The design of an acquisitional query processor for sensor networks

By Samuel Madden, M. Franklin, Joseph M Hellerstein, W. Hong. ACM SIGMOD Conference, 2003

1,089 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Signal Processing

View Paper: https://www.semanticscholar.org/paper/7dab84b8d7440bc1f22b0a24fa804290acbd9b61

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

In Signal Processing

Citations in the corpus

IrisNet: An Architecture for a Worldwide Sensor Web (2003, background): “7 None of this work considers sensor networks with intelligent sensor nodes, high-bit-rate sensor feeds, and global scale.”
Approximate Data Collection in Sensor Networks using Probabilistic Models (2006, methodology): “Even though the Sonoma Redwoods deployment was based on TinyDB [20], a sensor network query processor capable of in-network aggregation and filtering, the biologists were only willing to issue the " SELECT * FREQ f " query, where the modifier FREQ f indicates the query should repeat at the given fre”
MQTT-S — A publish/subscribe protocol for Wireless Sensor Networks (2008, methodology): “Our implementation of MQTT-S is presented in Section V. Open challenges and future work are presented in Section VI, and the conclusions are given in Section VII.”
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].”
Macro-programming Wireless Sensor Networks Using Kairos (2005, background): “Thus, the work on SQL-like expressive but Turingincomplete query systems (e.g., TinyDB [10] [9] and Cougar [11]), falls into this class.”
Declarative Support for Sensor Data Cleaning (2006, background): “Several systems provide mechanisms for interacting with wireless sensor networks ([27] [10]).”
Tuning Database Configuration Parameters with iTuned (2009, background): “Adaptive Sampling shares goals, but not techniques, with conventional database problems like online aggregation [8], acquisitional query processing [11], and sampling for statistics estimation [2].”
A macroscope in the redwoods (2005, methodology): “TinyDB does support the computation of aggregation functions over table columns, but for this deployment, we used a simple selection query: SELECT result_time, epoch, nodeid, parent, voltage, depth, humidity, humid_temp, hamatop, hamabot FROM sensors SAMPLE PERIOD 5 min To provide a backup in ca”
Model-based approximate querying in sensor networks (2005, background): “Our prior work presented the notion of acquisitional query processing (ACQP) [3] – that is, query processing in environments like sensor networks where it is necessary to”
Top-k Query Processing in Uncertain Databases (2007, background): “Efficient processing of uncertain (probabilistic) data is a crucial requirement in different domains including sensor networks [18] [22] [8], moving objects tracking [7] [9] and data cleaning [12] [3].”
The Design of the Borealis Stream Processing Engine (2005, methodology): “To date systems have exclusively focused on either a server-heavy environment [14, 17, 32] or a sensor-heavy environment [31].”
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.”
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.”
Approximate aggregation techniques for sensor databases (2004, background): “After that, if no more processing is needed for that step, it enters again into the sleeping mode [16].”
Habitat monitoring with sensor networks (2004, background): “In contrast, TinyDB [5] defines a SQL variant as the query language and an associated interpreter running on sensor nodes.”
Secure hierarchical in-network aggregation in sensor networks (2006, background): “Congestion is a commonly used metric in ad-hoc networks since it measures how quickly the heaviest-loaded nodes will exhaust their batteries [6,12].”