project 2

Our lab has focused on vehicular sensing systems, mobile computing, and networked sensing. The following sections list some papers in each of these topics.

Vehicular sensing systems

1. MobiSys

   AutoCast: Scalable Infrastructure-Less Cooperative Perception for Distributed Collaborative Driving

   Hang Qiu, Po-Han Huang, Namo Asavisanu, and 3 more authors

   In Proceedings of the 20th Annual International Conference on Mobile Systems, Applications and Services, 2022

   Abs Bib Link

   Autonomous vehicles use 3D sensors for perception. Cooperative perception enables vehicles to share sensor readings with each other to improve safety. Prior work in cooperative perception scales poorly even with infrastructure support. AUTOCAST1 enables scalable infrastructure-less cooperative perception using direct vehicle-to-vehicle communication. It carefully determines which objects to share based on positional relationships between traffic participants, and the time evolution of their trajectories. It coordinates vehicles and optimally schedules transmissions in a distributed fashion. Extensive evaluation results under different scenarios show that, unlike competing approaches, AUTOCAST can avoid crashes and near-misses which occur frequently without cooperative perception, its performance scales gracefully in dense traffic scenarios providing 2-4x visibility into safety critical objects compared to existing cooperative perception schemes, its transmission schedules can be completed on the real radio testbed, and its scheduling algorithm is near-optimal with negligible computation overhead.

   @inproceedings{qiu22a,
     author = {Qiu, Hang and Huang, Po-Han and Asavisanu, Namo and Liu, Xiaochen and Psounis, Konstantinos and Govindan, Ramesh},
     title = {AutoCast: Scalable Infrastructure-Less Cooperative
     		  Perception for Distributed Collaborative Driving},
     year = {2022},
     isbn = {9781450391856},
     publisher = {Association for Computing Machinery},
     address = {New York, NY, USA},
     url = {https://doi.org/10.1145/3498361.3538925},
     doi = {10.1145/3498361.3538925},
     booktitle = {Proceedings of the 20th Annual International Conference on
     		  Mobile Systems, Applications and Services},
     pages = {128–141},
     numpages = {14},
     keywords = {cooperative perception, V2V communication, autonomous
     		  cars},
     location = {Portland, Oregon},
     topics = {vehicular},
     series = {MobiSys '22}
   }

2. NSDI

   CarMap-Fast 3D Feature Map Updates for Automobiles

   Fawad Ahmad, Hang Qiu, Ray Eells, and 2 more authors

   In 17th USENIX Symposium on Networked Systems Design and Implementation (NSDI 20), 2020

   Bib Link Code Slides

   @inproceedings{ahmad2020,
     title = {CarMap-Fast 3D Feature Map Updates for Automobiles},
     author = {Ahmad, Fawad and Qiu, Hang and Eells, Ray and Bai, Fan and Govindan, Ramesh},
     video = {https://www.youtube.com/watch?v=SlG4QGq5ypk},
     year = {2020},
     date = {2020-01-01},
     booktitle = {17th USENIX Symposium on Networked Systems Design and
     		  Implementation (NSDI 20)},
     publisher = {USENIX Association},
     address = {Santa Clara, CA},
     keywords = {},
     pubstate = {published},
     topics = {vehicular},
     tppubtype = {inproceedings}
   }

3. Fusion

   QuickSketch: Building 3D Representations in Unknown Environments Using Crowdsourcing

   Fawad Ahmad, Hang Qiu, Xiaochen Liu, and 2 more authors

   In 2018 21st International Conference on Information Fusion (FUSION), 2018

   Bib Link

   @inproceedings{ahmad:2018,
     title = {QuickSketch: Building 3D Representations in Unknown
     		  Environments Using Crowdsourcing},
     author = {Ahmad, Fawad and Qiu, Hang and Liu, Xiaochen and Bai, Fan and Govindan, Ramesh},
     doi = {10.23919/ICIF.2018.8455437},
     year = {2018},
     date = {2018-07-01},
     booktitle = {2018 21st International Conference on Information Fusion
     		  (FUSION)},
     pages = {2314-2321},
     keywords = {Three-dimensional
     		  displays;Visualization;Cameras;Simultaneous localization
     		  and mapping;Feature extraction},
     pubstate = {published},
     topics = {vehicular},
     tppubtype = {inproceedings}
   }

