Towards Sensor Database Systems

By Philippe Bonnet, Johannes Gehrke, Praveen Seshadri. International Conference on Mobile Data Management, 2001

923 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition, Signal Processing

View Paper: https://www.semanticscholar.org/paper/83a500fcc7cd98db063b73461277ac885c8fe7c3

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

In Computer Networks and Communications

In Computer Vision and Pattern Recognition

In Signal Processing

Citations in the corpus

Hyrax: Cloud Computing on Mobile Devices using MapReduce (2009, methodology): “They provide high-level database interfaces for executing queries on distributed data Yao and Gehrke [2002], Bonnet et al. [2001], Madden et al.”
Proceedings of the 5th Symposium on Operating Systems Design and Implementation Tag: a Tiny Aggregation Service for Ad-hoc Sensor Networks (positive): “As is the case in Cougar [23], this table can be thought of as an append-only relational table with one attribute per input of the motes (e.g., temperature, light.)”
Middleware for Internet of Things: A Survey (2016, positive): “COUGAR provides flexible and scalable access to large collections of sensors.”
Real-time communication and coordination in embedded sensor networks (2003, methodology): “This approach is implemented in the COUGAR sensor network database [21].”
Connected sensor cover: self-organization of sensor networks for efficient query execution (2003, background): “in the sensor network has a geographic location associated with it in addition to a timestamp [3], [4].”
Evaluating window joins over unbounded streams (2003, methodology): “Examples of this work include Berkeleys Telegraph [13] and Cornells Cougar database project [14].”
Synopsis diffusion for robust aggregation in sensor networks (2004, methodology): “A popular approach used by sensor database systems such as TinyDB [22] and Cougar [6, 27] is to construct a spanning tree in the network, rooted at the querying node, and then perform in-network aggregation along the tree.”
TinyDB: an acquisitional query processing system for sensor networks (2005, methodology): “There has been some recent publication in the database and systems communities on query processing in sensor networks [Intanagonwiwat et al. 2000; Madden et al. 2002a; Bonnet et al. 2001; Madden and Franklin 2002; Yao and Gehrke 2002].”
Approximate join processing over data streams (2003, background): “Adaptive query processing systems like Telegraph [18], NiagaraCQ [9], sensor database systems [5] and adaptive techniques as proposed in [7, 20, 24] aim at providing the best possible query performance in continuously changing environments like the Internet.”
Issues in data stream management (2003, background): “Limitations of traditional DBMSs in supporting streaming applications have been recognized, prompting research to augment existing technologies and build new systems to manage streaming data.”
Efficient Computation of Frequent and Top-k Elements in Data Streams (2005, background): “Currently, data stream management systems are used for monitoring click streams [31], stock tickers [11, 46], sensor readings [7], telephone call records [15], network packet traces [17], auction bidding patterns [2], traffic management [3], network-aware clustering [12], and security against DoS [1”
Wireless sensor networks: A survey on the state of the art and the 802.15.4 and ZigBee standards (2007, methodology): “Cougar [15,16,130] is a sensor network database developed at Cornell University and shares many similarities with TinyDB.”
Event Detection Services Using Data Service Middleware in Distributed Sensor Networks (2003, methodology): “…research projects in the area of sensor networks, such as Cougar, Rutgers Dataman, SINA, SCADDS, Smart-msgs, and some virtual-machine-like designs (Cougar Project, 2000)(Dataman Project, 1999)(SCADDS Project, 1999)(Smart Message Project, 2000)(Bonnet, 2001)(Feng, 2002)(Mattern, 2002)(Shen, 2001).”
Continuously adaptive continuous queries over streams (2002, methodology): “[29] discusses models of data streaming from sensors.”
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].”
APTEEN: a hybrid protocol for efficient routing and comprehensive information retrieval in wireless (2002, methodology): “[1][2] discuss the application of distributed query execution techniques to improve communication efficiency in sensor and device networks.”
IrisNet: An Architecture for a Worldwide Sensor Web (2003, methodology): “1–3 In contrast, in IrisNet we seek to broaden the traditional notion of sensor networks to include wide-area “sensor webs,” 4 such as those comprising Inter-net-connected, widely-dispersed PC-class nodes with powerful CPUs that can process rich sensor data sources.”