GHT: a geographic hash table for data-centric storage

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.

DOI: 10.1145/570738.570750
View Slides

Extracted Key Phrases

16 Figures and Tables

050100150'01'03'05'07'09'11'13'15'17
Citations per Year

1,036 Citations

Semantic Scholar estimates that this publication has 1,036 citations based on the available data.

See our FAQ for additional information.

Cite this paper

@inproceedings{Ratnasamy2002GHTAG, title={GHT: a geographic hash table for data-centric storage}, author={Sylvia Ratnasamy and Brad Karp and Li Yin and Fang Yu and Deborah Estrin and Ramesh Govindan and Scott Shenker}, booktitle={WSNA}, year={2002} }