4. IoTDI

   Kestrel: Video Analytics for Augmented Multi-Camera Vehicle Tracking

   H Qiu, X Liu, S Rallapalli, and 5 more authors

   In 2018 IEEE/ACM Third International Conference on Internet-of-Things Design and Implementation (IoTDI), 2018

   Bib

   @inproceedings{qiu18c,
     title = {Kestrel: Video Analytics for Augmented Multi-Camera
     		  Vehicle Tracking},
     author = {Qiu, H and Liu, X and Rallapalli, S and Bency, A J and Chan, K and Urgaonkar, R and Manjunath, B S and Govindan, R},
     doi = {10.1109/IoTDI.2018.00015},
     year = {2018},
     date = {2018-04-01},
     booktitle = {2018 IEEE/ACM Third International Conference on
     		  Internet-of-Things Design and Implementation (IoTDI)},
     pages = {48-59},
     pubstate = {published},
     tppubtype = {inproceedings},
     topics = {vehicular,sensing},
   }

5. TVT

   Towards Robust Vehicular Context Sensing

   H Qiu, J Chen, S Jain, and 7 more authors

   IEEE Transactions on Vehicular Technology, 2018

   Bib

   @article{qiu18b,
     title = {Towards Robust Vehicular Context Sensing},
     author = {Qiu, H and Chen, J and Jain, S and Jiang, Y and McCartney, M and Kar, G and Bai, F and Grimm, D K and Gruteser, M and Govindan, R},
     doi = {10.1109/TVT.2017.2771623},
     issn = {0018-9545},
     year = {2018},
     date = {2018-03-01},
     journal = {IEEE Transactions on Vehicular Technology},
     volume = {67},
     number = {3},
     pages = {1909-1922},
     keywords = {vehicular sensing},
     topics = {vehicular},
     pubstate = {published},
     tppubtype = {article}
   }

6. MobiSys

   AVR: Augmented Vehicular Reality

   Hang Qiu, Fawad Ahmad, Fan Bai, and 2 more authors

   In Proceedings of the 16th Annual International Conference on Mobile Systems, Applications, and Services (Mobisys), 2018

   Bib Link

   @inproceedings{qiu18d,
     title = {AVR: Augmented Vehicular Reality},
     author = {Qiu, Hang and Ahmad, Fawad and Bai, Fan and Gruteser, Marco and Govindan, Ramesh},
     url = {http://doi.acm.org/10.1145/3210240.3210319},
     doi = {10.1145/3210240.3210319},
     isbn = {978-1-4503-5720-3},
     year = {2018},
     date = {2018-01-01},
     booktitle = {Proceedings of the 16th Annual International Conference on
     		  Mobile Systems, Applications, and Services (Mobisys)},
     pages = {81--95},
     publisher = {ACM},
     address = {Munich, Germany},
     series = {MobiSys '18},
     topics = {vehicular},
     keywords = {Autonomous Cars, Collaborative Sensing, Extended Vision,
     		  vehicular sensing},
     pubstate = {published},
     tppubtype = {inproceedings}
   }

7. Augmented Vehicular Reality: Enabling Extended Vision for Future Vehicles

   Hang Qiu, Fawad Ahmad, Ramesh Govindan, and 3 more authors

   In Proceedings of the 18th International Workshop on Mobile Computing Systems and Applications, HotMobile 2017, Sonoma, CA, USA, February 21 - 22, 2017, 2017

   Bib

   @inproceedings{qiu17a,
     author = {Qiu, Hang and Ahmad, Fawad and Govindan, Ramesh and Gruteser, Marco and Bai, Fan and Kar, Gorkem},
     title = {Augmented Vehicular Reality: Enabling Extended Vision for
     		  Future Vehicles},
     booktitle = {Proceedings of the 18th International Workshop on Mobile
     		  Computing Systems and Applications, HotMobile 2017, Sonoma,
     		  CA, USA, February 21 - 22, 2017},
     pages = {67--72},
     topics = {vehicular},
     year = {2017}
   }

