M038/GZ06: Readings

Assigned Research Papers

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

Cuervo, E., Balasubramanian, A., Cho, D.-K., Wolman, A., Saroiu, S., Chandra, R., and Bahl, P. MAUI: Making Smartphones Last Longer with Code Offload. In ACM MobiSys, San Francisco, CA, 2010. pdf

Dean, J. and Ghemawat, S. MapReduce: Simplified Data Processing on Large Clusters. In ACM/USENIX OSDI, San Francisco, CA, 2004. pdf

DeCandio, G., Hastorun, D., Jampani, M., Kakulapati, G., Lakshman, A., Pichlin, A., Sivasubramanian, S., Vosshall, P., and Vogels, W. Dynamo: Amazon's Highly Available Key-Value Store. In ACM SOSP, Stevenson, WA, 2007. pdf

Forney, G. D. Jr. The Viterbi Algorithm. Proceedings of the IEEE, 61(3), p. 268-278, March 1973. pdf

Gollakota, S., Perli, S., and 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

Halperin, D., Hu, W., Sheth, A., Wetherall, D. 802.11 with Multiple Antennas for Dummies. In ACM SIGCOMM Computer Communication Review, 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

Perry, J., Balakrishnan, H., and Shah, D. Rateless Spinal Codes. In ACM HotNets, Cambridge, MA, November 2011. pdf

Rai, A., Chintalapudi, K., Padmanabhan, V., Sen, R. Zee: Zero-Effort Crowdsourcing for Indoor Localization. In ACM MobiCom, Istanbul, Turkey, 2012. pdf

Ravindranath, L., Newport, C., Balakrishnan, H., and Madden, S., Improving Wireless Network Performance Using Sensor Hints. In USENIX/ACM 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

Paper notes and errata

Presentation Research Papers

Mobile Applications and Location

How to virtualize a smartphone, so that there are several virtual smartphones running on one piece of smartphone hardware:
Andrus, J., Dall, C., Van't Hof, A., Laadan, O., and Nieh, J., Cells: A Virtual Mobile Smartphone Architecture, in ACM SOSP 2011. pdf (reserved)

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 classic paper on indoor localization that pioneered the radio map method of signal strength based localization:
Bahl, P., Padmanabhan, V. RADAR: An In-Building RF-based User Location and Tracking System, in IEEE Infocom 2000. pdf

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 (Reserved)

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 (reserved)

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

Making fingerprinting-based RF localization probabilistic:
Youssef, M. and Agrawala, A., The Horus WLAN Location Determination System, in ACM MobiSys 2005. pdf

Cloud Computing

How to build a fast yet power-efficient key-value storage system out of a cluster of low-end CPUs:
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 (reserved)

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 (Reserved)

An assessment of how well 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 (Reserved)

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 (Reserved)

How to build a really fast key-value storage system on a multi-core server:
Mao, Y., Kohler, E., and Morris, R., Cache Craftiness for Fast Multicore Key-Value Storage, in ACM EuroSys 2012. pdf (reserved)

A system for incrementally processing many small updates to a large data set:
Peng, D., Dabek, F., Large-Scale Incremental Processing Using Distributed Transactions and Notifications, in USENIX OSDI 2010. pdf (reserved)

How to replicate a database across data centers thousands of miles apart, while maintaining data consistency and offering clients low latency (seemingly conflicting goals!):
Sovran, Y., Power, R., Aguilera, M., and Li, J., Transactional Storage for Geo-Replicated Systems, in ACM SOSP 2011. pdf (reserved)

To make a cloud-based storage system fast, keep all user data in RAM, while using disks purely to ensure durability in the face of power failures:
Ongaro, D., Rumble, S., Stutsman, R, Ousterhout, J., and Rosenblum, M., Fast Crash Recovery in RAMCloud, in ACM SOSP 2011. pdf (reserved)

How to build a cloud-based service in which clients need not trust cloud servers to execute correctly--they can detect if a cloud server deviates from correct execution. Incorporates operational transformation, a classic technique for resolving conflicting concurrent operations done by clients:
Feldman, A., Zeller, W., Freedman, M., and Felten, E., SPORC: Group Collaboration using Untrusted Cloud Resources, in USENIX OSDI 2010. pdf (reserved)

Wireless Networking

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

Combining SIC and rateless codes to overcome the problem of wireless senders not knowing the best rate to choose:
Gudipati, A., Pereira, S., Katti, S. AutoMAC: Rateless Wireless Concurrent Medium Access, in ACM MobiCom 2012. 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

RateMore is a link-layer protocol for rateless codes that learns the probability distribution of the number of symbols required to decode a packet, and uses that distribution in a dynamic programming strategy to produce an optimal transmission schedule:
Iannucci, P., Perry, J., Balakrishnan, H., Shah, D. No Symbol Left Behind: a Link-Layer Protocol for Rateless Codes, in ACM MobiCom 2012. 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 (Reserved)

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

Allowing wideband networks to coexist with narrowband (802.11, Zigbee) devices:
Rahul, H., Kushman, N., Katabi, D., Sodini, C., and Edalat, F., Learning to Share: Narrowband-Friendly Wideband Networks, in ACM SIGCOMM 2008. pdf (reserved)

A system that enables different access points to beamform their signals, and communicate with their clients on the same channel as if they were one large MIMO transmitter:
Rahul, H., Kumar, S., Katabi, D., JMB: Scaling Wireless Capacity with User Demands, in ACM SIGCOMM 2012. pdf (reserved)

The design of a software-defined radio built using commodity multi-core PCs:
Tan, K., Zhang, J., Fang, J., Liu, H., Ye, Y., Wang, S., Zhang, Y., Wu, H., Wang, W., Voelker, G. Sora: High Performance Software Radio Using General Purpose Multi-core Processors, in USENIX NSDI 2008. pdf

Boosting the capacity of wireless LANs by using spatial division techniques to share the wireless channel:
Tan, K., Liu, H., Fang, J., Wang, W., Zhang, J., Chen, M., Voelker, G. SAM: Enabling Practical Spatial Multiple Access in Wireless LAN, in ACM MobiCom. pdf

A new approach to backscatter communication, treating all nodes as if they were a single virtual sender. One can then view collisions as a code across the bits transmitted by the nodes:
Wang, J., Hassanieh, H., Katabi, D., Indyk, P., Efficient and Reliable Low-Power Backscatter Networks, in ACM SIGCOMM 2012. pdf

A follow-on to SampleRate rate adaptation and related work:
Wong, S. H. Y., Yang, H., Lu, S., Bharghavan, V., Robust Rate Adaptation in 802.11 Wireless Networks, in ACM MobiCom 2006. pdf (reserved)

Distinguishing collisions from weak signals:
Rayanchu, S., Mishra, A., Agrawal, D., Saha, S., Banerjee, S. Diagnosing Wireless Packet Losses in 802.11: Separating Collision from Weak Signals, in IEEE INFOCOM 2008. pdf (reserved)

Using PHY-layer information to improve rate adaptation:
Vutukuru, M., Balakrishnan, H., Jamieson, K. Cross-Layer Wireless Bit Rate Adaptation, in ACM SIGCOMM 2009. pdf (reserved)

Synopsis Diffusion: how to forward sensor readings over multiple paths to a base station for robustness, without duplicating sensed values:
Nath, S., Gibbons, P., Seshan, S., and Anderson, Z. Synopsis Diffusion for Robust Aggregation in Sensor Networks, in ACM SenSys 2004. pdf