementation of the performance model. The second one is the process of performance model and activities of each step, and the third one is online workrooms (websites) to support the performances. Moreover, members of the community applied core progressive strategies to accomplish projects and a few suggestions were raised so as to make aggressive and dynamic activities of online learning community. Based on the ‘Online Learning Community’, the members who carry out international educational cooperative projects acquired meaningful knowledge not by one-way giving from others but by forming recursive process, where the members with various cultures and backgrounds could be an instructor at one time or a learner at the other time, so they experienced social learning process acquiring knowledge cooperatively.

A interferência do módulo de resiliência do concreto asfáltico no período de projeto de pavimentos rodoviários

Os pavimentos rodoviários são dimensionados para atender uma determinada vida útil em função dos materiais e do tráfego. A análise mecanicista prevê que o Módulo de Resiliência do Concreto Asfáltico será constante ao longo de sua vida útil, fato divergente ao encontrado na literatura, ao envelhecimento natural do ligante e às condições climáticas. Neste artigo foi possível constatar, por meio de uma verificação teórico-mecanicista, que pavimentos asfálticos dimensionados para tráfegos moderado, pesado ou muito pesado, independente da capacidade de suporte do subleito, podem perder até 78% da sua vida útil a partir do terceiro ano de operação se o Módulo de Resiliência do Concreto Asfáltico obedecer a uma tendência decrescente, e um ganho de até 172% para uma tendência crescente. Desse modo, constata-se a importância de se desenvolver modelos de desempenho que considerem os fatores que interferem no comportamento do Concreto Asfáltico para que se possa elaborar projetos mais racionais.

Development of Performance Models for Boiler Feed Water Treatment Ion Exchange Facility

The treatments of raw water using resins embedded with cation and anion were investigated in this study via a developed mathematical model. The developed mathematical model was used to predict the amount of sodium (Na+), calcium (Ca2+), magnesium (Mg2+) and ammonium (NH4＋ ) ions removed by the resin embedded with hydrogen ion (H+) in the cation bed. The model was also used to investigate the amount of chloride (Cl－) and sulphate (SO42－ ) ions treated by the resin embedded with hydroxyl ion (OH－) in the anion bed. The effect of flow rate and superficial velocity were also investigated. The simulation results showed that there was significant reduction of Na+, Ca2+, Mg2+, , Cl－ and SO4 2－from their initial concentrations in raw water. This showed that the mathematical model was able to predict the concentrations of cations and anions investigated in this study. The result revealed that the flow rate of water has effect on the treatment of cations and anions in raw water using ion-exchange resins. Thus, operating the resin beds at very high flow rate reduced its performance while at very low flow rate the residence time of wastewater on the bed increased with resultant increase in performance. Similarly, high superficial velocity reduced the amount of ion concentration removed by the resin in both beds. The total final concentrations of cations in the cation bed by the model were 0.0003156, 0.0003452 and 0.0036 mol/m3 at 4.0, 4.5 and 6.5 m/min respectively while that from the anion bed were 0.0002597, 0.0002769 and 0.00205 mol/m3 at 4.0, 4.5 and 6.5 m/min respectively. The predicted model results, when compared with the maximum allowable limit of total concentration of both cations and anions of a functional industrial company (Notore chemical), showed a maximum percentage deviation ranging from 2.00% to 3.53%. This showed that the developed model has achieved its set objectives.

Application of Markov chains and Monte Carlo simulations for developing pavement performance models for urban network management

Existing performance models developed for interurban pavements are not applicable to urban pavements due to differences in traffic demands and deterioration trends. The objective of the study was to develop performance models for the management of urban pavement networks. Markov chains and Monte Carlo simulation were applied to account for the probabilistic nature of pavements deterioration over time, using data collected in the field. One of the advantages of this methodology is that it can be used by local agencies with scarce technical resources and historical data. Eight performance models were developed and successfully validated for asphalt and concrete pavements in humid, dry and Mediterranean climates with different functional hierarchies. The resulting models evidence the impact of design, traffic demand, climate and construction standards on urban pavements performance. Predicted service life of asphalt and concrete pavements in primary networks are consistent with design standards. However, pavements in secondary and local networks present shorter and longer service life compared to design life, respectively. Climate is a relevant factor for asphalt pavements, where higher deterioration was observed compared to that expected. Opposite to this, no relevant differences between design and performance can be attributed to climate in concrete pavements.

