PRESTO: a predictive storage architecture for sensor networks

  • Authors:
  • Peter Desnoyers;Deepak Ganesan;Huan Li;Ming Li;Prashant Shenoy

  • Affiliations:
  • University of Massachusetts Amherst;University of Massachusetts Amherst;University of Massachusetts Amherst;University of Massachusetts Amherst;University of Massachusetts Amherst

  • Venue:
  • HOTOS'05 Proceedings of the 10th conference on Hot Topics in Operating Systems - Volume 10
  • Year:
  • 2005

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Abstract

We describe PRESTO, a predictive storage architecture for emerging large-scale, hierarchical sensor networks. In contrast to existing techniques, PRESTO is a proxy-centric architecture, where tethered proxies balance the need for interactive querying from users with the energy optimization needs of the remote sensors. The main novelty in this work lies in extensive use of predictive techniques that are a natural fit to the correlated behavior of the physical world. PRESTO exploits technology trends in storage to build an architecture that emphasizes archival at remote sensors and intelligent caching at proxies. The system also addresses user needs for querying such sensor networks by exposing a unified, easy to use data abstraction across numerous proxies and remote sensors.