Ananthanarayanan, G., Haridasan, M., Mohomed, I., Terry, D., Thekkath, C. StarTrack: A Framework for Enabling Track-Based Applications. In ACM MobiSys, Krakow, Poland, 2009. pdf
Bicket, J. Bitrate Selection in Wireless Networks. MIT MS Thesis, 2005. pdf
Bicket, J., Aguayo, D., Biswas, S., and Morris, R. Architecture and Evaluation of an Unplanned 802.11b Mesh Network. In ACM MobiCom, Koeln, Germany, 2005. pdf
Biswas, S., Morris, R. Opportunistic Routing in Multi-Hop Wireless Networks. In ACM SIGCOMM, Philadelphia, PA, 2005. pdf
Chandra, R., Mahajan, R., Moscibroda, T., Raghavendra, R, and Bahl, V. A Case for Adapting Channel Width in Wireless Networks. In ACM SIGCOMM, Seattle, WA, 2007. pdf
Forney, G. D. Jr. The Viterbi Algorithm. Proceedings of the IEEE 61(3), 268-278, March 1973. pdf
Gollakota, S., Perli, S., Katabi, D. Interference Alignment and Cancellation. In ACM SIGCOMM, Barcelona, Spain, 2009. pdf
Halperin, D., Anderson, T., and Wetherall, D. Taking the Sting out of Carrier Sense: Interference Cancellation for Wireless LANs. In ACM MobiCom, San Francisco, CA, 2008. pdf
Haridasan, M., Mohomed, I., Terry, D., Thekkath, C., Zhang, L. StarTrack Next Generation: A Scalable Infrastructure for Track-Based Applications. In USENIX OSDI, Vancouver, B.C., 2010. pdf
Karp, B. and Kung, H.T., GPSR: Greedy Perimeter Stateless Routing for Wireless Networks. In ACM MobiCom, Boston, MA, 2000. pdf
Kim, Y.-J., Govindan, R., Karp, B., and Shenker, S., Geographic Routing Made Practical. In USENIX NSDI, Boston, MA 2005. pdf
Miu, A., Balakrishnan, H., and Koksal, C. E. Improving Loss Resilience wih Multi-Radio Diversity in Wireless Networks. In ACM MobiCom, Cologne, Germany, 2005. pdf
Piatek, M., Isdal, T., Anderson, T., Krishnamurthy, A., and Venkataramani, A. Do Incentives Build Robustness in BitTorrent? In USENIX NSDI, Cambridge, MA, 2007. pdf
Ravindranath, L., Newport, C., Balakrishnan, H., and Madden, S., Improving Wireless Network Performance Using Sensor Hints, pre-publication draft, to appear in USENIX NSDI, Boston, MA, 2011. pdf
Stoica, I., Morris, R., Karger, D., Kaashoek, M.F., and Balakrishnan, H. Chord: A Scalable Peer-to-Peer Lookup Service for Internet Applications. In ACM SIGCOMM, San Diego, CA, 2001. pdf
Thiagarajan, A., Ravindranath, L., LaCurts, K., Madden, S., Balakrishnan, H., Toledo, S., Eriksson, J. VTrack: Accurate, Energy-Aware Road Traffic Delay Estimation Using Mobile Phones. In ACM SenSys, Berkeley, CA, 2009. pdf
Localizing mobile phones based on ambient sounds they hear:
Azizyan, M., Constandache, I., Choudhury, R. SurroundSense: Mobile
Phone Localization via Ambience Fingerprinting, in ACM MobiCom
2009. pdf (Reserved)
A platform for enabling remote sensing with smartphones:
Das, T., Mohan, P., Padmanabhan, V. PRISM: Platform for Remote
Sensing Using Smartphones, in ACM MobiSys 2010. pdf
Access control for data and applications when sharing your phone
with another user:
Liu, Y., Rahmati, A., Huang, Y., Jang, H., Zhong, L., Zhang, Y.,
Zhang, S. xShare: Supporting Impromptu Sharing of Mobile Phones, in
ACM MobiSys 2009. pdf
An application for detecting available parking spaces as you drive by them
and alerting other drivers:
Mathur, S., Jin, T., Katurirangan, N., Chandrashekharan, J., Xue, W.,
Gruteser, M., and Trappe, W., ParkNet: Drive-by Sensing of Road-Side
Parking Statistics, in ACM MobiSys 2010. pdf (Reserved)
An application that senses when phone users are near one another and
shares the information over social network sites like Facebook:
Miluzzo, E., Lane, N., Fodor, K., Peterson, R., Lu, H., Musolesi, M.,
Eisenman, S., Zheng, X., Campbell, A. Sensing Meets Mobile Social
Networks: The Design, Implementation, and Evaluation of the CenceMe
Application, in ACM SenSys 2008. pdf (Reserved)
Applying machine learning techniques to sensing and inference on
mobile phones:
Miluzzo, E., Cornelius, C., Ramaswamy, A., Choudhury, T., Liu, Z.,
