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Cited by 328

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Emerging challenges: Mobile networking for “Smart Dust”

Kahn, Joseph M., Katz, Randy Howard, Pister, Kristofer S. J.·2000·Journal of Communications and Networks

Abstract

Large-scale networks of wireless sensors are becoming increasingly tractable. Advances in hardware technology and engineering design have led to dramatic reductions in size, power consumption and cost for digital circuitry, wireless communications and Micro ElectroMechanical Systems (MEMS). This has enabled very compact, autonomous and mobile nodes, each containing one or more sensors, computation and communication capabilities, and a power supply. The missing ingredient is the networking and applications layers needed to harness this revolutionary capability into a complete system. We review the key elements of the emergent technology of “Smart Dust” and outline the research challenges they present to the mobile networking and systems community, which must provide coherent connectivity to large numbers of mobile network nodes co-located within a small volume.

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Crossref · 10.1109/jcn.2000.6596708

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Metadata

Authors
Kahn, J. M., Katz, R. H., & Pister, K. S. J.
Venue
Journal of Communications and Networks
Published
2000-09
Volume
2
Issue
3
Pages
188-196
ISSN
  • 1229-2370 (ISSN-L)
  • 1976-5541
OpenAlex
W2280940837
Cited by
328
References
2
FWCI
19.10
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Emerging challenges: Mobile networking for “Smart Dust”. https://app.cochat.ai/papers/10.1109/jcn.2000.6596708
The paper
Kahn, J. M., Katz, R. H., & Pister, K. S. J. (2000). Emerging challenges: Mobile networking for “Smart Dust”. Journal of Communications and Networks. https://doi.org/10.1109/jcn.2000.6596708

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.