8. SEC

   Real-time Traffic Estimation at Vehicular Edge Nodes

   Gorkem Kar, Shubham Jain, Marco Gruteser, and 2 more authors

   In Proceedings of the Second ACM/IEEE Symposium on Edge Computing, San Jose / Silicon Valley, SEC 2017, CA, USA, October 12-14, 2017, 2017

   Bib

   @inproceedings{kar17b,
     author = {Kar, Gorkem and Jain, Shubham and Gruteser, Marco and Bai, Fan and Govindan, Ramesh},
     title = {{Real-time Traffic Estimation at Vehicular Edge Nodes}},
     booktitle = {{Proceedings of the Second {ACM/IEEE} Symposium on Edge
     		  Computing, San Jose / Silicon Valley, {SEC} 2017, CA, USA,
     		  October 12-14, 2017}},
     pages = {3:1--3:13},
     topics = {vehicular},
     year = {2017}
   }

9. SEC

   Pre-DriveID: Pre-trip Driver Identification from In-vehicle Data

   Gorkem Kar, Shubham Jain, Marco Gruteser, and 3 more authors

   In Proceedings of the Second ACM/IEEE Symposium on Edge Computing, San Jose / Silicon Valley, SEC 2017, CA, USA, October 12-14, 2017, 2017

   Bib

   @inproceedings{kar17a,
     author = {Kar, Gorkem and Jain, Shubham and Gruteser, Marco and Chen, Jinzhu and Bai, Fan and Govindan, Ramesh},
     title = {{Pre-DriveID: Pre-trip Driver Identification from
     		  In-vehicle Data}},
     booktitle = {{Proceedings of the Second {ACM/IEEE} Symposium on Edge
     		  Computing, San Jose / Silicon Valley, {SEC} 2017, CA, USA,
     		  October 12-14, 2017}},
     pages = {2:1--2:12},
     year = {2017},
     topics = {vehicular},
     doi = {10.1145/3132211.3134462}
   }

10. TVT

    Towards Robust Vehicular Context Sensing

    Hang Qiu, Jinzhu Chen, Shubham Jain, and 7 more authors

    IEEE Transactions on Vehicular Technology, 2017

    Bib

    @article{qiu17b,
      author = {Qiu, Hang and Chen, Jinzhu and Jain, Shubham and Jiang, Yurong and McCartney, Matt and Kar, Gorkem and Bai, Fan and Grimm, Donald K. and Gruteser, Marco and Govindan, Ramesh},
      title = {{Towards Robust Vehicular Context Sensing}},
      journal = {IEEE Transactions on Vehicular Technology},
      topics = {vehicular},
      year = {2017}
    }

11. SenSys

    CARLOC: Precisely Tracking Automobile Position

    Yurong Jiang, Hang Qiu, Matthew McCartney, and 5 more authors

    In Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems (SenSys) , no 2015

    Bib

    @inproceedings{jiang15a,
      author = {Jiang, Yurong and Qiu, Hang and McCartney, Matthew and Sukhatme, Gaurav and Gruteser, Marco and Bai, Fan and Grimm, Donald and Govindan, Ramesh},
      title = { {CARLOC: Precisely Tracking Automobile Position} },
      booktitle = { Proceedings of the 13th ACM Conference on Embedded
      		  Networked Sensor Systems (SenSys) },
      month =  no,
      topics = {vehicular},
      location = { Seoul, Korea },
      year = {2015}
    }

Mobile computing

1. SoCC

   Scrooge: A Cost-Effective Deep Learning Inference System

   Yitao Hu, Rajrup Ghosh, and Ramesh Govindan

   In SoCC ’21: ACM Symposium on Cloud Computing, Seattle, WA, USA, November 1 - 4, 2021, 2021

