# Presentation: 319648

## Experiences with OGSA-DAI : Portlet Access and Benchmark

- Deepti Kodeboyina and Beth Plale
- Computer Science Dept.
- Indiana University

## Portals for Grids

**Portals** as user-oriented interfaces to the grid. They are used for providing user access to grid services
- Potential for **data access**, integration, collaborative data analysis of large datasets. Data access to either commercial or scientific data would add value to the day-to-day operations of grid users.
**OGSA-DAI** – collaboration of grid services for providing access to heterogeneous data sources (exactly what we need)
- Our **goal** – creation of a portlet to provide an interface for data management of disparate and heterogeneous data sources using OGSA- DAI and to understand the overheads associated with that.

## Portal infrastructure				

- The portlet is currently deployed onto the Alliance portal that is hosted on a Linux server.

## Portlet interaction

## Portlet interaction return results

- Provided Factory Service Handle

- GDS Create service document
- assigned

- Perform document chosen

- Response as XML and html

- Perform document sent to the
- GDS. GDS replies with response
-  document.

## Portlet interaction: asynchronous requests through gFTP

## On-going work

**Transfer of data** by means of other mechanisms (grid ftp) for providing secure access.
**Transparency** of the perform document location to be added.
-  By way of using WebDAV in order to remove existing usage restrictions.
**Dynamic creation** of perform documents via the portlet itself.
- Plan is to allow user to enter/choose required information in a web form and dynamically generate the XML documents from that.

## IU RGRbench

- IU RGR Benchmark – benchmark/workload for grid information servers.
- realistic grid information server specific questions
- Synthetic workloads to test query response time under multi-client workload
- Applied benchmark to analyze performance of OGSA-DAI.
- quantify overhead of grid service interface to database.
- Benchmark queries
- 13 queries, iterate, sequential access to database.
- Data size of result set varies from few bytes to 45 KB
- Benchmark scenarios
- synthetic workloads evaluate sensitivity of query response time to update load.
- Query workloads run for 20 minutes; concurrent updates begun at minute 6, run through minute 11.
- Response times averaged over interval.

## Experiment details

- Platform Specifications
- Globus toolkit 3.0 version and OGSA_DAI v3.0 deployed on linux server
- Database accessed: mySQL
- situated on a separate dual processor Xeon server
- All these machines are part of the Local Area Network of the CS department.
- Experiment summarization
- Average query response times vary from 100 ms to 600 ms for synchronous requests.
- Query response times vary with the size of the data sets also.
- Scenarios have varying response times extremely sensitive to the no. of updates.

## Ogsa-Dai v3.0 Query Results

- Note that scale is 10^4

- Synchronous response mechanism

- Asynchronous response mechanism

**Notes:**
Graphs estimate of the response times obtained for different queries. 
Note the queries in the second graph have a much higher response time. Why ? 
What about indexed and non-indexed queries ?

## Ogsa-Dai v3.0 Scenario Results

- Multiple Attribute Updates

- Insertion of records

## Future work 

**On-the-fly creation** of Grid Data Services in response to multiple users is being explored.
- Also, when the users require data from resources which can not be created by existing factories, new ones to access these will have to be created.
- More **profiling** being done to determine and understand the latencies caused at a finer granularity.
- Aiming at a much more broader usage of the portlet