Survey White Paper Outline

Part 1. Introduction of Cloud Computing Technology

Part 2. Science Stories and Requirements for the Cloud

There are a lot of practices of implementing scientific applications on cloud computing resources such as biology/bioinformatics (Stein 2010, Schatz et al. 2010), Geospatial Information System (Yang et al. 2011), Astronomy, and Environmental Science.

Due to different requirements in each science area, the focuses of cloud computing applications are various. In Biology/Bioinformatics area, many applications such as DNA sequencing require processing of large data throughput (Schatz et al. 2010 and Langmead et al. 2009). The cloud computing workflow in Geospatial sciences mainly involves data storage and processing (Cui et al. 2010, Huang et al. 2010, Park et al. 2011, Yang et al. 2010, Bunzel et al. 2010) and simulation and modeling. Also, a main IT challenge in Geospatial sciences is to deal with massive concurrent users access (Huang et al. 2010, Bernstein et al. 2010, Wang et al. 2010, Janakiraman et al. 2010, Blower et al. 2010). The practice of cloud computing in Astronomy is focused on data processing such as processing images from telescope (Berriman et al. 2010, Jackson et al. 2010, Berriman et al. 2010(2), Hoffa et al. 2008) or data sharing (Juve et al. 2010). In Environmental sciences, the practice of implementing cloud computing is focused on modeling such as ocean climate modeling (Evangelinos et al. 2008) and groundwater modeling (Hunt et al. 2010), cloud computing is also used in data analysis such as parallel sequential data analysis tasks (Hasenkamp et al. 2010).

Part 3. Cloud Computing Platforms and Tools

Part 4. Gap Analysis and Known Issues

Part 5. Recommendations

What should NCSA do next step? Should we invest some time on setting up some private cloud? some Cloud tools?