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COUGAR: the network is the database
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Source International Conference on Management of Data archive
Proceedings of the 2002 ACM SIGMOD international conference on Management of data table of contents
Madison, Wisconsin
DEMONSTRATION SESSION: Networks applications table of contents
Pages: 621 - 621  
Year of Publication: 2002
ISBN:1-58113-497-5
Authors
Wai Fu Fung  Cornell University, Ithaca, NY
David Sun  Cornell University, Ithaca, NY
Johannes Gehrke  Cornell University, Ithaca, NY
Sponsor
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
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ABSTRACT

The widespread distribution and availability of small-scale sensors, actuators, and embedded processors is transforming the physical world into a computing platform. One such example is a sensor network consisting of a large number of sensor nodes that combine physical sensing capabilities such as temperature, light, or seismic sensors with networking and computation capabilities [1]. Applications range from environmental control, warehouse inventory, health care to military environments. Existing sensor networks assume that the sensors are preprogrammed and send data to a central frontend where the data is aggregated and stored for offfsline querying and analysis. This approach has two major draw-backs. First, the user cannot change the behavior of the system on the fly. Second, communication in today's networks is orders of magnitude more expensive than local computation, thus in-network processing can vastly reduce resource usage and thus extend the lifetime of a sensor network.This demo demonstrates a database approach to unite the seemingly conflicting requirements of scalability and flexibility in monitoring the physical world. We demonstrate the COUGAR System, a new distributed data management infrastructure that scales with the growth of sensor interconnectivity and computational power on the sensors over the next decades. Our system resides directly on the sensor nodes and creates the abstraction of a single processing node without centralizing data or computation.




Collaborative Colleagues:
Wai Fu Fung: colleagues
David Sun: colleagues
Johannes Gehrke: colleagues