Transcript Ohio State University

Ohio State University
Cyberinfrastructure for Coastal
Forecasting and Change Analysis
Gagan Agrawal
Hakan Ferhatosmanoglu
Xutong Niu
Ron Li
Keith Bedford
1
Ohio State University
Coastal Forecasting and Change
Detection (Lake Erie)
GLOS: Collaboration between
OSU Civil and NOAA
Lake Erie Coastal Erosion Analysis:
OSU Geodetic Science and ODNR
2
Ohio State University
Proposed Infrastructure and
Collaboration
3
Ohio State University
Project Premise and Challenges
• Limitation of Current Environmental Observation
Systems
– Tightly coupled systems
» No reuse of algorithms
» Very hard to experiment with new algorithms
– Closely tied to existing resources
• Our claim
– Emerging trends towards web-services and grid-services can help
• Challenges
– Existing Grid Middleware Systems have not considered streaming
data or data integration issues
– Enabling algorithms (data mining, query planning, data fusion)
need to be implemented as grid/web-services
4
Ohio State University
Middleware Developed at Ohio State
• Automatic Data Virtualization Framework
– Enabling processing and integration of data in lowlevel formats
• GATES (Grid-based AdapTive Execution on
Streams)
– Processing of distributed data streams
• FREERIDE-G (FRamework for Rapid
Implementation of Datamining Engines in
Grid)
– Supporting scalable data analysis on remote data
5
Ohio State University
Application Details: Coastal Erosion
Prediction and Analysis
• Focus: Erosion along Lake
• Erie Shore
– Serious problem
– Substantial Economic Losses
• Prediction requires data from
– Variety of Satellites
– In-situ sensors
– Historical Records
• Challenges
– Analyzing distributed data
– Data Integration/Fusion
 Long Term Goal : Create
Service-oriented
implementation
o Design a WSDL to describe
available data
o Describe available tools and
services
o Support discovery and
composition of datasets and
services for a given query
6
Ohio State University
Application Details: Great Lakes
Now/ForeCasting
• GLOS: Great Lakes
Observing System
– Co-designer/project
manager: K. Bedford, a coPI on this project
– Collaboration with NOAA
• Limitations: Hard-wired
– Cannot incorporate new
streams or algorithms
• Create a Demand-driven
Implementation using
GATES
• Event of Interest
– A boat accident, oil leakage
• Need to run a new model
– Time Constraints
– Find grid resources on the
fly
• Need to decide:
– Spatial and Temporal
Granularity
– Parameters to Model
7