dQUOB (dynamic QUery OBjects, pronounced d' quob) is a middleware system providing continuous evaluation of queries over time sequenced data. The system provides access to data in data streams by means of SQL queries. The queries are dynamically embedded into the data streams at runtime, and managed remotely during application execution. dQUOB SQL queries have the power to filter and aggregate data, combine streams, and create new streams. Support for embedded user defined functions provides data transformation capabilities.

dQUOB is targeted towards data streaming parallel and distributed computations such as scientific visualization, performance monitoring, and large-scale sensor data. The dQUOB system has been applied to such diverse applications as a safety critical autonomous robotics simulation, and scientific software visualization for global atmospheric transport modeling.

Project Members

Current Research Topics

• RS-Algo Rate Sizing algorithm. Monitors stream rates and adapts join window "sliding windows" on-line to maintain constant time interval. Goal of algorithm is improved overall memory utilization.
• grid-based streaming architecture: some stream systems, such as sensor networks and other continuous data production networks, can be viewed as a distributed data resource. The best way to bring these systems onto the grid is still an open problem. Our approach explained in "Using Global Snapshots to Access Data Streams on the Grid" leverages OGSA-DAI, the grid service access framework developed at the e-Science Institute in Edinburgh.

Publications

• Beth Plale Architecture for Accessing Data Streams on the Grid 2nd EUROPEAN ACROSS GRIDS CONFERENCE (AxGrids 2004), January 2004. Revised version to appear as Using Global Snapshots to Access Data Streams on the Grid in Lecture Notes in Computer Science Series Springer Verlag.
  
  
• Nithya Vijaykumar and Beth Plale Run Time Adaptations for Improved Performance on Asynchronous Data Streams manuscript submitted to conference, February 2004.
  
  
• Beth Plale and Karsten Schwan, Dynamic Querying of Streaming Data with the dQUOB System, IEEE Transactions on Parallel and Distributed Systems, vol. 14, number 3, April 2003, pdf.
  
  
• Beth Plale, George Turner, and Akshay Sharma, Real Time Response to Streaming Data on Linux Clusters, LCI Linux Clusters: the HPC Revolution,, October, 2002 pdf.
  
  
• Beth Plale, Leveraging Run Time Knowledge about Event Rates to Improve Memory Utilization in Wide Area Data Stream Filtering, IEEE High Performance Distributed Computing (HPDC), August 2002, pdf.
• Beth Plale, Patrick Widener, and Karsten Schwan, Taking the Step From Meta-information to Communication Middleware in Computational Data Streams, IEEE Heterogeneous Computing Workshop, April 2001 postscript, pdf.
  
  
• Beth Plale and Karsten Schwan, Optimizations Enabled by a Relational Data Model View to Querying Data Streams, IEEE International Parallel and Distributed Processing Symposium (IPDPS), April 2001 postscript, pdf.
  
  
• Beth Plale and Karsten Schwan, dQUOB: Managing Large Data Flows by Dynamic Embedded Queries, IEEE High Performance Distributed Computing (HPDC), August 2000, postscript, pdf. Extended version available as technical report GIT-TR-00-07 postscript, pdf.
  
  
• Beth Plale and Karsten Schwan, Run-time Detection in Parallel and Distributed Systems: Application to Safety-Critical Systems, 19th IEEE Int'l Distributed Computing Systems (ICDCS), June 1999, compressed postscript, pdf.
  
  
• Beth Plale-Schroeder, Sudhir Aggarwal, and Karsten Schwan, Software Approach to Hazard Detection Using On-line Analysis of Safety Constraints, 16th IEEE Symposium on Reliable Distributed Systems (SRDS), October, 1997, compressed postscript, pdf.
  
  

Last updated April, 2004 by Beth Plale