Developing performance models for treated gravel roads to evaluate the cost-effectiveness of using dust chemical treatments

The objective of this study is to develop a long-term performance model to predict the service life of treated gravel roads. Fugitive dust emissions from 11 recently treated gravel roads located in five different counties in the state of Wyoming were measured periodically for 12 months. Visual survey ratings of the 11 roads were taken each time. Surfacing moisture samples were collected. Traffic speeds and volumes by class were also collected using a two-tube traffic counting system. Surfacing aggregate samples were collected and their gradations were determined. Performance curves were developed for each of the selected 11 roads. A comprehensive long-term performance model was developed that predicts the service life of treatment on gravel roads. A life cycle cost analysis comparison study was also conducted to compare the cost of maintaining untreated gravel roads with the cost of maintaining treated gravel roads. Statistical analyses generated regression models that allowed the prediction of factors significant to the service life of treatment on gravel roads. It was found that the daily traffic, the percentage of fines in the soil and the annual rainfall had the highest contribution to road deteriorations and increase in dust generation. Dust treatment was found to have a service life of one year before dust emission rates went back to before treatment levels. The life cycle cost analysis indicates that the initial cost of applying dust suppressant treatment to gravel roads is expensive. However, it will increase the road service life and significantly reduce dust generation.

Subspace approach to performance modelling of range‐sidelobe suppressed waveforms

An important concern in radar is understanding the consequence of waveform design constraints on the signal-to-interference-plus-noise ratio (SINR) performance. In this study, the authors develop performance models for the attendant drop in SINR as an integrated sidelobe (ISL) constraint is placed on the waveform. The performance models are developed using an eigenbasis subspace approach. The authors validate the performance models against measured data and conclude that the proposed approach provides reasonable performance modelling of the SINR as a function of the ISL constraint.

Radial turbine performance measurement under extreme off-design conditions

During automotive urban driving conditions and future homologation cycles, automotive radial turbines experience transient conditions, whereby the same operate at very high blade speed ratios and, thus, at very low power outputs. Under those conditions, the turbine power output might not be enough to feed the mechanical power needs of the compressor. Typical fast one-dimensional full engine simulations rely on steady-state performance maps to characterize the turbocharger. Due to the restricting compressor braking power, extreme off-design measurements cannot be obtained in standard gas stands without using an external brake instead of the compressor or without using a motor attached to the turbocharger shaft. Such turbocharger assemblies cause shaft balancing issues inherent to the connection to a brake operating at high rotational speeds or need basic changes of the turbocharger geometry. This paper presents a novel approach for turbine performance map measurements at very low expansion ratio and very low mass flow without the aforementioned issues. The method uses the turbocharger compressor as a centrifugal turbine, providing mechanical power to the shaft and enabling turbine performance measurements from points of very high expansion ratio up to very low pressure ratio. It is even possible to measure at almost zero flow rate in the turbine when it consumes shaft power instead of producing it. This experimental procedure that can be applied to whatever turbocharger produces valuable information for the development and validation of turbine performance models aiming to extrapolate its behaviour at off-design conditions.

Accelerated Load Testing to Compare the Performance of Full-Depth Reclamation with Foamed Asphalt Under Three Environmental Conditions

Full-depth reclamation (FDR) with foamed asphalt has been successfully used as a rehabilitation strategy in California since 2001. Long-term field monitoring on several projects, combined with a comprehensive laboratory study, resulted in the preparation of guidelines and specification language in 2008. However, the design criteria were essentially empirical, in line with California’s design procedures for this level of rehabilitation project. There has been growing interest in the use of cement, engineered emulsion, and no-stabilizer full-depth reclamation strategies in addition to foamed asphalt, and in the use of mechanistic design in a greater range of rehabilitation projects. Consequently, the research initiative was extended to a second phase, to include accelerated load testing on an instrumented test track constructed with these four FDR strategies. The second phase gathered data for the development of performance models that can be included in mechanistic–empirical rehabilitation design procedures. This paper summarizes the results of three of the 11 tests in this accelerated loading study, which compared the performance of foamed asphalt under three environmental conditions (dry, wet, and at elevated temperature). All three sections performed well; however, performance was clearly influenced by wet conditions and higher asphalt concrete surface temperatures. As a consequence, good drainage and appropriate binder selection need to be considered when undertaking rehabilitation designs with full-depth reclamation.

