Directed diffusion: a scalable and robust communication paradigm for sensor networks
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Adaptive precision setting for cached approximate values
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
On the interdependence of routing and data compression in multi-hop sensor networks
Proceedings of the 8th annual international conference on Mobile computing and networking
Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Efficient Stepwise Selection in Decomposable Models
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
Energy-Efficient Communication Protocol for Wireless Microsensor Networks
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 8 - Volume 8
The impact of spatial correlation on routing with compression in wireless sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Snapshot Queries: Towards Data-Centric Sensor Networks
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
TAG: a Tiny AGgregation service for Ad-Hoc sensor networks
OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
Efficient gathering of correlated data in sensor networks
Proceedings of the 6th ACM international symposium on Mobile ad hoc networking and computing
Holistic aggregates in a networked world: distributed tracking of approximate quantiles
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Approximate Data Collection in Sensor Networks using Probabilistic Models
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Network correlated data gathering with explicit communication: NP-completeness and algorithms
IEEE/ACM Transactions on Networking (TON)
Constraint chaining: on energy-efficient continuous monitoring in sensor networks
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
ACM Transactions on Sensor Networks (TOSN)
Model-driven data acquisition in sensor networks
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Graphical Models in Applied Multivariate Statistics
Graphical Models in Applied Multivariate Statistics
The capacity of wireless networks
IEEE Transactions on Information Theory
Distributed source coding using syndromes (DISCUS): design and construction
IEEE Transactions on Information Theory
On computing compression trees for data collection in wireless sensor networks
INFOCOM'10 Proceedings of the 29th conference on Information communications
Efficient measurement generation and pervasive sparsity for compressive data gathering
IEEE Transactions on Wireless Communications
Processing continuous top-k data collection queries in lifetime-constrained wireless sensor networks
Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication
An adaptive and composite spatio-temporal data compression approach for wireless sensor networks
Proceedings of the 14th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems
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We address the problem of designing practical, energy-efficient protocols for data collection in wireless sensor networks using predictive modeling. Prior work has suggested several approaches to capture and exploit the rich spatio-temporal correlations prevalent in WSNs during data collection. Although shown to be effective in reducing the data collection cost, those approaches use simplistic corelation models and further, ignore many idiosyncrasies of WSNs, in particular the broadcast nature of communication. Our proposed approach is based on approximating the joint probability distribution over the sensors using undirected graphical models, ideally suited to exploit both the spatial correlations and the broadcast nature of communication. We present algorithms for optimally using such a model for data collection under different communication models, and for identifying an appropriate model to use for a given sensor network. Experiments over synthetic and real-world datasets show that our approach significantly reduces the data collection cost.