998 resultados para Could computing


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In an enterprise grid computing environments, users have access to multiple resources that may be distributed geographically. Thus, resource allocation and scheduling is a fundamental issue in achieving high performance on enterprise grid computing. Most of current job scheduling systems for enterprise grid computing provide batch queuing support and focused solely on the allocation of processors to jobs. However, since I/O is also a critical resource for many jobs, the allocation of processor and I/O resources must be coordinated to allow the system to operate most effectively. To this end, we present a hierarchical scheduling policy paying special attention to I/O and service-demands of parallel jobs in homogeneous and heterogeneous systems with background workload. The performance of the proposed scheduling policy is studied under various system and workload parameters through simulation. We also compare performance of the proposed policy with a static space–time sharing policy. The results show that the proposed policy performs substantially better than the static space–time sharing policy.

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The advent of commodity-based high-performance clusters has raised parallel and distributed computing to a new level. However, in order to achieve the best possible performance improvements for large-scale computing problems as well as good resource utilization, efficient resource management and scheduling is required. This paper proposes a new two-level adaptive space-sharing scheduling policy for non-dedicated heterogeneous commodity-based high-performance clusters. Using trace-driven simulation, the performance of the proposed scheduling policy is compared with existing adaptive space-sharing policies. Results of the simulation show that the proposed policy performs substantially better than the existing policies.

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Deployment of applications and scientific workflows that require resources from multiple distributed platforms are fuelling the federation of autonomous clouds to create cyber infrastructure environments. As the scope of federated cloud computing enlarges to ubiquitous and pervasive computing, there will be a need to assess and maintain the trustworthiness of the cloud computing entities. In this paper, we present a fully distributed framework that enable interested parties determine the trustworthiness of federated cloud computing entities.

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The overall performance of a distributed system often depends on the effectiveness of its interconnection network. Thus, the study of the communication networks for distributed systems–which is the focus of this paper–is very important. In particular, we address the problem of fat-tree based interconnection networks performance modeling for multi-user heterogeneous multi-cluster computing systems. To this end, we present an analytical model and validate the model through comprehensive simulation. The results of the simulation demonstrate that the proposed model exhibits a good degree of accuracy for various system organizations and under different working conditions. On the basis of the validated model, we propose an adaptive assignment function based on the existing heterogeneity of the system to minimize multi-user environment overhead.

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Purpose – The purpose of this paper is to explore characteristics of human-computer interaction when the human body and its movements become input for interaction and interface control in pervasive computing settings.

Design/methodology/approach –
The paper quantifies the performance of human movement based on Fitt's Law and discusses some of the human factors and technical considerations that arise in trying to use human body movements as an input medium.

Findings – The paper finds that new interaction technologies utilising human movements may provide more flexible, naturalistic interfaces and support the ubiquitous or pervasive computing paradigm.

Practical implications –
In pervasive computing environments the challenge is to create intuitive and user-friendly interfaces. Application domains that may utilize human body movements as input are surveyed here and the paper addresses issues such as culture, privacy, security and ethics raised by movement of a user's body-based interaction styles.

Originality/value –
The paper describes the utilization of human body movements as input for interaction and interface control in pervasive computing settings.

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When using linguistic approaches to solve decision problems, we need the techniques for computing with words (CW). Together with the 2-tuple fuzzy linguistic representation models (i.e., the Herrera and Mart´ınez model and the Wang and Hao model), some computational techniques for CW are also developed. In this paper, we define the concept of numerical scale and extend the 2-tuple fuzzy linguistic representation models under the numerical scale.We find that the key of computational techniques
based on linguistic 2-tuples is to set suitable numerical scale with
the purpose of making transformations between linguistic 2-tuples
and numerical values. By defining the concept of the transitive
calibration matrix and its consistent index, this paper develops an optimization model to compute the numerical scale of the linguistic term set. The desired properties of the optimization model are also presented. Furthermore, we discuss how to construct the transitive calibration matrix for decision problems using linguistic preference relations and analyze the linkage between the consistent index of the transitive calibration matrix and one of the linguistic preference relations. The results in this paper are pretty helpful to complete the fuzzy 2-tuple representation models for CW.

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This review examines the current state of knowledge related to the location of fast food restaurants. Previous studies have revealed some communities are more exposed to fast food restaurants. However, the influence of increased exposure to fast food on dietary behaviours remains unresolved. This is identified as an area of priority for future research.