   Bib Link

   @inproceedings{hu2021b,
     author = {Hu, Yitao and Ghosh, Rajrup and Govindan, Ramesh},
     editor = {Curino, Carlo and Koutrika, Georgia and Netravali, Ravi},
     title = {Scrooge: {A} Cost-Effective Deep Learning Inference
     		  System},
     booktitle = {SoCC '21: {ACM} Symposium on Cloud Computing, Seattle, WA,
     		  USA, November 1 - 4, 2021},
     pages = {624--638},
     publisher = {{ACM}},
     year = {2021},
     url = {https://doi.org/10.1145/3472883.3486993},
     doi = {10.1145/3472883.3486993},
     timestamp = {Sun, 31 Oct 2021 10:05:01 +0100},
     topics = {sensing,mobile},
     biburl = {https://dblp.org/rec/conf/cloud/HuGG21.bib}
   }

2. IoTDI

   Rim: Offloading Inference to the Edge

   Yitao Hu, Weiwu Pang, Xiaochen Liu, and 4 more authors

   In Proceedings of the 6th ACM/IEEE Conference on Internet of Things Design and Implementation, 2021, 2021

   Bib Link

   @inproceedings{hu2021,
     title = {Rim: Offloading Inference to the Edge},
     author = {Hu, Yitao and Pang, Weiwu and Liu, Xiaochen and Ghosh, Rajrup and Ko, Bongjun and Lee, Wei-Han and Govindan, Ramesh},
     url = {https://dl.acm.org/doi/abs/10.1145/3450268.3453521},
     year = {2021},
     date = {2021-05-18},
     booktitle = {Proceedings of the 6th ACM/IEEE Conference on Internet of
     		  Things Design and Implementation, 2021},
     pubstate = {published},
     topics = {sensing,mobile},
     tppubtype = {inproceedings}
   }

3. Middleware

   Olympian: Scheduling GPU Usage in a Deep Neural Network Model Serving System

   Yitao Hu, Swati Rallapalli, Bongjun Ko, and 1 more author

   In Proceedings of the 19th International Middleware Conference, 2018

   Bib Link

   @inproceedings{hu:2018,
     title = {Olympian: Scheduling GPU Usage in a Deep Neural Network
     		  Model Serving System},
     author = {Hu, Yitao and Rallapalli, Swati and Ko, Bongjun and Govindan, Ramesh},
     url = {http://doi.acm.org/10.1145/3274808.3274813},
     doi = {10.1145/3274808.3274813},
     isbn = {978-1-4503-5702-9},
     year = {2018},
     date = {2018-12-01},
     booktitle = {Proceedings of the 19th International Middleware
     		  Conference},
     pages = {53--65},
     publisher = {ACM},
     address = {Rennes, France},
     series = {Middleware '18},
     keywords = {Deep Neural Network, GPU Scheduling, Multiple Concurrent
     		  Requests, Predictable Latency, Scheduling Algorithms,
     		  Serving System},
     pubstate = {published},
     topics = {mobile},
     tppubtype = {inproceedings}
   }

4. MobiSys

   Gnome: A Practical Approach to NLOS Mitigation for GPS Positioning in Smartphones

   Xiaochen Liu, Suman Nath, and Ramesh Govindan

   In Proceedings of the 16th Annual International Conference on Mobile Systems, Applications, and Services (Mobisys), 2018

   Bib Link

   @inproceedings{liu18b,
     title = {Gnome: A Practical Approach to NLOS Mitigation for GPS
     		  Positioning in Smartphones},
     author = {Liu, Xiaochen and Nath, Suman and Govindan, Ramesh},
     url = {http://doi.acm.org/10.1145/3210240.3210343},
     doi = {10.1145/3210240.3210343},
     isbn = {978-1-4503-5720-3},
     year = {2018},
     date = {2018-01-01},
     booktitle = {Proceedings of the 16th Annual International Conference on
     		  Mobile Systems, Applications, and Services (Mobisys)},
     pages = {163--177},
     publisher = {ACM},
     address = {Munich, Germany},
     series = {MobiSys '18},
     topics = {mobile},
     keywords = {GPS, Localization, Mobile Computing, NLOS Mitigation},
     pubstate = {published},
     tppubtype = {inproceedings}
   }

