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Aimee Stewart

Publications and source records attributed to Aimee Stewart.

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Virtualizing Lifemapper Software Infrastructure for Biodiversity Expedition

One of the activities of the Pacific Rim Applications and Grid Middleware Assembly (PRAGMA) is fostering Virtual Biodiversity Expeditions (VBEs) by bringing domain scientists and cyber infrastructure specialists together as a team. Over the past few years PRAGMA members have been collaborating on virtualizing the Lifemapper software. Virtualization and cloud computing have introduced great flexibility and efficiency into IT projects. Virtualization provides application scalability, maximizes resources utilization, and creates a more efficient, agile, and automated infrastructure. However, there are downsides to the complexity inherent in these environments, including the need for special techniques to deploy cluster hosts, dependence on virtual environments, and challenging application installation, management, and configuration. In this paper, we report on progress of the Lifemapper virtualization framework focused on a reproducible and highly configurable infrastructure capable of fast deployment. A key contribution of this work is describing the practical experience in taking a complex, clustered, domain-specific, data analysis and simulation system and making it available to operate on a variety of system configurations. Uses of this portability range from whole cluster replication to teaching and experimentation on a single laptop. System virtualization is used to practically define and make portable the full application stack, including all of its complex set of supporting software.

cs.SE

The use of the GARP genetic algorithm and internet grid computing in the Lifemapper world atlas of species biodiversity

Lifemapper (http://www.lifemapper.org) is a predictive electronic atlas of the Earth's biological biodiversity. Using a screensaver version of the GARP genetic algorithm for modeling species distributions, Lifemapper harnesses vast computing resources through 'volunteers' PCs similar to SETI@home, to develop models of the distribution of the worlds fauna and flora. The Lifemapper project's primary goal is to provide an up to date and comprehensive database of species maps and prediction models (i.e. a fauna and flora of the world) using available data on species' locations. The models are developed using specimen data from distributed museum collections and an archive of geospatial environmental correlates. A central server maintains a dynamic archive of species maps and models for research, outreach to the general community, and feedback to museum data providers. This paper is a case study in the role, use and justification of a genetic algorithm in development of large-scale environmental informatics infrastructure.

q-bio.QM