94,094 research outputs found

    Reliability Guided Resource Allocation for Large-scale Supercomputing Systems

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    In high performance computing systems, parallel applications request a large number of resources for long time periods. In this scenario, if a resource fails during the application runtime, it would cause all applications using this resource to fail. The probability of application failure is tied to the inherent reliability of resources used by the application. Our investigation of high performance computing systems operating in the field has revealed a significant difference in the measured operational reliability of individual computing nodes. By adding awareness of the individual system nodes\u27 reliability to the scheduler along with the predicted reliability needs of parallel applications, reliable resources can be matched with the most demanding applications to reduce the probability of application failure arising from resource failure. In this thesis, the researcher describes a new approach developed for resource allocation that can enhance the reliability and reduce the costs of failures of large-scale parallel applications that use high performance computing systems. This approach is based on a multi-class Erlang loss system that allows us to partition system resources based on predicted resource reliability, and to size each of these partitions to bound the probability of blocking requests to each partition while simultaneously improving the reliability of the most demanding parallel applications running on the system. Using this model, the partition mean time to failure (MTTF) is maximized and the probability of blocking of resource requests directed to each partition by a scheduling system can be controlled. This new technique can be used to determine the size of the system, to service peak loads with a bounded probability of blocking to resource requests. This approach would be useful for high performance computing system operators seeking to improve the reliability, efficiency and cost-effectiveness of their systems

    Meditation Awareness Training (MAT) for Work-related Wellbeing and Job Performance: A Randomised Controlled Trial

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    Due to its potential to concurrently improve work-related wellbeing (WRW) and job performance, occupational stakeholders are becoming increasingly interested in the applications of meditation. The present study conducted the first randomized controlled trial to assess the effects of meditation on outcomes relating to both WRW and job performance. Office-based middle-hierarchy managers (n = 152) received an eight-week meditation intervention (Meditation Awareness Training; MAT) or an active control intervention. MAT participants demonstrated significant and sustainable improvements (with strong effect sizes) over control-group participants in levels of work-related stress, job satisfaction, psychological distress, and employer-rated job performance. There are a number of novel implications: (i) meditation can effectuate a perceptual shift in how employees experience their work and psychological environment and may thus constitute a cost-effective WRW intervention, (ii) meditation-based (i.e., present-moment-focussed) working styles may be more effective than goal-based (i.e., future-orientated) working styles, and (iii) meditation may reduce the separation made by employees between their own interests and those of the organizations they work for

    A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing

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    Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases. We then provide comprehensive taxonomies that cover various aspects of architecture, data transportation, data replication and resource allocation and scheduling. Finally, we map the proposed taxonomy to various Data Grid systems not only to validate the taxonomy but also to identify areas for future exploration. Through this taxonomy, we aim to categorise existing systems to better understand their goals and their methodology. This would help evaluate their applicability for solving similar problems. This taxonomy also provides a "gap analysis" of this area through which researchers can potentially identify new issues for investigation. Finally, we hope that the proposed taxonomy and mapping also helps to provide an easy way for new practitioners to understand this complex area of research.Comment: 46 pages, 16 figures, Technical Repor

    Cloud computing resource scheduling and a survey of its evolutionary approaches

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    A disruptive technology fundamentally transforming the way that computing services are delivered, cloud computing offers information and communication technology users a new dimension of convenience of resources, as services via the Internet. Because cloud provides a finite pool of virtualized on-demand resources, optimally scheduling them has become an essential and rewarding topic, where a trend of using Evolutionary Computation (EC) algorithms is emerging rapidly. Through analyzing the cloud computing architecture, this survey first presents taxonomy at two levels of scheduling cloud resources. It then paints a landscape of the scheduling problem and solutions. According to the taxonomy, a comprehensive survey of state-of-the-art approaches is presented systematically. Looking forward, challenges and potential future research directions are investigated and invited, including real-time scheduling, adaptive dynamic scheduling, large-scale scheduling, multiobjective scheduling, and distributed and parallel scheduling. At the dawn of Industry 4.0, cloud computing scheduling for cyber-physical integration with the presence of big data is also discussed. Research in this area is only in its infancy, but with the rapid fusion of information and data technology, more exciting and agenda-setting topics are likely to emerge on the horizon

    Improving water productivity in agriculture in developing economies: in search of new avenues

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    Water ProductivityCrop productionWheatCottonEvapotranspirationEcnomic aspects

    RISK ASSESSMENT OF MALICIOUS ATTACKS AGAINST POWER SYSTEMS

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    The new scenarios of malicious attack prompt for their deeper consideration and mainly when critical systems are at stake. In this framework, infrastructural systems, including power systems, represent a possible target due to the huge impact they can have on society. Malicious attacks are different in their nature from other more traditional cause of threats to power system, since they embed a strategic interaction between the attacker and the defender (characteristics that cannot be found in natural events or systemic failures). This difference has not been systematically analyzed by the existent literature. In this respect, new approaches and tools are needed. This paper presents a mixed-strategy game-theory model able to capture the strategic interactions between malicious agents that may be willing to attack power systems and the system operators, with its related bodies, that are in charge of defending them. At the game equilibrium, the different strategies of the two players, in terms of attacking/protecting the critical elements of the systems, can be obtained. The information about the attack probability to various elements can be used to assess the risk associated with each of them, and the efficiency of defense resource allocation is evidenced in terms of the corresponding risk. Reference defense plans related to the online defense action and the defense action with a time delay can be obtained according to their respective various time constraints. Moreover, risk sensitivity to the defense/attack-resource variation is also analyzed. The model is applied to a standard IEEE RTS-96 test system for illustrative purpose and, on the basis of that system, some peculiar aspects of the malicious attacks are pointed ou
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