GHT: a geographic hash table for data-centric storage

  • Authors:

  • Sylvia Ratnasamy;Brad Karp;Li Yin;Fang Yu;Deborah Estrin;Ramesh Govindan;Scott Shenker

  • Affiliations:

  • ICIR/ICSI, Berkeley, CA;ICIR/ICSI, Berkeley, CA;Berkeley EECS, Berkeley, CA;Berkeley EECS, Berkeley, CA;UCLA Comp. Sci., LA, CA;USC Comp. Sci., LA, CA;ICIR/ICSI, Berkeley, CA

  • Venue:
  • WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
  • Year:
  • 2002

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Abstract

Making effective use of the vast amounts of data gathered by large-scale sensor networks will require scalable, self-organizing, and energy-efficient data dissemination algorithms. Previous work has identified data-centric routing as one such method. In an asso-ciated position paper [23], we argue that a companion method, data-centric storage (DCS), is also a useful approach. Under DCS, sensed data are stored at a node determined by the name associated with the sensed data. In this paper, we describe GHT, a Geographic Hash Table system for DCS on sensornets. GHT hashes keys into geographic coordi-nates, and stores a key-value pair at the sensor node geographically nearest the hash of its key. The system replicates stored data lo-cally to ensure persistence when nodes fail. It uses an efficient consistency protocol to ensure that key-value pairs are stored at the appropriate nodes after topological changes. And it distributes load throughout the network using a geographic hierarchy. We evaluate the performance of GHT as a DCS system in simulation against two other dissemination approaches. Our results demonstrate that GHT is the preferable approach for the application workloads predicted in [23], offers high data availability, and scales to large sensornet deployments, even when nodes fail or are mobile.