5. Ubicomp

   ALPS: Accurate Landmark Positioning at City Scales

   Yitao Hu, Xiaochen Liu, Suman Nath, and 1 more author

   In the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2016) , se 2016

   Bib

   @inproceedings{yitao16a,
     author = {Hu, Yitao and Liu, Xiaochen and Nath, Suman and Govindan, Ramesh},
     title = { {ALPS: Accurate Landmark Positioning at City Scales} },
     booktitle = { the 2016 ACM International Joint Conference on Pervasive
     		  and Ubiquitous Computing (UbiComp 2016) },
     month =  se,
     location = { Heidelberg, Germany },
     year = {2016},
     topics = {mobile},
     		  }
   }

6. MobiSys

   Efficient Privilege De-Escalation for Ad Libraries in Mobile Apps

   Bin Liu, Bin Liu, Hongxia Jin, and 1 more author

   In The 13th Annual International Conference on Mobile Systems, Applications, and Services (MobiSys 2015) , ma 2015

   Bib

   @inproceedings{liu15a,
     author = {Liu, Bin and Liu, Bin and Jin, Hongxia and Govindan, Ramesh},
     title = { {Efficient Privilege De-Escalation for Ad Libraries in
     		  Mobile Apps} },
     booktitle = { The 13th Annual International Conference on Mobile
     		  Systems, Applications, and Services (MobiSys 2015) },
     month =  ma,
     location = { Florence, Italy },
     topics = {mobile},
     year = {2015},
     projects = { }
   }

7. MobiSys

   FlexiWeb: Network-Aware Compaction for Accelerating Mobile Web Transfers

   S. Singh, H. Madhyastha, S. Krishnamurthy, and 1 more author

   In Proc. ACM MobiCom, ma 2015

   Bib

   @inproceedings{singh15a,
     author = {Singh, S. and Madhyastha, H. and Krishnamurthy, S. and Govindan, R.},
     title = {{FlexiWeb: Network-Aware Compaction for Accelerating
     		  Mobile Web Transfers}},
     booktitle = {Proc. ACM MobiCom},
     year = {2015},
     topics = {mobile},
     address = {Paris, France}
   }

Networked sensing

1. MobiCom

   UbiPose: Towards Ubiquitous Outdoor AR Pose Tracking Using Aerial Meshes

   Weiwu Pang, Chunyu Xia, Branden Leong, and 3 more authors

   In Proceedings of the 29th Annual International Conference on Mobile Computing and Networking, 2023

   Bib Link

   @inproceedings{ubipose,
     author = {Pang, Weiwu and Xia, Chunyu and Leong, Branden and Ahmad, Fawad and Paek, Jeongyeup and Govindan, Ramesh},
     title = {UbiPose: Towards Ubiquitous Outdoor AR Pose Tracking Using
     		  Aerial Meshes},
     booktitle = {Proceedings of the 29th Annual International Conference on
     		  Mobile Computing and Networking},
     year = {2023},
     series = {ACM MobiCom '23},
     address = {New York, NY, USA},
     publisher = {Association for Computing Machinery},
     isbn = {9781450399906},
     url = {https://doi.org/10.1145/3570361.3613263},
     doi = {10.1145/3570361.3613263},
     articleno = {49},
     numpages = {16},
     keywords = {augmented reality, outdoor pose estimation, aerial mesh},
     location = {Madrid, Spain},
     topics = {sensing},
   }

2. ICLR

   MCAL: Minimum Cost Human-Machine Active Labeling

   Hang Qiu, Krishna Chintalapudi, and Ramesh Govindan

   In The Eleventh International Conference on Learning Representations , 2023

   Bib Link

   @inproceedings{qiu2023,
     title = {{MCAL}: Minimum Cost Human-Machine Active Labeling},
     author = {Qiu, Hang and Chintalapudi, Krishna and Govindan, Ramesh},
     booktitle = {The Eleventh International Conference on Learning
     		  Representations },
     year = {2023},
     url = {https://openreview.net/forum?id=1FxRPKrH8bw},
     topics = {sensing},
   }