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Provides an overview of current research by the author and related Australian scholars on the problem of vigilantism as a question of media representation, as opposed to a substantive crime prevention trend. Implications of this research discussed for a professional security audience.

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Cloud computing is offering utility-oriented IT services to users worldwide. Based on a pay-as-you-go model, it enables hosting of pervasive applications from consumer, scientific, and business domains. However, data centers hosting Cloud applications consume huge amounts of energy, contributing to high operational costs and carbon footprints to the environment. Therefore, we need Green Cloud computing solutions that can not only save energy for the environment but also reduce operational costs. This paper presents vision, challenges, and architectural elements for energy-efficient management of Cloud computing environments. We focus on the development of dynamic resource provisioning and allocation algorithms that consider the synergy between various data center infrastructures (i.e., the hardware, power units, cooling and software), and holistically work to boost data center energy efficiency and performance. In particular, this paper proposes (a) architectural principles for energy-efficient management of Clouds; (b) energy-efficient resource allocation policies and scheduling algorithms considering quality-of-service expectations, and devices power usage characteristics; and (c) a novel software technology for energy-efficient management of Clouds. We have validated our approach by conducting a set of rigorous performance evaluation study using the CloudSim toolkit. The results demonstrate that Cloud computing model has immense potential as it offers significant performance gains as regards to response time and cost saving under dynamic workload scenarios.

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There is growing worldwide interest in Japanese Lesson Study as a form of professional development, with adaptations of Lesson Study taking place in hundreds of schools clusters in USA, large-scale adoption in the UK, and smaller scale implementation in Australia, and many other countries, including Chile, Indonesia, Malaysia, Mexico, Peru, Philippines, Singapore, Thailand, and Vietnam. This presentation will use classroom video to illustrate the typical Japanese structured-problem-solving research lessons that form the basis for Lesson Study, and discuss how they are planned, the role of the teacher, and the use of Lesson Study as a means of professional
development.

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While the nascent Cloud Computing paradigm supported by virtualization has the upward new notion of edges, it lacks proper security and trust mechanisms. Edges are like on demand scalability and infinite resource provisioning as per the `pay-as-you-go' manner in favour of a single information owner (abbreviated as INO from now onwards) to multiple corporate INOs. While outsourcing information to a cloud storage controlled by a cloud service provider (abbreviated as CSP from now onwards) relives an information owner of tackling instantaneous oversight and management needs, a significant issue of retaining the control of that information to the information owner still needs to be solved. This paper perspicaciously delves into the facts of the Cloud Computing security issues and aims to explore and establish a secure channel for the INO to communicate with the CSP while maintaining trust and confidentiality. The objective of the paper is served by analyzing different protocols and proposing the one in commensurate with the requirement of the security property like information or data confidentiality along the line of security in Cloud Computing Environment (CCE). To the best of our knowledge, we are the first to derive a secure protocol by successively eliminating the dangling pitfalls that remain dormant and thereby hamper confidentiality and integrity of information that is worth exchanging between the INO and the CSP. Besides, conceptually, our derived protocol is compared with the SSL from the perspectives of work flow related activities along the line of secure trusted path for information confidentiality.

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One reason for semi-supervised clustering fail to deliver satisfactory performance in document clustering is that the transformed optimization problem could have many candidate solutions, but existing methods provide no mechanism to select a suitable one from all those candidates. This paper alleviates this problem by posing the same task as a soft-constrained optimization problem, and introduces the salient degree measure as an information guide to control the searching of an optimal solution. Experimental results show the effectiveness of the proposed method in the improvement of the performance, especially when the amount of priori domain knowledge is limited.

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Many intervention programmes to increase the number of women in theInformation and Communications Technology (ICT) profession have been implemented over the last twenty years. Detailed evaluations help us to determine the effectiveness of these programmes yet few comprehensive evaluations appear in the literature.The research reported here describes an investigation of the evaluation of the intervention programmes focusing on increasing the enrolment and retention of females in ICT in Australia. This paper describes an empirical study which explores how evaluation has been and might be conducted and concludes with guidelines for evaluation for those developing programmes for increasing the participation of women in ICT.The guidelines encourage evaluation to be considered early, highlight the importance of establishing objective outcomes and promote the publication of results to build knowledge for those planning programmes in the future. Further, the developed guidelines could adapted and used with other ICT intervention programs.