269,610 research outputs found

    Exploiting the Enumeration of All Feature Model Configurations

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    .Feature models are widely used to encode the configurations of a software product line in terms of mandatory, optional and exclusive features as well as propositional constraints over the features. Numerous computationally expensive procedures have been developed to model check, test, configure, debug, or compute relevant information of feature models. In this paper we explore the possible improvement of relying on the enumeration of all configurations when performing automated analysis operations. We tackle the challenge of how to scale the existing enumeration techniques by relying on distributed computing. We show that the use of distributed computing techniques might offer practical solutions to previously unsolvable problems and opens new perspectives for the automated analysis of software product lines.Junta de AndalucĂ­a P12-TIC-1867Ministerio de EconomĂ­a y Competitividad TIN2015- 70560-

    Optimisation multi-critère pour l'allocation de ressources sur clouds distribués avec prise en compte de l'énergie

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    International audienceReducing energy consumption is an increasingly important issue in cloud computing, more specifically when dealing with High Performance Computing (HPC). Minimizing energy consumption can significantly reduce the amount of energy bills and then increases the provider's profit. In addition, the reduction of energy decreases greenhouse gas emissions. Therefore, many researches are carried out to develop new methods in order to consume less energy. In this paper, we present a multi-objective genetic algorithm (MO-GA) that optimizes the energy consumption, CO2 emissions and the generated profit of a geographically distributed cloud computing infrastructure. We also propose a heuristic that aims to maximize the number of scheduled applications in order to compare it with the MO-GA. The two approaches have been experimented using realistic workload traces from Feitelson's Parallel Workload Archive (PWA). The results show that MO-GA outperforms the heuristic by a significant margin in terms of energy consumption and CO2 emissions. In addition, MO-GA is also proved to be slightly better in terms of profit while scheduling more applications. We also propose in the perspectives how to integrate our approach in the project StratusLab for the exploitation of the geographical dispersion offered by EGI

    Introduction

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    Professor Joan C. Williams “seeks to build bridges” across audiences and disciplines with her latest book, Reshaping the Work-Family Debate: Why Men and Class Matter. She also attempts to bridge seemingly insuperable chasms of gender and class, to encourage the formation of a political coalition that is simultaneously profamily and prowork. In Web 2.0 argot, “crowdsourcing” is a distributed, networked computing method of solving problems through the combination of ideas from individual sources and different perspectives. This issue of the Seattle University Law Review features ten other distinguished legal scholars who add their designs to Williams’s bridge blueprint through scholarly crowdsourcing. Their approaches result in surprising, sometimes provocative new ideas for cultural, legal, and policy reform at the nexus of work and family

    Research on advanced technologies – design and development of cloud computing model

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    This article is a bibliographic review and focuses on a brief introduction to Cloud Computing as an innovative educational tool. Cloud technology is rapidly spreading in educational institutions, sometimes replacing the in-house infrastructure with cloud services. Education plays an important role in a country’s economy and today, the educational model in many countries has evolved with technology. Schools and universities in the world extensively use cloud Based Technology. Digital teaching – E-Learning and cloud-based technology are the latest models that have been widely adopted in the educational field. The identified trends in the use of cloud computing in education are clear, ranging from the design of cloud-oriented learning environments for future information technology specialists to the training of information technology specialists to enable them to obtain competencies in the use of cloud technologies. Cloud computing is a distributed computing paradigm, where, instead of acquiring information technology products, users access shared resources under various service models through a network, usually the Internet. The application of cloud computing is very broad and growing daily because of many advantages to the users, and is driven by the increasing use of various mobile devices (laptops, tablets and smartphones) and mobile Internet access being more available. The perspectives of its integration in the learning process are highlighted, as well as the factors that make its implementation difficult. Finally, some general conclusions presented on how technologies should be adopted to meet the educational needs of this new global challenge and some suggestions are made for more effective training through the Cloud Computing, as the need for further research emerge

    The Futures of Computing and Wisdom

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    There has been an increasing interest in discussing the consequences of the technologies we invent and study in HCI. Whether it is climate change, ethical computing, capitalist and neo-liberal models of commerce and society, grassroots movements, big data or alternative paradigms in distributed systems, this workshop will invite participants to explore these consequences and ask how we move forward with responsibility and new forms of knowing and knowledge. We invite participants to join us, as we cast forward fifty years to 2068 to imagine the future of wisdom, and to reflect on how we got there. By writing Fictional Abstracts, an abstract from a research paper yet to be written, we will unpick critical tensions in the advancement of computing over the next decades. The workshop will develop perspectives on the futures of computing and critically reflect on the assumptions, methods, and tools for enabling (and disabling) such futures

    Large Scale In Silico Screening on Grid Infrastructures

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    Large-scale grid infrastructures for in silico drug discovery open opportunities of particular interest to neglected and emerging diseases. In 2005 and 2006, we have been able to deploy large scale in silico docking within the framework of the WISDOM initiative against Malaria and Avian Flu requiring about 105 years of CPU on the EGEE, Auvergrid and TWGrid infrastructures. These achievements demonstrated the relevance of large-scale grid infrastructures for the virtual screening by molecular docking. This also allowed evaluating the performances of the grid infrastructures and to identify specific issues raised by large-scale deployment.Comment: 14 pages, 2 figures, 2 tables, The Third International Life Science Grid Workshop, LSGrid 2006, Yokohama, Japan, 13-14 october 2006, to appear in the proceeding
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