3. ToSN

   Sensing the Sensor: Estimating Camera Properties with Minimal Information

   Pradipta Ghosh, Xiaochen Liu, Hang Qiu, and 3 more authors

   ACM Trans. Sen. Netw., Feb 2022

   Abs Bib Link

   Public outdoor surveillance cameras often have limited metadata describing their properties. Frequently, a public camera’s precise position, orientation, focal length, and image center are unknown; these attributes are necessary to precisely pinpoint the location of events seen in the camera. In this article, we ask: what is the minimal information needed to accurately estimate these properties for public cameras? We show, using a judicious combination of projective geometry, neural networks, and crowd-sourced annotations from human workers, that it is possible to, for example, localize 95% of the cameras in our test data set to within 12 m using a single image taken from the camera. This performance is an order of magnitude better than PoseNet, a state-of-the-art neural network that needs significantly more information than our approach, and can only estimate position and orientation (and not other properties). Finally, we show that the camera’s inferred pose and properties can help design a number of virtual sensors, all of which have good accuracy.

   @article{ghosh22,
     author = {Ghosh, Pradipta and Liu, Xiaochen and Qiu, Hang and Vieira, Marcos A. M. and Sukhatme, Gaurav S. and Govindan, Ramesh},
     title = {Sensing the Sensor: Estimating Camera Properties with
     		  Minimal Information},
     year = {2022},
     issue_date = {May 2022},
     publisher = {Association for Computing Machinery},
     address = {New York, NY, USA},
     volume = {18},
     number = {2},
     issn = {1550-4859},
     url = {https://doi.org/10.1145/3508393},
     doi = {10.1145/3508393},
     journal = {ACM Trans. Sen. Netw.},
     month = feb,
     articleno = {28},
     numpages = {26},
     topics = {sensing},
     keywords = {mechanical turk, Localization, neural network, camera,
     		  vanishing point}
   }

4. TMC

   Synthesis of Large-Scale Instant IoT Networks

   Pradipta Ghosh, Jonathan Bunton, Dimitrios Pylorof, and 6 more authors

   IEEE Transactions on Mobile Computing, Feb 2021

   Abs Bib

   While most networks have long lifetimes, temporary network infrastructure is often useful for special events, pop-up retail, or disaster response. An instant IoT network is one that is rapidly constructed, used for a few days, then dismantled. We consider the synthesis of instant IoT networks in urban settings. This synthesis problem must satisfy complex and competing constraints: sensor coverage, line-of-sight visibility, and network connectivity. The central challenge in our synthesis problem is quickly scaling to large regions while producing cost-effective solutions. We explore two qualitatively different representations of the synthesis problems using satisfiability modulo convex optimization (SMC), and mixed-integer linear programming (MILP). The former is more expressive, for our problem, than the latter, but is less well-suited for solving optimization problems like ours. We show how to express our network synthesis in these frameworks. To scale to problem sizes beyond what these frameworks are capable of, we develop a hierarchical synthesis technique that independently synthesizes networks in sub-regions of the deployment area, then combines these. We find that, while MILP outperforms SMC in some settings for smaller problem sizes, the fact that SMC’s expressivity matches our problem ensures that it uniformly generates better quality solutions at larger problem sizes.

   @article{ghosh2021b,
     title = {Synthesis of Large-Scale Instant IoT Networks},
     author = {Ghosh, Pradipta and Bunton, Jonathan and Pylorof, Dimitrios and Vieira, Marcos A. M. and Chan, Kevin and Govindan, Ramesh and Sukhatme, Gaurav S. and Tabuada, Paulo and Verma, Gunjan},
     doi = {10.1109/TMC.2021.3099005},
     year = {2021},
     date = {2021-09-01},
     journal = {IEEE Transactions on Mobile Computing},
     pubstate = {published},
     topics = {sensing},
     tppubtype = {article}
   }

5. SoCC

   Scrooge: A Cost-Effective Deep Learning Inference System

   Yitao Hu, Rajrup Ghosh, and Ramesh Govindan

   In SoCC ’21: ACM Symposium on Cloud Computing, Seattle, WA, USA, November 1 - 4, 2021, Feb 2021

