Artificial Intelligence
An analysis of first-order logics of probability
Artificial Intelligence
A tutorial on hidden Markov models and selected applications in speech recognition
Readings in speech recognition
Probabilistic logic programming
Information and Computation
Probabilistic Horn abduction and Bayesian networks
Artificial Intelligence
Probabilistic deductive databases
ILPS '94 Proceedings of the 1994 International Symposium on Logic programming
From statistical knowledge bases to degrees of belief
Artificial Intelligence
Principles of Database and Knowledge-Base Systems: Volume II: The New Technologies
Principles of Database and Knowledge-Base Systems: Volume II: The New Technologies
Parameter Estimation in Stochastic Logic Programs
Machine Learning
Learning Probabilistic Relational Models
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
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
Learning probabilistic models of link structure
The Journal of Machine Learning Research
TOSSIM: accurate and scalable simulation of entire TinyOS applications
Proceedings of the 1st international conference on Embedded networked sensor systems
Hood: a neighborhood abstraction for sensor networks
Proceedings of the 2nd international conference on Mobile systems, applications, and services
Simulating the power consumption of large-scale sensor network applications
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Region streams: functional macroprogramming for sensor networks
DMSN '04 Proceeedings of the 1st international workshop on Data management for sensor networks: in conjunction with VLDB 2004
Declarative routing: extensible routing with declarative queries
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
Implementing declarative overlays
Proceedings of the twentieth ACM symposium on Operating systems principles
Machine Learning
Kairos: a macro-programming system for wireless sensor networks
Proceedings of the twentieth ACM symposium on Operating systems principles
Approximate Data Collection in Sensor Networks using Probabilistic Models
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
A robust architecture for distributed inference in sensor networks
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Telos: enabling ultra-low power wireless research
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Entirely declarative sensor network systems
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Robust message-passing for statistical inference in sensor networks
Proceedings of the 6th international conference on Information processing in sensor networks
Programming sensor networks using abstract regions
NSDI'04 Proceedings of the 1st conference on Symposium on Networked Systems Design and Implementation - Volume 1
The design and implementation of a declarative sensor network system
Proceedings of the 5th international conference on Embedded networked sensor systems
Suppression and failures in sensor networks: a Bayesian approach
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Learning probabilities for noisy first-order rules
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
PRISM: a language for symbolic-statistical modeling
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
IBAL: a probabilistic rational programming language
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
BLOG: probabilistic models with unknown objects
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Loglinear models for first-order probabilistic reasoning
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
2PDA: two-phase data approximation in wireless sensor network
Proceedings of the 7th ACM workshop on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks
Inference in probabilistic logic programs with continuous random variables
Theory and Practice of Logic Programming
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Synthesizing high-level semantic knowledge from low-level sensor data is an important problem in many sensor network applications. Programming a network to perform such synthesis in situ is especially difficult due to the stringent resource constraints, unreliable wireless communication, and complex distributed algorithms and network protocols required to manipulate the data. Recently, a declarative programming language called Snlog [5] has been developed to address this problem. However, statistical reasoning for modeling noise in the context of sensor networks has not been addressed in Snlog. In this paper, we develop a methodology based on the PRISM [36] framework, which integrates logical and statistical reasoning, for specifying sensor network programs that deal with noisy data and tolerate faults in the network. The relationship between high-level (synthesized) and low-level (observed) data is captured by logical rules, while statistical models are used to specify computations in the presence of noise and faults. We illustrate our methodology with three examples: (i) estimating temperature at various points in a region, (ii) evaluating the trajectory of an object observed by a sensor network, based on the Hidden Markov Model, and (iii) evaluating most reliable communication paths between sensor nodes. We analyze the results of simulations as well as an experimental deployment to evaluate the practical feasibility of our approach.