Wavelet-based histograms for selectivity estimation
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Multi-resolution indexing for shape images
Proceedings of the seventh international conference on Information and knowledge management
Distributed Processing of Similarity Queries
Distributed and Parallel Databases
Evaluating continuous nearest neighbor queries for streaming time series via pre-fetching
Proceedings of the eleventh international conference on Information and knowledge management
One-Pass Wavelet Decompositions of Data Streams
IEEE Transactions on Knowledge and Data Engineering
Haar Wavelets for Efficient Similarity Search of Time-Series: With and Without Time Warping
IEEE Transactions on Knowledge and Data Engineering
A Compact Wavelet Index for Retrieval in Image Database
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Adaptive filters for continuous queries over distributed data streams
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Efficient elastic burst detection in data streams
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
The Cauchy-Schwarz Master Class: An Introduction to the Art of Mathematical Inequalities
The Cauchy-Schwarz Master Class: An Introduction to the Art of Mathematical Inequalities
The VLDB Journal — The International Journal on Very Large Data Bases
Finding (Recently) Frequent Items in Distributed Data Streams
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Distributed Data Streams Indexing using Content-Based Routing Paradigm
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
Holistic aggregates in a networked world: distributed tracking of approximate quantiles
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Tributaries and deltas: efficient and robust aggregation in sensor network streams
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Wavelet synopsis for data streams: minimizing non-euclidean error
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
One-pass wavelet synopses for maximum-error metrics
VLDB '05 Proceedings of the 31st international conference on Very large data bases
A geometric approach to monitoring threshold functions over distributed data streams
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Efficient range-constrained similarity search on wavelet synopses over multiple streams
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
StatStream: statistical monitoring of thousands of data streams in real time
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Approximate NN queries on streams with guaranteed error/performance bounds
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Fast approximate wavelet tracking on streams
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
PROUD: a probabilistic approach to processing similarity queries over uncertain data streams
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Scalable kNN search on vertically stored time series
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
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We present LeeWave --- a bandwidth-efficient approach to searching range-specified k-nearest neighbors among distributed streams by LEvEl-wise distribution of WAVElet coefficients. To find the k most similar streams to a range-specified reference one, the relevant wavelet coefficients of the reference stream can be sent to the peer sites to compute the similarities. However, bandwidth can be unnecessarily wasted if the entire relevant coefficients are sent simultaneously. Instead, we present a level-wise approach by leveraging the multi-resolution property of the wavelet coefficients. Starting from the top and moving down one level at a time, the query initiator sends only the single-level coefficients to a progressively shrinking set of candidates. However, there is one difficult challenge in LeeWave: how does the query initiator prune the candidates without knowing all the relevant coefficients? To overcome this challenge, we derive and maintain a similarity range for each candidate and gradually tighten the bounds of this range as we move from one level to the next. The increasingly tightened similarity ranges enable the query initiator to effectively prune the candidates without causing any false dismissal. Extensive experiments with real and synthetic data show that, when compared with prior approaches, LeeWave uses significantly less bandwidth under a wide range of conditions.