   Bib Link

   @inproceedings{hu2021b,
     author = {Hu, Yitao and Ghosh, Rajrup and Govindan, Ramesh},
     editor = {Curino, Carlo and Koutrika, Georgia and Netravali, Ravi},
     title = {Scrooge: {A} Cost-Effective Deep Learning Inference
     		  System},
     booktitle = {SoCC '21: {ACM} Symposium on Cloud Computing, Seattle, WA,
     		  USA, November 1 - 4, 2021},
     pages = {624--638},
     publisher = {{ACM}},
     year = {2021},
     url = {https://doi.org/10.1145/3472883.3486993},
     doi = {10.1145/3472883.3486993},
     timestamp = {Sun, 31 Oct 2021 10:05:01 +0100},
     topics = {sensing,mobile},
     biburl = {https://dblp.org/rec/conf/cloud/HuGG21.bib}
   }

6. IoTDI

   Rim: Offloading Inference to the Edge

   Yitao Hu, Weiwu Pang, Xiaochen Liu, and 4 more authors

   In Proceedings of the 6th ACM/IEEE Conference on Internet of Things Design and Implementation, 2021, Feb 2021

   Bib Link

   @inproceedings{hu2021,
     title = {Rim: Offloading Inference to the Edge},
     author = {Hu, Yitao and Pang, Weiwu and Liu, Xiaochen and Ghosh, Rajrup and Ko, Bongjun and Lee, Wei-Han and Govindan, Ramesh},
     url = {https://dl.acm.org/doi/abs/10.1145/3450268.3453521},
     year = {2021},
     date = {2021-05-18},
     booktitle = {Proceedings of the 6th ACM/IEEE Conference on Internet of
     		  Things Design and Implementation, 2021},
     pubstate = {published},
     topics = {sensing,mobile},
     tppubtype = {inproceedings}
   }

7. IoTJ

   New Frontiers in IoT: Networking, Systems, Reliability, and Security Challenges

   Saurabh Bagchi, Tarek F Abdelzaher, Ramesh Govindan, and 4 more authors

   IEEE Internet of Things Journal, Feb 2020

   Bib Link

   @article{bagchi2020new,
     title = {New Frontiers in IoT: Networking, Systems, Reliability,
     		  and Security Challenges},
     author = {Bagchi, Saurabh and Abdelzaher, Tarek F and Govindan, Ramesh and Shenoy, Prashant and Atrey, Akanksha and Ghosh, Pradipta and Xu, Ran},
     url = {https://ieeexplore.ieee.org/document/9136673},
     year = {2020},
     date = {2020-01-01},
     journal = {IEEE Internet of Things Journal},
     keywords = {},
     topics = {sensing},
     pubstate = {published},
     tppubtype = {article}
   }

8. IROS

   Persistent Connected Power Constrained Surveillance with Unmanned Aerial Vehicles

   Pradipta Ghosh, Paulo Tabuada, Ramesh Govindan, and 1 more author

   In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Feb 2020

   Bib

   @inproceedings{ghosh2020iros,
     title = {Persistent Connected Power Constrained Surveillance with
     		  Unmanned Aerial Vehicles},
     author = {Ghosh, Pradipta and Tabuada, Paulo and Govindan, Ramesh and Sukhatme, Gaurav S},
     year = {2020},
     date = {2020-01-01},
     booktitle = {Proceedings of the IEEE/RSJ International Conference on
     		  Intelligent Robots and Systems (IROS)},
     keywords = {},
     pubstate = {published},
     topics = {sensing},
     tppubtype = {inproceedings}
   }

9. Grab: Fast and Accurate Sensor Processing for Cashier-Free Shopping

   Xiaochen Liu, Yurong Jiang, Kyu-Han Kim, and 1 more author

   In , Feb 2020

   Bib Link

   @inproceedings{liu2020,
     title = {Grab: Fast and Accurate Sensor Processing for Cashier-Free
     		  Shopping},
     author = {Liu, Xiaochen and Jiang, Yurong and Kim, Kyu-Han and Govindan, Ramesh},
     year = {2020},
     date = {2020-01-07},
     publisher = {arXiv preprint arXiv:2001.01033},
     keywords = {},
     pubstate = {published},
     topics = {sensing},
     tppubtype = {inproceedings}
   }

