8 research outputs found

    Improving utilization of heterogeneous clusters

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    Datacenters often agglutinate sets of nodes with different capabilities, leading to a sub-optimal resource utilization. One of the best ways of improving utilization is to balance the load by taking into account the heterogeneity of these clusters. This article presents a novel way of expressing computational capacity, more adequate for heterogeneous clusters, and also advocates for task migration in order to further improve the utilization. The experimental evaluation shows that both proposals are advantageous and allow improving the utilization of heterogeneous clusters and reducing the makespan to 16.7% and 17.1%, respectively.This work has been supported by the Spanish Science and Technology Commission under contracts TIN2016-76635-C2-2-R and TIN2016-81840-REDT (CAPAP-H6 network) and the European HiPEAC Network of Excellenc

    Heterogeneity, High Performance Computing, Self-Organization and the Cloud

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    application; blueprints; self-management; self-organisation; resource management; supply chain; big data; PaaS; Saas; HPCaa

    Heterogeneity, High Performance Computing, Self-Organization and the Cloud

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    application; blueprints; self-management; self-organisation; resource management; supply chain; big data; PaaS; Saas; HPCaa

    Heterogeneity, high performance computing, self-organization and the Cloud

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    This open access book addresses the most recent developments in cloud computing such as HPC in the Cloud, heterogeneous cloud, self-organising and self-management, and discusses the business implications of cloud computing adoption. Establishing the need for a new architecture for cloud computing, it discusses a novel cloud management and delivery architecture based on the principles of self-organisation and self-management. This focus shifts the deployment and optimisation effort from the consumer to the software stack running on the cloud infrastructure. It also outlines validation challenges and introduces a novel generalised extensible simulation framework to illustrate the effectiveness, performance and scalability of self-organising and self-managing delivery models on hyperscale cloud infrastructures. It concludes with a number of potential use cases for self-organising, self-managing clouds and the impact on those businesses

    Automated Realistic Test Input Generation and Cost Reduction in Service-centric System Testing

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    Service-centric System Testing (ScST) is more challenging than testing traditional software due to the complexity of service technologies and the limitations that are imposed by the SOA environment. One of the most important problems in ScST is the problem of realistic test data generation. Realistic test data is often generated manually or using an existing source, thus it is hard to automate and laborious to generate. One of the limitations that makes ScST challenging is the cost associated with invoking services during testing process. This thesis aims to provide solutions to the aforementioned problems, automated realistic input generation and cost reduction in ScST. To address automation in realistic test data generation, the concept of Service-centric Test Data Generation (ScTDG) is presented, in which existing services used as realistic data sources. ScTDG minimises the need for tester input and dependence on existing data sources by automatically generating service compositions that can generate the required test data. In experimental analysis, our approach achieved between 93% and 100% success rates in generating realistic data while state-of-the-art automated test data generation achieved only between 2% and 34%. The thesis addresses cost concerns at test data generation level by enabling data source selection in ScTDG. Source selection in ScTDG has many dimensions such as cost, reliability and availability. This thesis formulates this problem as an optimisation problem and presents a multi-objective characterisation of service selection in ScTDG, aiming to reduce the cost of test data generation. A cost-aware pareto optimal test suite minimisation approach addressing testing cost concerns during test execution is also presented. The approach adapts traditional multi-objective minimisation approaches to ScST domain by formulating ScST concerns, such as invocation cost and test case reliability. In experimental analysis, the approach achieved reductions between 69% and 98.6% in monetary cost of service invocations during testin

    Telekomunikacja i Techniki Informacyjne, 2010, nr 1-2

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    Forest landscapes and global change. New frontiers in management, conservation and restoration. Proceedings of the IUFRO Landscape Ecology Working Group International Conference

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    This volume contains the contributions of numerous participants at the IUFRO Landscape Ecology Working Group International Conference, which took place in Bragança, Portugal, from 21 to 24 of September 2010. The conference was dedicated to the theme Forest Landscapes and Global Change - New Frontiers in Management, Conservation and Restoration. The 128 papers included in this book follow the structure and topics of the conference. Sections 1 to 8 include papers relative to presentations in 18 thematic oral and two poster sessions. Section 9 is devoted to a wide-range of landscape ecology fields covered in the 12 symposia of the conference. The Proceedings of the IUFRO Landscape Ecology Working Group International Conference register the growth of scientific interest in forest landscape patterns and processes, and the recognition of the role of landscape ecology in the advancement of science and management, particularly within the context of emerging physical, social and political drivers of change, which influence forest systems and the services they provide. We believe that these papers, together with the presentations and debate which took place during the IUFRO Landscape Ecology Working Group International Conference – Bragança 2010, will definitively contribute to the advancement of landscape ecology and science in general. For their additional effort and commitment, we thank all the participants in the conference for leaving this record of their work, thoughts and science
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