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Cabernet: vehicular content delivery using WiFi
Abstract
Cabernet is a system for delivering data to and from moving vehicles using open 802.11 (WiFi) access points encountered opportunistically during travel. Using open WiFi access from the road can be challenging. Network connectivity in Cabernet is both fleeting (access points are typically within range for a few seconds) and intermittent (because the access points do not provide continuous coverage), and suffers from high packet loss rates over the wireless channel. On the positive side, WiFi data transfers, when available, can occur at broadband speeds.
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Citations
Cited by
Predictable 802.11 packet delivery from wireless channel measurements
Halperin, D., Hu, W., Sheth, A., & Wetherall, D. (2010) · ACM SIGCOMM Computer Communication Review · doi:10.1145/1851275.1851203 · Cited by 341
Throughput Analysis of Vehicular Internet Access via Roadside WiFi Hotspot
Xu, W., Shi, W., Lyu, F., Zhou, H., Cheng, N., & Shen, X. (2019) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2019.2900032 · Cited by 46
Metadata
- Authors
- Eriksson, J., Balakrishnan, H., & Madden, S.
- Venue
- Proceedings of the 14th ACM international conference on Mobile computing and networking
- Publisher
- ACM
- Published
- 2008-09-14
- Pages
- 199-210
- OpenAlex
- W2106125650
- Cited by
- 427
- References
- 0
- FWCI
- 37.63
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Cabernet: vehicular content delivery using WiFi. https://app.cochat.ai/papers/10.1145/1409944.1409968
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- Eriksson, J., Balakrishnan, H., & Madden, S. (2008). Cabernet: vehicular content delivery using WiFi. Proceedings of the 14th ACM international conference on Mobile computing and networking. https://doi.org/10.1145/1409944.1409968
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.