eScience的协作市场:一个医学成像用例

Mengsong Zou, J. Montes, I. Rodero, M. Parashar, I. Petri, O. Rana, X. Qi, D. Foran
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引用次数: 1

摘要

数字成像技术的发展正在创造非凡的精度水平,为提高图像分析不同方面的可靠性提供支持,如基于内容的图像检索、图像分割和分类。这极大地增加了数据量和生成速度,使得查询和共享变得非常重要,并使集中式解决方案变得不可行的。此外,在许多情况下,这些数据是自然分布的,或者必须在需要分散解决方案的多个机构之间共享。在本文中,我们提出了一种联邦方法,该方法可以利用先进的网络基础设施(ACI),与位于地理分布资源中的信息/数据进行无缝和安全的交互。我们描述并评估了在医学成像合作研究的背景下,跨越英国和美国资源的联合市场的建立。我们将展示来自不同站点的用户如何通过在市场中放置计算请求来透明地访问远程数据。此外,我们评估了不同的定价政策,以展示网站提供商和用户如何从这种联合中受益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Collaborative marketplaces for eScience: A medical imaging use case
The development of digital imaging technology is creating extraordinary levels of accuracy that provide support for improved reliability in different aspects of the image analysis such as content-based image retrieval, image segmentation and classification. This has dramatically increased the volume and generation rates of data, which make querying and sharing non-trivial, and render centralized solutions infeasible. Moreover, in many cases this data is naturally distributed or has to be shared across multiple institutions requiring decentralized solutions. In this paper, we present a federation approach that can take advantage of advanced cyber-infrastructure (ACI) by seamlessly and securely interacting with information/data located across geographically distributed resources. We describe and evaluate the establishment of a federated marketplace across resources from UK and US in the context of collaborative research in medical imaging. We show how users from different sites can transparently access to remote data by placing computational requests in the marketplace. Moreover, we evaluate different pricing policies to demonstrate how site providers and users can benefit from such federation.
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