Supporting aggregate queries over ad-hoc wireless sensor networks

By Samuel Madden, Robert Szewczyk, M. Franklin, David E. Culler. Proceedings Fourth IEEE Workshop on Mobile Computing Systems and Applications, 2002

546 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Signal Processing

View Paper: https://www.semanticscholar.org/paper/274361bbe658e91839256ffaf3351b59b8df7577

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In Signal Processing

Citations in the corpus

The platforms enabling wireless sensor networks (2004, background): “Each provides the option of using high-level interpreters [2, 6, 7] to simplify application development.”
LEAP+: Efficient security mechanisms for large-scale distributed sensor networks (2006, background): “Passive participation is another form of in-network processing in which a sensor node can take certain actions based on overheard messages [Karlof et al. 2003; Madden et al. 2002], for example, a sensor can decide to not report an event if it overhears a neighboring node reporting the same event.”
Synopsis diffusion for robust aggregation in sensor networks (2004, background): “Computing aggregates in sensor networks has been studied in a number of recent papers [19, 20, 21, 29].”
The impact of spatial correlation on routing with compression in wireless sensor networks (2008, methodology): “…[Intanagonwiwat et al. 2002, 2003]; explored the use of data aggregation operators to optimize the performance of sensor database-type queries [Madden et al. 2002]; and the possibility of adapting the aggregation routing structures to data content and availability in the network [Bon.ls…”
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].”
Real-time forest fire detection with wireless sensor networks (2005, methodology): “When a cluster header receives a QR packet, the header can apply the aggregation algorithms (e.g. [11]) to process the QR packet.”
Tributaries and deltas: efficient and robust aggregation in sensor network streams (2005, background): “There has been a flurry of recent papers on energy-efficient, in-network computation of aggregate queries in sensor networks [5, 6, 8, 11, 12, 13, 17, 19, 21, 24, 25].”
Gossip-based aggregation in large dynamic networks (2005, background): “For instance, [17] represents a reactive approach where queries are propagated through the system and the answer propagates back to the source node (see the distinction between reactive and proactive approaches in the Introduction).”
Energy-efficient computing for wildlife tracking: design tradeoffs and early experiences with ZebraNet (2002, background): “Finally, there has also been work on high level da t a processing and programming in sensor network to reduce bandwidth or storage needs [3, 14, 20].”
Efficient algorithms for maximum lifetime data gathering and aggregation in wireless sensor networks (2003, background): “The focus of the work in [17] is on a class of aggregation predicates that is particularly well suited to the in-network regime.”
An efficient clustering-based heuristic for data gathering and aggregation in sensor networks (2003, background): “Madden et al [13] describe the TinyOS operating system that can be used by an ad-hoc network of sensors to locate each other and route data.”
TinySec: a link layer security architecture for wireless sensor networks (2004, unknown): “To prune these redundant messages to reduce traffic and save energy, sensor networks use innetwork processing such as aggregation and duplicate elimination [29, 30].”
Prediction-based strategies for energy saving in object tracking sensor networks (2004, background): “Query processing and data aggregation also provides many energy optimization opportunities that were extensively explored in literatures [12, 13, 20].”