ACM Transactions on Database Systems (TODS)
Implementing data cubes efficiently
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Materialized view maintenance and integrity constraint checking: trading space for time
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
NiagaraCQ: a scalable continuous query system for Internet databases
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Filtering algorithms and implementation for very fast publish/subscribe systems
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Models and issues in data stream systems
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Continuously adaptive continuous queries over streams
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Gigascope: a stream database for network applications
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Tribeca: a system for managing large databases of network traffic
ATEC '98 Proceedings of the annual conference on USENIX Annual Technical Conference
Streaming queries over streaming data
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Monitoring streams: a new class of data management applications
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Data stream query processing: a tutorial
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Resource sharing in continuous sliding-window aggregates
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
On-the-fly sharing for streamed aggregation
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
State-slice: new paradigm of multi-query optimization of window-based stream queries
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Sharing aggregate computation for distributed queries
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Synopsis diffusion for robust aggregation in sensor networks
ACM Transactions on Sensor Networks (TOSN)
Prefilter: predicate pushdown at streaming speeds
SSPS '08 Proceedings of the 2nd international workshop on Scalable stream processing system
Index tuning for parameterized streaming groupby queries
SSPS '08 Proceedings of the 2nd international workshop on Scalable stream processing system
Rule-based multi-query optimization
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Small synopses for group-by query verification on outsourced data streams
ACM Transactions on Database Systems (TODS)
Information discovery across multiple streams
Information Sciences: an International Journal
An Approximation Algorithm for Optimizing Multiple Path Tracking Queries over Sensor Data Streams
DEXA '09 Proceedings of the 20th International Conference on Database and Expert Systems Applications
Scalable delivery of stream query result
Proceedings of the VLDB Endowment
High-dimensional kNN joins with incremental updates
Geoinformatica
What can hierarchies do for data streams?
BIRTE'06 Proceedings of the 1st international conference on Business intelligence for the real-time enterprises
Journal of Intelligent Information Systems
Mining time-delayed associations from discrete event datasets
DASFAA'07 Proceedings of the 12th international conference on Database systems for advanced applications
Transformation of continuous aggregation join queries over data streams
SSTD'07 Proceedings of the 10th international conference on Advances in spatial and temporal databases
Streaming multiple aggregations using phantoms
The VLDB Journal — The International Journal on Very Large Data Bases
Optimized processing of multiple aggregate continuous queries
Proceedings of the 20th ACM international conference on Information and knowledge management
Shared execution strategy for neighbor-based pattern mining requests over streaming windows
ACM Transactions on Database Systems (TODS)
Supporting efficient distributed top-k monitoring
WAIM '06 Proceedings of the 7th international conference on Advances in Web-Age Information Management
Loyalty-based selection: retrieving objects that persistently satisfy criteria
Proceedings of the 21st ACM international conference on Information and knowledge management
Multi-query optimization for semantic news feed query
Proceedings of the International Conference on Management of Emergent Digital EcoSystems
A thin monitoring layer for top-k aggregation queries over a database
Proceedings of the 7th International Workshop on Ranking in Databases
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Monitoring aggregates on IP traffic data streams is a compelling application for data stream management systems. The need for exploratory IP traffic data analysis naturally leads to posing related aggregation queries on data streams, that differ only in the choice of grouping attributes. In this paper, we address this problem of efficiently computing multiple aggregations over high speed data streams, based on a two-level LFTA/HFTA DSMS architecture, inspired by Gigascope.Our first contribution is the insight that in such a scenario, additionally computing and maintaining fine-granularity aggregation queries (phantoms) at the LFTA has the benefit of supporting shared computation. Our second contribution is an investigation into the problem of identifying beneficial LFTA configurations of phantoms and user-queries. We formulate this problem as a cost optimization problem, which consists of two sub-optimization problems: how to choose phantoms and how to allocate space for them in the LFTA. We formally show the hardness of determining the optimal configuration, and propose cost greedy heuristics for these independent sub-problems based on detailed analyses. Our final contribution is a thorough experimental study, based on real IP traffic data, as well as synthetic data, to demonstrate the effectiveness of our techniques for identifying beneficial configurations.