ARES: a relational database with the capability of performing flexible interpretation of queries
IEEE Transactions on Software Engineering
VAGUE: a user interface to relational databases that permits vague queries
ACM Transactions on Information Systems (TOIS)
System architecture directions for networked sensors
ASPLOS IX Proceedings of the ninth international conference on Architectural support for programming languages and operating systems
The cougar approach to in-network query processing in sensor networks
ACM SIGMOD Record
A Server for Fuzzy SQL Queries
FQAS '98 Proceedings of the Third International Conference on Flexible Query Answering Systems
The nesC language: A holistic approach to networked embedded systems
PLDI '03 Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation
The design of an acquisitional query processor for sensor networks
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
TOSSIM: accurate and scalable simulation of entire TinyOS applications
Proceedings of the 1st international conference on Embedded networked sensor systems
TinyDB: an acquisitional query processing system for sensor networks
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
A New Approach for Information Processing inWireless Sensor Network
ICDEW '06 Proceedings of the 22nd International Conference on Data Engineering Workshops
dmFSQL: a Language for Data Mining
DEXA '06 Proceedings of the 17th International Conference on Database and Expert Systems Applications
Fuzzy Databases: Modeling, Design, and Implementation
Fuzzy Databases: Modeling, Design, and Implementation
A virtual machine for sensor networks
Proceedings of the 2nd ACM SIGOPS/EuroSys European Conference on Computer Systems 2007
Simulation environment scenarios using cellular automata for wireless sensor network analysis
SpringSim '09 Proceedings of the 2009 Spring Simulation Multiconference
SQLf: a relational database language for fuzzy querying
IEEE Transactions on Fuzzy Systems
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In this paper, we describe a fuzzy query processing approach to support application development in sensor networks. Using a fuzzy query, an application programmer can provide a linguistic and semantic specification of the desired data, eliminating the need to specify explicit and exact thresholds as part of a query. The returned fuzzy query results are each associated with a degree of membership measurement that indicates how closely each returned data value matches the semantic intent of the fuzzy query, providing applications with additional information that can be used to reason about the query result. Our approach to in-network fuzzy query processing allows for each sensor node to tailor its evaluation of a fuzzy query; this feature allows for consideration of micro-environments embedded within the sensor network that can impact how individual sensor data values should be interpreted with respect to the semantic intent of the query. To demonstrate that a fuzzy query processing approach is feasible, we use an application scenario to evaluate the implementation of our fuzzy query processing system in a simulated sensor network environment; results show that precision and overhead for our approach are comparable to traditional query processing.