1. Elke A. Rundensteiner Database Systems Research Group Email: rundenst@cs.wpi.edurundenst@cs.wpi.edu Office: Fuller 238 Phone: Ext. – 5815 WebPages: http://www.cs.wpi.edu/~rundenst http://davis.wpi.edu/dsrg

2. CAPE : Engine for Querying and Monitoring Streaming Data Example of Stream Data Applications: Market Analysis –Streams of Stock Exchange Data - get rich Critical Care –Streams of Vital Sign Measurements – save lives Physical Plant Monitoring –Streams of Environmental Readings – protect env data Query data streams of data static data Standing queries one-time queries

3. Stream Query Monitoring Projects  CAPE Query Engine Load Spiller Service (JAVA):  Service for run-time spill/unspill services for a complete query plan  Design query policies, operator data structures, algorithms  Implement in CAPE engine, conduct experiments  Event Pattern Monitoring Engine  Support Sequence Queries and Extend to more Complex AND/OR Patterns  Handle out-of-order event input arrivals by either logging and result-correction or by exploiting predicting meta-data messages  Scale to support multiple event queries  RFID Data Service  Install actual RFID equipment in some campus environment  Support simple data collection and tracking queries, of either goods or people  Handling missing values or clean-up errors using domain knowledge  Visual Stream Monitoring Tool  Target a real stream application, such as flow simulation tool  Develop algorithms for multi-resolution data aggregation in time and space  Support visual query refinement of asking about a particular object or region  CAPE Query Engine Load Spiller Service (JAVA):  Service for run-time spill/unspill services for a complete query plan  Design query policies, operator data structures, algorithms  Implement in CAPE engine, conduct experiments  Event Pattern Monitoring Engine  Support Sequence Queries and Extend to more Complex AND/OR Patterns  Handle out-of-order event input arrivals by either logging and result-correction or by exploiting predicting meta-data messages  Scale to support multiple event queries  RFID Data Service  Install actual RFID equipment in some campus environment  Support simple data collection and tracking queries, of either goods or people  Handling missing values or clean-up errors using domain knowledge  Visual Stream Monitoring Tool  Target a real stream application, such as flow simulation tool  Develop algorithms for multi-resolution data aggregation in time and space  Support visual query refinement of asking about a particular object or region

4.  Acquisition: Brand New Purchase of 20-Node High-Performance PC Cluster (Rundensteiner/Mani/Heineman – NSF )  Project 1: Implement and evaluate allocation/re- allocation algorithms for assigning stream query nodes to processor  Project 2: Implement and compare two solutions for migrating at run-time query plans into new rewritten plans  Project 3: Develop launch-pad for statistics monitoring for monitoring DCAPE experiments  Acquisition: Brand New Purchase of 20-Node High-Performance PC Cluster (Rundensteiner/Mani/Heineman – NSF )  Project 1: Implement and evaluate allocation/re- allocation algorithms for assigning stream query nodes to processor  Project 2: Implement and compare two solutions for migrating at run-time query plans into new rewritten plans  Project 3: Develop launch-pad for statistics monitoring for monitoring DCAPE experiments PC-Cluster Java Applications