Performance analysis of air source heat pump system for office building

In this study, the performance of an air source heat pump system installed in a commercial building is analyzed using the developed heat pump performance model and building load simulation data of several regions in Korea. The performance test of an air source heat pump system with a variable speed compressor is tested to develop model that considers changes in the performance characteristics of the heat pump system under various operating conditions. The heat pump system is installed in an environmental chamber, and the experimental equipment is set up according to the manufacturer’s specifications as well as the AHRI 1230 test specifications. The performance test conditions of the heat pump system are selected using a central composite design method, in which 29 points for each cooling and heating mode are selected. The developed performance model based on experimental data predicts experimental values with an error of ±5 %. Building cooling and heating loads in three regions in Korea are analyzed using TRNSYS software, which includes standard building and weather data from Seoul, Daejeon and Busan in Korea. The effects of outdoor air temperature and part load ratio on the performance and regional monthly average power consumption of the heat pump system are analyzed.

Concrete performance subject to coupled deterioration in cold environments

The design of concrete durability is normally based on the assessment of its performance when subject to a single deterioration mechanism. In reality, concrete structures are subject to varying environmental exposure conditions which often results in multi-deterioration mechanisms occurring. The Nordic climate, with cold harsh winters, poses a severe challenge to the long-term durability of concrete. The most common deterioration mechanisms are freeze-thaw damage, carbonation and chloride induced corrosion. Research is now more focused on the assessment of coupled deterioration mechanisms. For instance, evaluating how cracks resulting from freeze-thaw influence chloride ingress, or how carbonation changes the surface properties and thereby influencing freeze-thaw scaling and chloride penetration.This paper presents the results of research projects at VTT focusing on coupling deterioration mechanisms. These research projects have built on several decades of concrete durability research at VTT, including 15years of field station studies. The durability of the concretes has been assessed using both accelerated laboratory testing and also from in situ exposure results from field stations. This research has contributed to the development of concrete performance models and service life tools, supporting a holistic approach for deterioration assessment.

Using Performance-Power Modeling to Improve Energy Efficiency of HPC Applications

Energy-efficient scientific applications require insight into how high-performance computing system features impact the applications' power and performance. This insight results from the development of performance and power models. When used with an earthquake simulation and an aerospace application, a proposed modeling framework reduces energy consumption by up to 48.65 percent and 30.67 percent, respectively.

Signal-to-interference-plus- noise-ratio analysis for constrained radar waveforms

To fully appreciate the benefits of arbitrary waveform design capability for transmit adaptive systems, the trade space between constraints (employed to increase the measure of practicality for radar) and the usual performance driver (signal-to-interference-plus-noise ratio) needs to be better defined and understood.We address this issue by developing performance models for radar waveforms with cumulative-modulus and energy constraints. Radar waveforms typically require a constant-modulus (constant-amplitude) transmit signal to efficiently exploit the available transmit power. However, recent hardware advances and the capability for arbitrary (phase and amplitude) designed waveforms have forced a reexamination of this assumption in order to quantify the impact of the nonconstant modulus property.We develop performance models for the signal-to-interference-plus-noise ratio as a function of the cumulative modulus for a random colored interference environment and validate the models against measured data.

