The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.
This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.
You can access and play with the graphs:
- Evolution of the number of publications between 2005 and 2015
- Map of most publishing countries between 2005 and 2015
- Network of country collaborations
- Network of institutional collaborations (+10 publications)
- Network of keywords relating to data - Link
FastStor: improving the performance of a large scale hybrid storage system via caching and prefetching
Storing enormous amount of data on hybrid storage systems has become a widely accepted solution for today's production level applications in order to trade off the performance and cost. However, how to improve the performance of large scale storage systems with hybrid components (e.g. solid state disks, hard drives and tapes) and complicated user behaviors is not fully explored. In this paper, we conduct an in-depth case study (we call it FastStor) on designing a high performance hybrid storage system to support one of the world's largest satellite images distribution systems operated by the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) center. We demonstrate how to combine conventional caching policies with innovative current popularity oriented and user-specific prefetching algorithms to improve the performance of the EROS system. We evaluate the effectiveness of our proposed solution using over 5 million real world user download requests provided by EROS. Our experimental results show that using the Least Recently Used (LRU) caching policy alone, we are able to achieve an overall 64 % or 70 % hit ratio on a 100 TB or 200 TB FTP server farm composed of Solid State Disks (SSDs) respectively. The hit ratio can be further improved to 70 % (for 100 TB SSDs) and 76 % (for 200 TB SSDs) if intelligent prefetching algorithms are used together with LRU.
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