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A resource provisioning framework for bioinformatics applications in multi-cloud environments

机译:多云环境中生物信息学应用程序的资源供应框架

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摘要

The significant advancement in Next Generation Sequencing (NGS) have enabled the generation of several gigabytes of raw data in a single sequencing run. This amount of raw data introduces new scalability challenges in processing, storing and analyzing it, which cannot be solved using a single workstation, the only resource available for the majority of biological scientists, in a reasonable amount of time. These scalability challenges can be complemented by provisioning computational and storage resources using Cloud Computing in a cost-effective manner. There are multiple cloud providers offering cloud resources as a utility within various business models, service levels and functionalities. However, the lack of standards in cloud computing leads to interoperability issues among the providers rendering the selected one unalterable. Furthermore, even a single provider offers multiple configurations to choose from. Therefore, it is essential to develop a decision making system that facilitates the selection of the suitable cloud provider and configuration together with the capability to switch among multiple providers in an efficient and transparent manner. In this paper, we propose BioCloud as a single point of entry to a multi-cloud environment for non-computer savvy bio-researchers. We discuss the architecture and components of BioCloud and present the scheduling algorithm employed in BioCloud. Experiments with different use-cases and scenarios reveal that BioCloud can decrease the workflow execution time for a given budget while encapsulating the complexity of resource management in multiple cloud providers.
机译:下一代测序(NGS)的重大进步已使一次测序运行能够生成数GB的原始数据。大量原始数据在处理,存储和分析原始数据方面带来了新的可扩展性挑战,而这些问题无法在合理的时间内使用单个工作站来解决,这是大多数生物科学家唯一可用的资源。这些可扩展性挑战可以通过以经济高效的方式使用云计算配置计算和存储资源来弥补。有多种云提供商在各种业务模型,服务级别和功能内将云资源作为实用程序提供。但是,云计算中缺乏标准导致提供商之间的互操作性问题,从而使选定的一站式服务无法更改。此外,即使是单个提供商,也可以提供多种配置供您选择。因此,至关重要的是开发一种决策系统,该决策系统有助于选择合适的云提供商并进行配置,并具有以有效且透明的方式在多个提供商之间进行切换的能力。在本文中,我们建议BioCloud作为非计算机精明的生物研究人员进入多云环境的单一入口点。我们讨论了BioCloud的体系结构和组件,并介绍了BioCloud中采用的调度算法。在不同用例和场景下进行的实验表明,对于给定的预算,BioCloud可以减少工作流程的执行时间,同时将资源管理的复杂性封装在多个云提供商中。

著录项

  • 来源
    《Future generation computer systems》 |2018年第1期|379-391|共13页
  • 作者单位

    Department of Biomedical Informatics, The Ohio State University, Columbus, OH, 43210, United States;

    KINDI Center for Computing Research, Qatar University, Doha, Qatar;

    Department of Biomedical Informatics, The Ohio State University, Columbus, OH, 43210, United States;

    Department of Biomedical Informatics, The Ohio State University, Columbus, OH, 43210, United States,Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul Turkey;

    KINDI Center for Computing Research, Qatar University, Doha, Qatar;

    Department of Biomedical Informatics, The Ohio State University, Columbus, OH, 43210, United States;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Cloud computing; Cloud broker; Interoperability; Multi-cloud; Bioinformatics;

    机译:云计算;云经纪人;互操作性;多云生物信息学;

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