The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
PRISM: platform for remote sensing using smartphones
Abstract
To realize the potential of opportunistic and participatory sensing using mobile smartphones, a key challenge is ensuring the ease of developing and deploying such applications, without the need for the application writer to reinvent the wheel each time. To this end, we present a Platform for Remote Sensing using Smartphones (PRISM) that balances the interconnected goals of generality, security, and scalability. PRISM allows application writers to package their applications as executable binaries, which offers efficiency and also the flexibility of reusing existing code modules. PRISM then pushes the application out automatically to an appropriate set of phones based on a specified set of predicates. This push model enables timely and scalable application deployment while still ensuring a good degree of privacy. To safely execute untrusted applications on the smartphones, while allowing them controlled access to sensitive sensor data, we augment standard software sandboxing with several PRISM-specific elements like resource metering and forced amnesia.
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Tor: The Second-Generation Onion Router
Dingledine, R., Mathewson, N., & Syverson, P. (2004) · doi:10.21236/ada465464 · Cited by 4,104
Nericell: rich monitoring of road and traffic conditions using mobile smartphones
Mohan, P., Padmanabhan, V. N., & Ramjee, R. (2008) · Proceedings of the 6th ACM conference on Embedded network sensor systems · doi:10.1145/1460412.1460444 · Cited by 1,267
Self-citationThe pothole patrol: using a mobile sensor network for road surface monitoring
Eriksson, J., Girod, L., Hull, B., Newton, R., Madden, S., & Balakrishnan, H. (2008) · Proceedings of the 6th international conference on Mobile systems, applications, and services · doi:10.1145/1378600.1378605 · Cited by 1,116
Miluzzo, E., Lane, N. D., Fodor, K., Peterson, R., Lu, H., Musolesi, M., Eisenman, S. B., Zheng, X., & Campbell, A. T. (2008) · Proceedings of the 6th ACM conference on Embedded network sensor systems · doi:10.1145/1460412.1460445 · Cited by 1,032
Mun, M., Reddy, S., Shilton, K., Yau, N., Burke, J., Estrin, D., Hansen, M., Howard, E., West, R., & Boda, P. (2009) · Proceedings of the 7th international conference on Mobile systems, applications, and services · doi:10.1145/1555816.1555823 · Cited by 662
The Rise of People-Centric Sensing
Campbell, A. T., Eisenman, S. B., Lane, N. D., Miluzzo, E., Peterson, R. A., Lu, H., Zheng, X., Musolesi, M., Fodor, K., & Ahn, G.-S. (2008) · IEEE Internet Computing · doi:10.1109/mic.2008.90 · Cited by 573
MoteLab: a wireless sensor network testbed
Werner-Allen, G., Swieskowski, P., & Welsh, M. (2005) · Information Processing in Sensor Networks · doi:10.5555/1147685.1147769 · Cited by 521
Micro-Blog: sharing and querying content through mobile phones and social participation
Gaonkar, S., Li, J., Choudhury, R. R., Cox, L., & Schmidt, A. (2008) · Proceedings of the 6th international conference on Mobile systems, applications, and services · doi:10.1145/1378600.1378620 · Cited by 405
Scale and performance in the Denali isolation kernel
Whitaker, A., Shaw, M., & Gribble, S. D. (2002) · ACM SIGOPS Operating Systems Review · doi:10.1145/844128.844147 · Cited by 377
Anonysense: privacy-aware people-centric sensing
Cornelius, C., Kapadia, A., Kotz, D., Peebles, D., Shin, M., & Triandopoulos, N. (2008) · Proceedings of the 6th international conference on Mobile systems, applications, and services · doi:10.1145/1378600.1378624 · Cited by 377
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Lane, N., Miluzzo, E., Lu, H., Peebles, D., Choudhury, T., & Campbell, A. (2010) · IEEE Communications Magazine · doi:10.1109/mcom.2010.5560598 · Cited by 2,292
Wireless Sensor Networks for Healthcare
Ko, J., Lu, C., Srivastava, M. B., Stankovic, J. A., Terzis, A., & Welsh, M. (2010) · Proceedings of the IEEE · doi:10.1109/jproc.2010.2065210 · Cited by 733
A Survey on Mobile Crowdsensing Systems: Challenges, Solutions, and Opportunities
Capponi, A., Fiandrino, C., Kantarci, B., Foschini, L., Kliazovich, D., & Bouvry, P. (2019) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2914030 · Cited by 594
A location-based incentive mechanism for participatory sensing systems with budget constraints
Jaimes, L. G., Vergara-Laurens, I., & Labrador, M. A. (2012) · 2012 IEEE International Conference on Pervasive Computing and Communications · doi:10.1109/percom.2012.6199855 · Cited by 256
Twitch crowdsourcing: crowd contributions in short bursts of time
Vaish, R., Wyngarden, K., Chen, J., Cheung, B., & Bernstein, M. S. (2014) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/2556288.2556996 · Cited by 95
Metadata
- Authors
- Das, T., Mohan, P., Padmanabhan, V. N., Ramjee, R., & Sharma, A.
- Venue
- Proceedings of the 8th international conference on Mobile systems, applications, and services
- Publisher
- ACM
- Published
- 2010-06-15
- Pages
- 63-76
- OpenAlex
- W1964375680
- Cited by
- 274
- References
- 26
- FWCI
- 23.25
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Das, T., Mohan, P., Padmanabhan, V. N., Ramjee, R., & Sharma, A. (2010). PRISM: platform for remote sensing using smartphones. Proceedings of the 8th international conference on Mobile systems, applications, and services. https://doi.org/10.1145/1814433.1814442
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