The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Augmenting mobile 3G using WiFi
Abstract
We investigate if WiFi access can be used to augment 3G capacity in mobile environments. We rst conduct a detailed study of 3G and WiFi access from moving vehicles, in three different cities. We find that the average 3G and WiFi availability across the cities is 87% and 11%, respectively. WiFi throughput is lower than 3G through-put, and WiFi loss rates are higher. We then design a system, called Wiffler, to augments mobile 3G capacity. It uses two key ideas leveraging delay tolerance and fast switching -- to overcome the poor availability and performance of WiFi. For delay tolerant applications, Wiffler uses a simple model of the environment to predict WiFi connectivity. It uses these predictions to delays transfers to offload more data on WiFi, but only if delaying reduces 3G usage and the transfers can be completed within the application's tolerance threshold. For applications that are extremely sensitive to delay or loss (e.g., VoIP), Wiffler quickly switches to 3G if WiFi is unable to successfully transmit the packet within a small time window. We implement and deploy Wiffler in our vehicular testbed. Our experiments show that Wiffler significantly reduces 3G usage. For a realistic workload, the reduction is 45% for a delay tolerance of 60 seconds.
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Cites
CarTel: a distributed mobile sensor computing system
Hull, B., Bychkovsky, V., Zhang, Y., Chen, K., Goraczko, M., Miu, A., Shih, E., Balakrishnan, H., & Madden, S. (2006) · Proceedings of the 4th international conference on Embedded networked sensor systems · doi:10.1145/1182807.1182821 · Cited by 1,030
BreadCrumbs: forecasting mobile connectivity
Nicholson, A. J., & Noble, B. D. (2008) · Proceedings of the 14th ACM international conference on Mobile computing and networking · doi:10.1145/1409944.1409952 · Cited by 346
Rahmati, A., & Zhong, L. (2007) · International Conference on Mobile Systems, Applications, and Services · doi:10.1145/1247660.1247681 · Cited by 262
Predictive methods for improved vehicular WiFi access
Deshpande, P., Kashyap, A., Sung, C., & Das, S. R. (2009) · International Conference on Mobile Systems, Applications, and Services · doi:10.1145/1555816.1555843 · Cited by 137
Understanding wifi-based connectivity from moving vehicles
Mahajan, R., Zahorjan, J., & Zill, B. (2007) · ACM SIGCOMM Internet Measurement Conference (IMC) · doi:10.1145/1298306.1298351 · Cited by 108
Self-citationBalasubramanian, A., Zhou, Y., Croft, W. B., Levine, B. N., & Venkataramani, A. (2007) · ACM Workshop on Challenged Networks (CHANTS) · doi:10.1145/1287791.1287803 · Cited by 95
Self-citationSupporting vehicular mobility in urban multi-hop wireless networks
Giannoulis, A., Fiore, M., & Knightly, E. W. (2008) · International Conference on Mobile Systems, Applications, and Services · doi:10.1145/1378600.1378608 · Cited by 67
Cited by
Impact of cloudlets on interactive mobile cloud applications
Fesehaye, D., Gao, Y., Nahrstedt, K., & Wang, G. (2012) · 2012 IEEE 16th International Enterprise Distributed Object Computing Conference · doi:10.1109/edoc.2012.23 · Cited by 147
Computing at the mobile edge: designing elastic android applications for computation offloading
Orsini, G., Bade, D., & Lamersdorf, W. (2015) · 2015 8th IFIP Wireless and Mobile Networking Conference (WMNC) · doi:10.1109/wmnc.2015.10 · Cited by 112
Metadata
- Authors
- Balasubramanian, A., Mahajan, R., & Venkataramani, A.
- Venue
- Proceedings of the 8th international conference on Mobile systems, applications, and services
- Publisher
- ACM
- Published
- 2010-06-15
- Pages
- 209-222
- OpenAlex
- W2132777427
- Cited by
- 587
- References
- 7
- FWCI
- 57.82
- Type
- conference paper
- Language
- en
- Open access
- closed
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