10. Rapid Top-Down Synthesis of Large-Scale IoT Networks

    Pradipta Ghosh, Jonathan Bunton, Dimitrios Pylorof, and 6 more authors

    In Proceedings of the IEEE International Conference on Computer Communications and Networks (ICCCN), Feb 2020

    Bib Link

    @inproceedings{ghosh2020rapid,
      title = {Rapid Top-Down Synthesis of Large-Scale IoT Networks},
      author = {Ghosh, Pradipta and Bunton, Jonathan and Pylorof, Dimitrios and Vieira, Marcos and Chan, Kevin and Govindan, Ramesh and Sukhatme, Gaurav and Tabuada, Paulo and Verma, Gunjan},
      year = {2020},
      date = {2020-01-01},
      booktitle = {Proceedings of the IEEE International Conference on
      		  Computer Communications and Networks (ICCCN)},
      keywords = {},
      pubstate = {published},
      topics = {sensing},
      tppubtype = {inproceedings}
    }

11. Sensys

    Caesar: Cross-camera Complex Activity Recognition

    Xiaochen Liu, Pradipta Ghosh, Oytun Ulutan, and 3 more authors

    Feb 2019

    Bib Link

    @conference{liu2019,
      title = {Caesar: Cross-camera Complex Activity Recognition},
      author = {Liu, Xiaochen and Ghosh, Pradipta and Ulutan, Oytun and Manjunath, B.S. and Chan, Kevin and Govindan, Ramesh},
      doi = {doi.org/10.1145/3356250.3360041},
      year = {2019},
      date = {2019-11-11},
      booktitle = {SenSys ’19: Conference on Embedded Networked Sensor
      		  Systems},
      publisher = {ACM},
      address = {New York, USA},
      pubstate = {published},
      tppubtype = {conference},
      topics = {sensing},
    }

12. IoTDI

    Kestrel: Video Analytics for Augmented Multi-Camera Vehicle Tracking

    H Qiu, X Liu, S Rallapalli, and 5 more authors

    In 2018 IEEE/ACM Third International Conference on Internet-of-Things Design and Implementation (IoTDI), Feb 2018

    Bib

    @inproceedings{qiu18c,
      title = {Kestrel: Video Analytics for Augmented Multi-Camera
      		  Vehicle Tracking},
      author = {Qiu, H and Liu, X and Rallapalli, S and Bency, A J and Chan, K and Urgaonkar, R and Manjunath, B S and Govindan, R},
      doi = {10.1109/IoTDI.2018.00015},
      year = {2018},
      date = {2018-04-01},
      booktitle = {2018 IEEE/ACM Third International Conference on
      		  Internet-of-Things Design and Implementation (IoTDI)},
      pages = {48-59},
      pubstate = {published},
      tppubtype = {inproceedings},
      topics = {vehicular,sensing},
    }

13. ToN

    Scalability and Satisfiability of Quality-of-Information in Wireless Networks

    Scott T Rager, Ertugrul N Ciftcioglu, Ram Ramanathan, and 2 more authors

    IEEE/ACM Trans. Netw., Feb 2018

    Bib Link

    @article{rager18a,
      title = {Scalability and Satisfiability of Quality-of-Information
      		  in Wireless Networks},
      author = {Rager, Scott T and Ciftcioglu, Ertugrul N and Ramanathan, Ram and Porta, Thomas F La and Govindan, Ramesh},
      url = {https://doi.org/10.1109/TNET.2017.2781202},
      doi = {10.1109/TNET.2017.2781202},
      issn = {1063-6692},
      year = {2018},
      date = {2018-01-01},
      journal = {IEEE/ACM Trans. Netw.},
      volume = {26},
      number = {1},
      pages = {398--411},
      publisher = {IEEE Press},
      address = {Piscataway, NJ, USA},
      keywords = {},
      pubstate = {published},
      topics = {sensing},
      tppubtype = {article}
    }

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