Development and Implementation of Lithium-Ion Battery Performance and Capacity Fade Models for Resource Planning Tools

The usefulness of renewable sources of energy in grid applications is dependent on the energy storage technology (i.e., battery type) and how the storage medium is utilized. Research is underway to develop resource planning tools that can select an optimum equipment set and operate the components in an energy-efficient manner.1-3 In this work, an optimization framework is used to select equipment sets including diesel generators, wind energy, solar energy, and batteries based on the location, mission size and duration. Such optimization problems fall in the category of mixed integer nonlinear programming (MINLP) models whose instances require lengthy solve times depending on the nonlinearity involved.4 To make the optimization problem computationally tractable, simplifying and other techniques (e.g., covexification) can be used to convert the original MINLP to a mixed integer linear program (MIP). Battery models, being severely nonlinear, pose significant challenges in such an optimization framework (MIP). Previous efforts in this direction were focused on using linear model for lithium-ion batteries (derived from available data on a commercial lithium-ion battery) to be used with other energy sources.5 While these linear models captured the essence of lithium-ion battery performance, they lacked the ability to capture the typical temperature-dependent performance and capacity degradation. Ignoring these effects may lead to under-sizing of the battery capacity. These linear models can be improved in two ways: 1) addition of temperature effects in the performance model of a lithium-ion battery and 2) incorporating capacity fade effects during the utilization of a battery. While incorporating these effects in the battery model adds nonlinearities, simplifying assumptions and convexification are used to circumvent computational difficulties. Addition of these two effects in the battery model will improve the fidelity of the model used in the optimization framework and will give rise to realistic prediction in a resource planning tool. With the improved battery model in the optimization framework, several scenarios with different loads and weather conditions are being studied to derive the best possible energy mix to efficiently and economically deliver power to the desired location. Acknowledgements The work presented herein was funded by the Office of Naval Research.

Performance Modeling and Analysis of the IEEE 802.11p EDCA Mechanism for VANET

This paper studies performance modeling of the IEEE 802.11p enhanced distributed channel access (EDCA) mechanism and develops performance models to analyze the access performance of the IEEE 802.11p EDCA mechanism. A 2-D Markov chain is first constructed to model the backoff procedure of an access category (AC) queue and establish a relationship between the transmission probability and collision probability of the AC queue. Then, a 1-D discrete-time Markov chain is constructed to model the contention period of an AC queue and establish another relationship between the transmission probability and collision probability of the AC queue. Unlike most existing work, the 1-D Markov chain is extended to be infinite in modeling the contention period of an AC queue under both saturated and nonsaturated conditions. The two Markov models take into account all major factors that could affect the access performance of the IEEE 802.11p EDCA mechanism, including the saturation condition, standard parameters, backoff counter freezing, and internal collision. Based on the two Markov models, performance models are further derived to describe the relationships between the parameters of an AC queue and the access performance of the AC queue in terms of the transmission probability, collision probability, normalized throughput, and average access delay, respectively. The effectiveness of the performance models are verified through simulation results.

Full-Depth Reclamation: Cost-Effective Rehabilitation Strategy for Low-Volume Roads

Full-depth reclamation with or without various stabilizers has been successfully used as a rehabilitation strategy in California since 2001. Long-term field monitoring on a number of full-depth reclamation projects that use foamed asphalt with portland cement as the stabilizer combined with a comprehensive laboratory study resulted in the preparation of guidelines and specification language for this rehabilitation strategy in 2008. However, the design criteria were essentially empirical in line with California design procedures for this level of rehabilitation project. There has been growing interest in the use of full-depth reclamation with no stabilizer as a rehabilitation option for lower-volume roads and in the use of mechanistic design in a greater range of rehabilitation projects. Consequently, the research initiative was extended to a second phase to include accelerated load testing on an instrumented test track constructed with four full-depth reclamation strategies to gather data for the development of performance models that can be included in mechanistic–empirical rehabilitation design procedures. This paper summarizes the results of a set of tests in this accelerated loading study, which compared dry and wet performance of a pavement rehabilitated with full-depth reclamation without any stabilizer. The section performed well in terms of expected low-volume traffic (i.e., up to 500,000 equivalent single-axle wheel loads). Poorer performance under wet base course conditions emphasized the need for appropriate drainage on low-volume road structures. The findings indicate that full-depth reclamation with no stabilizer, followed by the placement of an appropriate surface treatment or thin asphalt concrete layer, is a potentially cost-effective rehabilitation strategy for distressed low-volume pavements.

Semimechanistic model describing gastric emptying and glucose absorption in healthy subjects and patients with type 2 diabetes.

