Your search

In order to understand network technology it is important to know how information is represented for transmission from one computer to another. Information can be transferred between computers in one of two ways: an analog signal or a digital signal.

Dynamic voltage and frequency scaling (DVFS) is a well-known technique to optimize the power dissipation of electronic systems without significantly compromising overall system performance. DVFS exploits the periods of inter-core data exchange (memory-bound operations) to reduce the voltage and frequency (V/F) of the cores in order to reduce the power dissipation during the execution flow of an application running on the CMP. As the lengths of the idle and busy periods of the cores vary depending on the benchmarks, it is crucial for any DVFS technique to maximize the power saving without losing a significant performance. In this work we present two power optimization methodologies that are integrated into a full-system simulator to make online predictions about the voltage and frequency of the cores during the execution time of the benchmarks. We evaluate these methodologies in terms of the V/F predictions vs. the actual utilization of each core periodically. We also compare the overall execution time, energy dissipation, and energy-delay product (EDP) of the power optimization methodologies for various benchmarks. © 2015 IEEE.

We find that the relative preference of hedonic products is disproportionately enhanced when they are offered at a free price. This “free price bounce” is more subdued for utilitarian products. This is surprising because rational choice theory posits that relative preference amidst two options - say a hedonic and a utilitarian product - remains intact as long as the price difference between them is constant. We propose and demonstrate that this axiom is violated when a hedonic product is offered for free. (C) 2015 Elsevier B.V. All rights reserved.

Given the popularity of PHP frameworks used in developing webbased applications, a comparative study is conducted to determine which framework is best suited for incorporation into the curriculum of an undergraduate software engineering course that uses project-based learning. The top six PHP frameworks (Zend, Yii, CakePHP, CodeIgniter, PRADO, and Symphony) were initially considered and then narrowed down to two (CakePHP and CodeIgniter) based on their alignment with common functionality in previous class projects, framework complexity for those new to frameworks (learning curve), and developer friendliness (availability of documentation and online resources). An in-depth comparative study is conducted by developing a functionally-equivalent web application using each of the two frameworks as well as plain PHP (no framework). This work was motivated by the difficulties that were encountered in an evolving, content-rich software engineering course and discusses the educational changes that were made to align student learning with sound software engineering principles and current software development practices used in the computing industry. Copyright © 2013 ACM.

In this paper, we examined why information searchers perceive search tasks as difficult, and what factors/reasons make them perceive tasks as difficult. We also examined if task difficulty reasons vary across different tasks (task types). Data was collected through a controlled laboratory experiment in which tasks were designed following a classification scheme. A total of 32 undergraduate students participated, each was given 4 search tasks, and they were asked in questionnaires both before and after the tasks for task difficulty ratings and why they gave those ratings. We developed a coding scheme based on the difficulty reasons users gave, which covered various aspects of task, user, and user-task interaction. Difficulty reasons were categorized following this scheme. Results showed that searchers had some common reasons for task difficulty in different tasks, but most of the difficulty reasons varied across tasks. For each task, there were also common reasons for task difficulty, although there was some variation here as well. Task difficulty was also found to be negatively correlated with users topic knowledge, previous experience, and topic interest. Our findings help understand search task difficulty, as well as the relationships between task difficulty and task type, knowledge background, etc. These can also be helpful with experiment task design. © 2013 ACM.

This paper reports on an examination of why information searchers find search tasks difficult and the specific reasons they feel difficult. Data was collected through a controlled laboratory experiment with 32 participants, each working with 4 search tasks. They were asked in questionnaires, both before and after the tasks, for task difficulty ratings and their reasoning for giving those ratings. We developed a coding scheme based on the difficulty reasons users gave, which covered various aspects of task, user, and user-task interaction. This helps us understand search task difficulty, as well as provides a scheme for task difficulty control in experiment task design.

Research and training in atmospheric lidar remote sensing requires highly versatile software environments for both experimentation and analysis. Experimentation and analysis may be conducted either directly on site at the location of the lidar equipment and/or institutional computer center or remotely from a distant location. The requirements for lidar software environments depend not only on type of user access (remote or onsite) but also on the nature of the teaching or research missions they support and the characteristics of the lidar systems for which they are used. The software environments discussed in this paper have been used to support lidar aerosol studies in settings ranging from urban locations to a remote atmospheric baseline station. Experiments and data analysis studies have been conducted for two different ground-based lidar systems, a monostatic Micro Pulse Lidar system and a bistatic imaging lidar system. © 2013 IEEE.

We consider the problem of propagating an update to nodes in a distributed system using two gossiping protocols. The first is an idealized algorithm with static and dynamic knowledge of the system, and the second is a simple randomized algorithm. We construct a theoretical model that allows us to derive work and completion time statistics under varying transmission delay distributions. Numerical results are obtained for both exponential and nonexponential transmission times using linear-algebraic queueing theory techniques. Additionally, we present the results of simulation experiments showing that under node churn assumptions, the randomized algorithm's performance is qualitatively different than in a fault-free system. © 2010 IEEE.

