Video query processing in the VDBMS testbed for video database research
MMDB '03 Proceedings of the 1st ACM international workshop on Multimedia databases
Nile: A Query Processing Engine for Data Streams
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Adaptive ordering of pipelined stream filters
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Exploiting k-constraints to reduce memory overhead in continuous queries over data streams
ACM Transactions on Database Systems (TODS)
A framework for spatio-temporal query processing over wireless sensor networks
DMSN '04 Proceeedings of the 1st international workshop on Data management for sensor networks: in conjunction with VLDB 2004
Nile-PDT: a phenomenon detection and tracking framework for data stream management systems
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Adaptive load shedding for windowed stream joins
Proceedings of the 14th ACM international conference on Information and knowledge management
Exploiting predicate-window semantics over data streams
ACM SIGMOD Record
In-network execution of monitoring queries in sensor networks
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
GrubJoin: An Adaptive, Multi-Way, Windowed Stream Join with Time Correlation-Aware CPU Load Shedding
IEEE Transactions on Knowledge and Data Engineering
Scheduling for shared window joins over data streams
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Executing stream joins on the cell processor
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
A substrate for in-network sensor data integration
Proceedings of the 5th workshop on Data management for sensor networks
Multiple continuous queries evaluation over data streams
ACS'08 Proceedings of the 8th conference on Applied computer scince
A query processor for prediction-based monitoring of data streams
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
CellJoin: a parallel stream join operator for the cell processor
The VLDB Journal — The International Journal on Very Large Data Bases
Information discovery across multiple streams
Information Sciences: an International Journal
Transformation of continuous aggregation join queries over data streams
SSTD'07 Proceedings of the 10th international conference on Advances in spatial and temporal databases
Continuous constraint query evaluation for spatiotemporal streams
SSTD'07 Proceedings of the 10th international conference on Advances in spatial and temporal databases
MG-join: detecting phenomena and their correlation in high dimensional data streams
Distributed and Parallel Databases
Load shedding for multi-way stream joins based on arrival order patterns
Journal of Intelligent Information Systems
Adaptive optimization for multiple continuous queries
Data & Knowledge Engineering
Semantics of data streams and operators
ICDT'05 Proceedings of the 10th international conference on Database Theory
Querying sliding windows over online data streams
EDBT'04 Proceedings of the 2004 international conference on Current Trends in Database Technology
Phenomenon-aware sensor database systems
EDBT'06 Proceedings of the 2006 international conference on Current Trends in Database Technology
Driver input selection for main-memory multi-way joins
Proceedings of the 28th Annual ACM Symposium on Applied Computing
On clustering large number of data streams
Intelligent Data Analysis
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The widespread use of sensor networks presents revolutionary opportunities for life and environmental science applications. Many of these applications involve continuous queries that require the tracking, monitoring, and correlation of multi-sensor data that represent moving objects. We propose to answer these queries using a multi-way stream window join operator. This form of join over multi-sensor data must cope with the infinite nature of sensor data streams and the delays in network transmission. This paper introduces a class of join algorithms, termed W-join, for joining multiple infinite data streams. W-join addresses the infinite nature of the data streams by joining stream data items that lie within a sliding window and that match a certain join condition. W-join can be used to track the motion of a moving object or detect the propagation of clouds of hazardous material or pollution spills over time in a sensor network environment. We describe two new algorithms for W-join, and address variations and local/global optimizations related to specifying the nature of the window constraints to fulfill the posed queries. The performance of the proposed algorithms are studied experimentally in a prototype stream database system, using synthetic data streams and real time-series data. Tradeoffs of the proposed algorithms and their advantages and disadvantages are high-lighted, given variations in the aggregate arrival rates of the input data streams and the desired response times per query.