941 resultados para Multiprocessor scheduling with resource sharing
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In this paper, we develop an energy-efficient resource-allocation scheme with proportional fairness for downlink multiuser orthogonal frequency-division multiplexing (OFDM) systems with distributed antennas. Our aim is to maximize energy efficiency (EE) under the constraints of the overall transmit power of each remote access unit (RAU), proportional fairness data rates, and bit error rates (BERs). Because of the nonconvex nature of the optimization problem, obtaining the optimal solution is extremely computationally complex. Therefore, we develop a low-complexity suboptimal algorithm, which separates subcarrier allocation and power allocation. For the low-complexity algorithm, we first allocate subcarriers by assuming equal power distribution. Then, by exploiting the properties of fractional programming, we transform the nonconvex optimization problem in fractional form into an equivalent optimization problem in subtractive form, which includes a tractable solution. Next, an optimal energy-efficient power-allocation algorithm is developed to maximize EE while maintaining proportional fairness. Through computer simulation, we demonstrate the effectiveness of the proposed low-complexity algorithm and illustrate the fundamental trade off between energy and spectral-efficient transmission designs.
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Copia is a retrotransposon that appears to be distributed widely among the Drosophilidae subfamily. Evolutionary analyses of regulatory regions have indicated that the Copia retrotransposon evolved through both positive and purifying selection, and that horizontal transfer (HT) could also explain its patchy distribution of the among the subfamilies of the melanogaster subgroup. Additionally, Copia elements could also have transferred between melanogaster subgroup and other species of Drosophilidae-D. willistoni and Z. tuberculatus. In this study, we surveyed seven species of the Zaprionus genus by sequencing the LTR-ULR and reverse transcriptase regions, and by using RT-PCR in order to understand the distribution and evolutionary history of Copia in the Zaprionus genus. The Copia element was detected, and was transcriptionally active, in all species investigated. Structural and selection analysis revealed Zaprionus elements to be closely related to the most ancient subfamily of the melanogaster subgroup, and they seem to be evolving mainly under relaxed purifying selection. Taken together, these results allowed us to classify the Zaprionus sequences as a new subfamily-ZapCopia, a member of the Copia retrotransposon family of the melanogaster subgroup. These findings indicate that the Copia retrotransposon is an ancient component of the genomes of the Zaprionus species and broaden our understanding of the diversity of retrotransposons in the Zaprionus genus.
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In 2006 the Route load balancing algorithm was proposed and compared to other techniques aiming at optimizing the process allocation in grid environments. This algorithm schedules tasks of parallel applications considering computer neighborhoods (where the distance is defined by the network latency). Route presents good results for large environments, although there are cases where neighbors do not have an enough computational capacity nor communication system capable of serving the application. In those situations the Route migrates tasks until they stabilize in a grid area with enough resources. This migration may take long time what reduces the overall performance. In order to improve such stabilization time, this paper proposes RouteGA (Route with Genetic Algorithm support) which considers historical information on parallel application behavior and also the computer capacities and load to optimize the scheduling. This information is extracted by using monitors and summarized in a knowledge base used to quantify the occupation of tasks. Afterwards, such information is used to parameterize a genetic algorithm responsible for optimizing the task allocation. Results confirm that RouteGA outperforms the load balancing carried out by the original Route, which had previously outperformed others scheduling algorithms from literature.
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The aim of task scheduling is to minimize the makespan of applications, exploiting the best possible way to use shared resources. Applications have requirements which call for customized environments for their execution. One way to provide such environments is to use virtualization on demand. This paper presents two schedulers based on integer linear programming which schedule virtual machines (VMs) in grid resources and tasks on these VMs. The schedulers differ from previous work by the joint scheduling of tasks and VMs and by considering the impact of the available bandwidth on the quality of the schedule. Experiments show the efficacy of the schedulers in scenarios with different network configurations.
