Sensor Coordination using Active Dataspaces

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Programming wireless sensor networks is notoriously difficult because of severe resource constraints for sensors, unstable and low-bandwidth communication links, unreliable nodes, inaccessible and hostile deployment environments for certain applications, and potentially a large number of nodes. To ease the building of sensor network applications, the objective of this research is to develop a high-level programming abstraction that facilitates resource-efficient, data-centric, and trustworthy computing for large-scale sensor networks, and is applicable to a wide range of sensor network applications.

This approach involves designing a sensor coordination model called active dataspace (ADS), an active data repository that provides associative operations for data access, and developing techniques to implement the ADS model in a resource-efficient, robust, and trustworthy fashion. This research extends previous work on the tuple space coordination model to address the challenges for sensor networks. Specifically, the ADS model presents a novel construct called virtual tuple that supports a data-on-demand strategy to conserve the resources of data producers when their services are not needed, and presents constructs that facilitate in-network aggregation and exploiting locality.

This project is sponsored by the National Science Foundation, and is supported by an Intel Equipment Grant.

Principal Investigator:

Project Members:
  • Mohamed Abdelhafez (Georgia Institute of Technology)
  • Gautam Bhanage (Rutgers University)
  • Ahmed Mansy (Georgia Institute of Technology)

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Last updated: October 17, 2007