Campbell, A. Darwin Phones: The Evolution of Sensing and Inference on
Mobile Phones, in ACM MobiSys 2010. pdf
Using smartphones to measure traffic congestion and road conditions,
making the measurements available to others:
Mohan, P., Padmanabhan, V., Ramjee, R. Nericell: Rich Monitoring of
Road and Traffic Conditions using Mobile Smartphones, in ACM SenSys
2008. pdf
A system that models a user's mobility patterns to predict which
type of network connectivity is available:
Nicholson, A., Noble, B. Breadcrumbs: Forecasting Mobile
Connectivity, in ACM MobiCom 2008. pdf
Using smartphones as virtual machine image caches to reduce
the volume of data that must be sent wirelessly when migrating a virtual
machine:
Smaldone, S., Gilbert, B., Bila, N., Iftode, L., de Lara, E., and
Satyanarayanan, M., Leveraging Smart Phones to Reduce Mobility
Footprints, in ACM MobiSys 2009. pdf (Reserved)
Using humans to validate image search results:
Yan, T., Kumar, V., Ganesan, D. CrowdSearch: Exploiting Crowds for
Accurate Real-Time Image Search on Mobile Phones, in ACM MobiSys
2010. pdf
A design for a low-power cluster:
Andersen, D., Franklin, J., Kaminsky, M., Phanishayee, A., Tan, L., and Vasudevan, V., FAWN: A Fast Array of Wimpy Nodes, in ACM SOSP 2009. pdf
How to run dozens of virtualized PCs (virtual machines) on a single
physical PC:
Barham, P., Dragovic, B., Fraser, K., Hand, S., Harris, T., Ho, A.,
Neugebauer, R., Pratt, I., and Warfield, A., Xen and the Art of Virtualization, in ACM SOSP 2003. pdf (Reserved)
The design of the storage system Facebook uses for photo data:
Beaver, D., Kumar, S., Li, H., Sobel, J., and Vajgel, P., Finding a
Needle in a Haystack: Facebook's Photo Storage, in USENIX OSDI
2010. pdf
An assessment of how well server Linux scales to a 48-core CPU when
running server workloads:
Boyd-Wickizer, S., Clements, A., Mao, Y., Pesterev, A., Kaashoek,
M.F., Morris, R., and Zeldovich, N., An Analysis of Linux Scalability
to Many Cores, in USENIX OSDI 2010. pdf
One of Google's storage systems for very large datasets:
Chang, F., Dean, J., Ghemawat, S., Hsieh, W., Wallach, D., Burrows,
M., Chandra, T., Fikes, A., and Gruber, R., Bigtable: A Distributed
Storage System for Structured Data, in USENIX OSDI
2006. pdf
How to predict Wi-Fi connectivity using Bluetooth signals and cell
towers:
Ananthanarayanan, G. and Stoica, I., Blue-Fi: Enhancing Wi-Fi
Performance Using Bluetooth Signals, in ACM MobiSys
2009. pdf (Reserved)
Exploiting overhearing using network coding techniques:
Chachulski, S., Jennings, M., Katti, S., and Katabi, D. Trading
Structure for Randonmess in Wireless Opportunistic Routing, in ACM
SIGCOMM 2007.
pdf
Estimating the number of incorrect bits in a packet:
Chen, B., Zhou, Z., Zhao, Y., Yu, H. Efficient Error Estimating
Coding: Feasibility and Applications, in ACM SIGCOMM 2010.
pdf
A clever variation on interference cancellation that solves the hidden terminal problem:
Gollakota, S., and Katabi, D. ZigZag Decoding: Combating Hidden Terminals in Wireless Networks, in ACM SIGCOMM 2008.
pdf
Predicting packet delivery rate in an OFDM system:
Halperin, D., Hu, W., Sheth, A., Wetherall, D. Predictable 802.11
Packet Delivery from Wireless Channel Measurements, in ACM SIGCOMM
2010. pdf
Synchronizing 802.11 transmissions to a very fine timescale:
Rahul, H., Hassanieh, H., Katabi, D. SourceSync: A Distributed
Wireless Architecture for Exploiting Sender Diversity, in ACM SIGCOMM
2010. pdf (Reserved)
Sharing the channel in frequency as well as with random access:
Tan, K., Zhang, Y. Chen, S., Shi, L., Zhang, J., Zhang, Y.
Fine-grained Channel Access in Wireless LAN, ACM SIGCOMM
2010. pdf
Going beyond MRD to use soft information to combine
packets at multiple APs:
Woo, G., Kheradpour, P., Shen, D., Katabi, D. Beyond the Bits:
Cooperative Packet Recovery using Physical Layer Information, in
ACM MobiCom 2007. pdf