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The aim of this degree thesis is to see what research says about the use of computer and video games to support upper elementary pupils’ development in English reading comprehension in Swedish schools. Other goals are to see how online and offline gaming can be integrated in the Swedish schools and what attitudes teachers have towards gaming. The method used is a systematic literature review and the purpose is to analyze chosen articles and to find relevant content that answers the research questions. Five articles were chosen from different databases and were systematically analyzed in this thesis. The results show that online gaming as support for education can be rewarding for some upper elementary pupils in English learning. However, in English reading comprehension there is not much research found which means that more research needs to be made within this area. Moreover, involving online gaming in English language learning seems to be a challenge for teachers mostly because of their lack of knowledge about the subject, even though they are positive to gaming. The lack of knowledge about the subject could be altered with more education and courses in the area.
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HydroShare is an online, collaborative system being developed for open sharing of hydrologic data and models. The goal of HydroShare is to enable scientists to easily discover and access hydrologic data and models, retrieve them to their desktop or perform analyses in a distributed computing environment that may include grid, cloud or high performance computing model instances as necessary. Scientists may also publish outcomes (data, results or models) into HydroShare, using the system as a collaboration platform for sharing data, models and analyses. HydroShare is expanding the data sharing capability of the CUAHSI Hydrologic Information System by broadening the classes of data accommodated, creating new capability to share models and model components, and taking advantage of emerging social media functionality to enhance information about and collaboration around hydrologic data and models. One of the fundamental concepts in HydroShare is that of a Resource. All content is represented using a Resource Data Model that separates system and science metadata and has elements common to all resources as well as elements specific to the types of resources HydroShare will support. These will include different data types used in the hydrology community and models and workflows that require metadata on execution functionality. The HydroShare web interface and social media functions are being developed using the Drupal content management system. A geospatial visualization and analysis component enables searching, visualizing, and analyzing geographic datasets. The integrated Rule-Oriented Data System (iRODS) is being used to manage federated data content and perform rule-based background actions on data and model resources, including parsing to generate metadata catalog information and the execution of models and workflows. This presentation will introduce the HydroShare functionality developed to date, describe key elements of the Resource Data Model and outline the roadmap for future development.
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This paper analyzes the impact of profit sharing on the incentives that individuals face to set up their own business. It presents a model of capital accumulation in which individuals are equally skilled to be workers but differ in their abilities to manage a firm Given an exogenous profit sharing parameter, an individual chooses whether to be an employer or an employee in order to maximize his net income. It is shown that profit sharing can inhibit entrepreneurial initiatives, reducing the number of firms in operation, the aggregate output and the economy's long run capital stock.
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This paper analyzes the impact of profit sharing on the incentives that individuals face to set up their own business. It presents a model of capital accumulation in which individuals are equally skilled to be workers but differ in their abilities to manage a firmo It is shown that profit sharing can inhibit entrepreneurial initiatives, reducing the number of firms in operation, the aggregate output and the economy's long run capital stock.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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A lot sizing and scheduling problem from a foundry is considered in which key materials are produced and then transformed into many products on a single machine. A mixed integer programming (MIP) model is developed, taking into account sequence-dependent setup costs and times, and then adapted for rolling horizon use. A relax-and-fix (RF) solution heuristic is proposed and computationally tested against a high-performance MIP solver. Three variants of local search are also developed to improve the RF method and tested. Finally the solutions are compared with those currently practiced at the foundry.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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This paper studies the use of different population structures in a Genetic Algorithm (GA) applied to lot sizing and scheduling problems. The population approaches are divided into two types: single-population and multi-population. The first type has a non-structured single population. The multi-population type presents non-structured and structured populations organized in binary and ternary trees. Each population approach is tested on lot sizing and scheduling problems found in soft drink companies. These problems have two interdependent levels with decisions concerning raw material storage and soft drink bottling. The challenge is to simultaneously determine the lot sizing and scheduling of raw materials in tanks and products in lines. Computational results are reported allowing determining the better population structure for the set of problem instances evaluated. Copyright 2008 ACM.