Query Processing in Sensor Networks

By Yong Yao, Johannes Gehrke. 2003

1,025 citations recorded by the source corpus.

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Citations in the corpus

Over-the-air Function Computation in Sensor Networks (2016, background): “(a) Aggregated Wireless Sensor Networks : Most data aggregation work can be classiﬁed as: tree-based [17, 26, 16, 13], cluster-based [12, 27, 30, 18] or multipath [20, 19, 7].”
Synopsis diffusion for robust aggregation in sensor networks (2004, methodology): “A popular approach used by sensor database systems [20, 27] is to construct a spanning tree in the network, rooted at the querying node, and then perform innetwork aggregation along the tree.”
Gossip-based computation of aggregate information (2003, background): “our physical environment with sensor networks consisting of hundreds of thousands of small sensor nodes [24, 28, 35].”
Distributed regression: an efficient framework for modeling sensor network data (2004, background): “Adaptive Sampling. Rather than delivering samples at a continuous rate, as most sensor-network query systems propose (Mad03; YG03 ), our approach allows nodes to locally suppress messages that are very near to the value predicted by the regression model.”
Approximate aggregation techniques for sensor databases (2004, methodology): “However, similar approaches are used to compute aggregates in other systems [20, 21, 23, 13].”
Tributaries and deltas: efficient and robust aggregation in sensor network streams (2005, methodology): “Through extensive simulation with real-world and synthetic data, we show the signi.cant advantages of our techniques.”
Infrastructure for Data Processing in Large-Scale Interconnected Sensor Networks (2007, background): “Similarly, in Cougar [13] (http://www.cs.cornell.edu/database/cougar/) an extended version of SQL is used, modeling temporal characteristics in the language itself.”
Clock synchronization for wireless sensor networks: a survey (2005, background): “In wireless sensor networks, the basic operation is data fusion , whereby data from each sensor is agglomerated to form a single meaningful result [17,44,71,74,76–78].”
An Energy-Efficient Data Collection Framework for Wireless Sensor Networks by Exploiting Spatiotemporal Correlation (2007, methodology): “To exploit the spatial correlation, we partition the sensor nodes with similar observations into a cluster.”
Exploiting Virtual Coordinates for Improved Routing Performance in Sensor Networks (2011, methodology): “Combined with database technology such as data stream query processing, further optimization can be achieved [15].”
Issues in data stream management (2003, background): “characteristics (when transmitting and receiving) are known [51, 70].”
Online outlier detection in sensor data using non-parametric models (2006, background): “Yao and Gehrke [45] investigate the problem of query processing in sensor networks.”
Model-based approximate querying in sensor networks (2005, methodology): “We note that this approach to routing is substantially different than approaches used in other sensor network databases (e.g., Cougar [56] and TinyDB [40]) that use (scoped) flooding approaches to disseminate queries throughout a network.”
Model-Driven Data Acquisition in Sensor Networks (2004, background): “However , the leading approaches to query processing in sensornets [30] [21] follow a completist's approach, acquiring as much data as possible from the environment at a given point in time, even when most of that data provides little benefit in approximate answer quality.”