To accommodate execution mode change and hardware malfunction, dynamic system reconfiguration, which invokes application migration across different processing cores, needs to be supported on multi-core embedded systems. Different application migration strategies will impact system's timing behaviors in different manners, it is important to select an appropriate one such that the system's timing performance after the migration process is still acceptable. The focus of our research is to predict the system's timing change of possible migration strategies and upon which to choose the optimal one. Extensive experiments have been set up by running multiple benchmarks and experimental results validate the effectiveness of our proposed approach.

Reliability, longevity, availability, and deadline guarantees are the four most important metrics to measure the QoS of long-running safety-critical real-time applications. Software aging is one of the major factors that impact the safety of long-running real-time applications as the degraded performance and increased failure rate caused by software aging can lead to deadline missing and catastrophic consequences. Software rejuvenation is one of the most commonly used approaches to handle issues caused by software aging. In this paper, we study the optimal time when software rejuvenation shall take place so that the system's reliability, longevity, and availability are maximized, and application delays caused by software rejuvenation is minimized. In particular, we formally analyze the relationships between software rejuvenation frequency and system reliability, longevity, and availability. Based on the theoretic analysis, we develop approaches to maximizing system reliability, longevity, and availability, and use simulation to evaluate the developed approaches. In addition, we design the MIN-DELAY semi-priority-driven scheduling algorithm to minimize application delays caused by rejuvenation processes. The simulation experiments show that the developed semi-priority-driven scheduling algorithm reduces application delays by 9.01% and 14.24% over the earliest deadline first (EDF) and least release time (LRT) scheduling algorithms, respectively.

Researches in real-time scheduling often assume that the performance of a computing resource does not change overtime. However, as system softwares and system architectures become increasingly complex, resource performance degradation over time becomes more evident. In this paper, we study the schedulability of a hard real-time task set on a resource which has performance degradation over time with a known pattern and use both cold and warm periodic rejuvenations as countermeasures. Such resource model is referred to as P2D-resource model for performance degradation and periodic rejuvenation with dual-levels. In this paper, we study (1) the formal specification of the P2D-resource model, (2) P2D-resource supply analysis, and (3) task set utilization bounds of a P2D-resource under Earliest Deadline First (EDF) and Rate Monotonic (RM) scheduling policies.

Measurements of parameters in electricity grids are frequently captured as average values over some time interval. In scenarios of distributed measurements such as in distribution grids, offsets of local clocks can result in misaligned averaging intervals. This paper investigates the properties of the so-called time alignment error of such measurands that is caused by shifts of the averaging interval. We extend a previously derived Markov-modulated model and provide an approximation of the variance of the time alignment error. The model accounts for slow-decaying correlation structure found in actual traces of electrical measures. We compare results of three electrical measures for 20 traces with numerical results and simulations from the the fitted Markov model. © 2019 IEEE.

This work proposes a new approach in addressing Economic Load Dispatch (ELD) optimization problem in power unit systems using nature-inspired metaheuristics search algorithms. Solving such a problem requires a degree of maximization of the economic pact of a power network system, where this is possible with some existing population-based metaheuristic search algorithms. The key issue to be handled here is how to maximize the economic benevolence of a power network under a variety of operational constraints, taking into account the reduction in the generated fuel cost as well as the aggregate power loss in the transmission power network system. Some nature-inspired metaheuristics will be explored. Meanwhile, we shall focus our attention on a newly developed nature-inspired search algorithm, referred to as the Crow Search Algorithm or CSA for short, as well as the Differential Evolution (DE) that is commonly known as a metaheuristic. The CSA emerged to light by simulating the intelligent flocking behavior of crows. The practicability of the proposed approach-based CSA was conducted to common types of power generators, including three and six buses (nodes) in addition to the IEEE 30-bus standard system. The results of the presented approaches were compared to other results developed using existing nature-inspired metaheuristic algorithms like particle swarm optimization and genetic algorithms and also compared to traditional approaches such as quadratic programming method. The results reported here support that CSA has achieved an outstanding performance in solving the problem of ELD in power systems, demonstrating their good optimization capabilities through arriving at a combination of power loads that consummate the constraints of the ELD problem while simultaneously lessening the entire fuel cost. The experimental results also showed that the CSA solutions were capable of maximizing the reliability of the power supplied to the customers, and also reducing both the generated power cost and the loss of power in the transmission power systems.

Regrettably, a large proportion of likely patients with sleep apnea are underdiagnosed. Obstructive sleep apnea (OSA) is one of the main causes of hypertension, type II diabetes, stroke, coronary artery disease, and heart failure. OSA affects not only adults but also children where it forms one of the sources of learning disabilities for children. This study aims to provide a classification model for one of the well-known sleep disorders known as OSA, which causes a serious malady that affects both men and women. OSA affects both genders with different scope. Men versus women diagnosed with OSA are about 8:1. In this research, logistic regression (LR) and artificial neural networks were applied successfully in several classification applications with promising results, particularly in the bio-statistics area. LR was used to derive a membership probability for a potential OSA system from a range of anthropometric features including weight, height, body mass index (BMI), hip, waist, age, neck circumference, modified Friedman, snoring, Epworth sleepiness scale (ESS), sex, and daytime sleepiness. We developed two models to predict OSA, one for men and one for women. The proposed sleep apnea diagnosis model has yielded accurate classification results and possibly a prototype software module that can be used at home. These findings shall reduce the patient’s need to spend a night at a laboratory and make the study of sleep apnea to implement at home.