The integrated glucose-insulin (IGI) model is a previously published semimechanistic model that describes plasma glucose and insulin concentrations after glucose challenges. The aim of this work was to use knowledge of physiology to improve the IGI model's description of glucose absorption and gastric emptying after tests with varying glucose doses. The developed model's performance was compared to empirical models. To develop our model, data from oral and intravenous glucose challenges in patients with type 2 diabetes and healthy control subjects were used together with present knowledge of small intestinal transit time, glucose inhibition of gastric emptying, and saturable absorption of glucose over the epithelium to improve the description of gastric emptying and glucose absorption in the IGI model. Duodenal glucose was found to inhibit gastric emptying. The performance of the saturable glucose absorption was superior to linear absorption regardless of the gastric emptying model applied. The semiphysiological model developed performed better than previously published empirical models and allows better understanding of the mechanisms underlying glucose absorption. In conclusion, our new model provides a better description and improves the understanding of dynamic glucose tests involving oral glucose.

Modeling of the resource allocation in cloud computing centers

Cloud computing offers on-demand network access to the computing resources through virtualization. This paradigm shifts the computer resources to the cloud, which results in cost savings as the users leasing instead of owning these resources. Clouds will also provide power constrained mobile users accessibility to the computing resources. In this paper, we develop performance models of these systems. We assume that jobs arrive to the system according to a Poisson process and they may have quite general service time distributions. Each job may consist of multiple numbers of tasks with each task requiring a virtual machine (VM) for its execution. The size of a job is determined by the number of its tasks, which may be a constant or a variable. The jobs with variable sizes may generate new tasks during their service times. In the case of constant job size, we allow different classes of jobs, with each class being determined through their arrival and service rates and number of tasks in a job. In the variable case a job generates randomly new tasks during its service time. The latter requires dynamic assignment of VMs to a job, which will be needed in providing service to mobile users. We model the systems with both constant and variable size jobs using birth–death processes. In the case of constant job size, we determined joint probability distribution of the number of jobs from each class in the system, job blocking probabilities and distribution of the utilization of resources for systems with both homogeneous and heterogeneous types of VMs. We have also analyzed tradeoffs for turning idle servers off for power saving. In the case of variable job sizes, we have determined distribution of the number of jobs in the system and average service time of a job for systems with both infinite and finite amount of resources. We have presented numerical results and any approximations are verified by simulation. The results of the paper may be used in the dimensioning of cloud computing centers.

Predicting Stock Market Exchange Prices for the Reserve Bank of Australia Using Auto-Regressive Feedforward Neural Network Model

Predicting foreign exchange prices is one of the challenging fields of research due to its complexity, dynamical and non-linearity. It is usually affected by many factors such as economic conditions, investors' expectations, governmental events, and of course Wars in various areas of the world. The process of predicting money exchange rate help organizations, governments and business market to make decisions; it is essential for determining information about future markets. This paper introduces the basic idea of developing predicting models for currency exchange rate using Artificial Neural Network (ANN) and Linear Regression (LR) models. The data set used in the experiments collected during January 4, 2010 to December 31, 2013. Number of criterion were used to validate the developed model's performance. The ANN model show promising results.

Automatic tuning of sparse matrix-vector multiplication on multicore clusters

To have good performance and scalability, parallel applications should be sophisticatedly optimized to exploit intra-node parallelism and reduce inter-node communication on multicore clusters. This paper investigates the automatic tuning of the sparse matrix-vector (SpMV) multiplication kernel implemented in a partitioned global address space language, which supports a hybrid thread- and process-based communication layer for multicore systems. One-sided communication is used for inter-node data exchange, while intra-node communication uses a mix of process shared memory and multithreading. We develop performance models to facilitate selecting the best configuration of threads and processes hybridization as well as the best communication pattern for SpMV. As a result, our tuned SpMV in the hybrid runtime environment consumes less memory and reduces inter-node communication volume, without damaging the data locality. Experiments are conducted on 12 real sparse matrices. On 16-node Xeon and 8-node Opteron clusters, our tuned SpMV kernel gets on average 1.4X and 1.5X improvement in performance over the well-optimized process-based message-passing implementation, respectively.