Dynamic query evaluation plans
SIGMOD '89 Proceedings of the 1989 ACM SIGMOD international conference on Management of data
Optimization of dynamic query evaluation plans
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Optimization techniques for queries with expensive methods
ACM Transactions on Database Systems (TODS)
Optimization of queries with user-defined predicates
ACM Transactions on Database Systems (TODS)
Wireless integrated network sensors
Communications of the ACM
Query optimization in compressed database systems
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ASPLOS IX Proceedings of the ninth international conference on Architectural support for programming languages and operating systems
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Probabilistic Networks and Expert Systems
Filtering with Approximate Predicates
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Design and Analysis of Parametric Query Optimization Algorithms
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Optimization of Nonrecursive Queries
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Optimal depth-first strategies for and-or trees
Eighteenth national conference on Artificial intelligence
The design of an acquisitional query processor for sensor networks
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Adaptive ordering of pipelined stream filters
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Model-driven data acquisition in sensor networks
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
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ICDT'05 Proceedings of the 10th international conference on Database Theory
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DMSN '05 Proceedings of the 2nd international workshop on Data management for sensor networks
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VLDB '05 Proceedings of the 31st international conference on Very large data bases
Content-based routing: different plans for different data
VLDB '05 Proceedings of the 31st international conference on Very large data bases
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Flow algorithms for two pipelined filter ordering problems
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Cost-sensitive learning with conditional Markov networks
ICML '06 Proceedings of the 23rd international conference on Machine learning
InteMon: continuous mining of sensor data in large-scale self-infrastructures
ACM SIGOPS Operating Systems Review
System design issues in sensor databases
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ASAP: An Adaptive Sampling Approach to Data Collection in Sensor Networks
IEEE Transactions on Parallel and Distributed Systems
Intelligent system monitoring on large clusters
DMSN '06 Proceedings of the 3rd workshop on Data management for sensor networks: in conjunction with VLDB 2006
MIST: distributed indexing and querying in sensor networks using statistical models
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Foundations and Trends in Databases
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Cost-sensitive learning with conditional Markov networks
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Techniques for Improving Opportunistic Sensor Networking Performance
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Quality-Aware Probing of Uncertain Data with Resource Constraints
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ACM Transactions on Algorithms (TALG)
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Proceedings of the 2nd ACM international workshop on Foundations of wireless ad hoc and sensor networking and computing
ROX: run-time optimization of XQueries
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Fast likelihood search for hidden Markov models
ACM Transactions on Knowledge Discovery from Data (TKDD)
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Proceedings of the VLDB Endowment
Information storage, reduction and dissemination in sensor networks: a survey
CCNC'09 Proceedings of the 6th IEEE Conference on Consumer Communications and Networking Conference
Bayesian reasoning for sensor group-queries and diagnosis
DASFAA'07 Proceedings of the 12th international conference on Database systems for advanced applications
Sharing-aware horizontal partitioning for exploiting correlations during query processing
Proceedings of the VLDB Endowment
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ACE: exploiting correlation for energy-efficient and continuous context sensing
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Journal of Network and Computer Applications
Parallel pipelined filter ordering with precedence constraints
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Journal of Computer and System Sciences
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Proceeding of the 11th annual international conference on Mobile systems, applications, and services
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Sensor networks and other distributed information systems (such as the Web) must frequently access data that has a high per-attribute acquisition cost, in terms of energy, latency, or computational resources. When executing queries that contain several predicates over such expensive attributes, we observe that it can be beneficial to use correlations to automatically introduce low-cost attributes whose observation will allow the query processor to better estimate the selectivity of these expensive predicates. In particular, we show how to build conditional plans that branch into one or more sub-plans, each with a different ordering for the expensive query predicates, based on the runtime observation of low-cost attributes. We frame the problem of constructing the optimal conditional plan for a given user query and set of candidate low-cost attributes as an optimization problem. We describe an exponential time algorithm for finding such optimal plans, and describe a polynomial-time heuristic for identifying conditional plans that perform well in practice. We also show how to compactly model conditional probability distributions needed to identify correlations and build these plans. We evaluate our algorithms against several real-world sensor-network data sets, showing several-times performance increases for a variety of queries versus traditional optimization techniques.