IE 304 (Spring19): Principles of Wireless Communication and Mobile Networks

Project:

1. Teams

You are expected to carry out the project in a group of 1 or 2 students.

2. Proposal

The project proposal is due on Sunday, Mar. 31, 2019 (tentative)Friday, Apr. 5, 2019 (firm), and it should be no more than 2 pages without counting the references. The template for the project proposal can be found here.

Please email your proposal to wireless_sjtu@163.com no later than the deadline.

• Project title (a detailed title is better than a vague one; you can always change it later if you don't like it!) and names of investigators with email addresses.
• A clear statement of the research problem: a one-sentence summary followed by a one-paragraph explanation (the paragraph shouldn't be more than 10-12 lines long). This should identify clearly the research question you're addressing.
• A clear statement of your research methods. i.e., how are you going to solve the problems you've raised and motivated in the previous paragraph?
• A statement of plan and schedule, to convince us (and yourself!) that you can complete the project by the end of the semester.
• A comprehensive survey of related work with the list of references that shows the novelty of this project.

3. Expectations

Aim high in a focused way, and do the best you can! This semester-long project is research-oriented which must address an open research problem, and the best projects are usually publishable with a bit more additional work in top conferences.

4. Final Report

The final report is due at Sunday June 16, 2019 (tentative) 11:59 PM (CST), Thursday, June 20, 2019 (firm).

The report should follow the style of a conference paper describing the project and its key contributions/findings. It should be written in English using this template, and it should be no more than 10 pages with all contents included.

Please email your report to wireless_sjtu@163.com no later than the deadline.

5. Project Presentation

Students will present their projects in Week 16. The presentation should be a conference-style presentation. The presentation should be made in English.

Each group will have up to 14 minutes (with Q&A) for presentation. Please select a slot for your group from the sign-up sheet by filling in all members' names in your group.

Please email your slides to wireless_sjtu@163.com before the end of the day when you present.

6. Project Topics

Please refer to the following list for the possible topics that you may take for the course project. For each topic, I provide 3-4 most relevant references. You will, of course, have to survey more paper on your own to get a better understanding of the research directions listed. You are also welcomed to work on any other topics related to wireless communication and mobile networks.

• Mobile Crowdsourcing:
• Dejun Yang, Guoliang Xue, Xi Fang, Jian Tang, "Crowdsourcing to Smartphones: Incentive Mechanism Design for Mobile Phone Sensing", in Proc. of ACM MobiCom 2012.
• Yang Liu, Mingyan Liu, "An Online Learning Approach to Improving the Quality of Crowd-Sourcing", in Proc of ACM SIGMETRICS 2015.
• Chuishi Meng, Houping Xiao, Lu Su, Yun Cheng, "Tackling the Redundancy and Sparsity in Crowd Sensing Applications", in Proc. of ACM SenSys 2016.
• Ride Sharing Systems:
• Siddhartha Banerjee, Ramesh Johari, Carlos Riquelme, "Pricing in Ride-Sharing Platforms: A Queueing-Theoretic Approach", in Proc. of ACM EC 2015.
• Zhixuan Fang, Longbo Huang, Adam Wierman, "Prices and Subsidies in the Sharing Economy", in Proc. of WWW 2017.
• Javier Alonso-Mora, Samitha Samaranayake, Alex Wallar, Emilio Frazzoli, and Daniela Rus, "On-Demand High-Capacity Ride-Sharing via Dynamic Trip-Vehicle Assignment", in PNAS 2017.
• Lu Chen, Qilu Zhong, Xiaokui Xiao, Yunjun Gao, Pengfei Jin, Christian S. Jensen, "Price-and-Time-Aware Dynamic Ridesharing", in Proc of IEEE ICDE 2018.
• Bike Sharing Systems:
• Yexin Li, Yu Zheng, Qiang Yang, "Dynamic Bike Reposition: A Spatio-Temporal Reinforcement Learning Approach", in Proc. of ACM KDD 2018.
• Ling Pan, Qingpeng Cai, Zhixuan Fang, Pingzhong Tang, Longbo Huang, "A Deep Reinforcement Learning Framework for Rebalancing Dockless Bike Sharing Systems", in Proc. of AAAI 2019.
• Zhaoyang Liu, Yanyan Shen, Yanmin Zhu, "Where Will Dockless Shared Bikes be Stacked?: Parking Hotspots Detection in a New City ", in Proc. of ACM KDD 2018.
• Tianfu He, Jie Bao, Ruiyuan Li, Sijie Ruan, Yanhua Li, Chao Tian, Yu Zheng, "Detecting Vehicle Illegal Parking Events using Sharing Bikes' Trajectories", in Proc of IEEE KDD 2018.
• Electric Vehicles:
• Zheng Dong, Cong Liu, YanHua Li, Jie Bao, Yu Gu, Tian He, "REC: Predictable Charging Scheduling for Electric Taxi Fleets", in Proc. of IEEE RTSS 2017.
• Ankur Sarker, Haiying Shen, John A. Stankovic, "MORP: Data-Driven Multi-Objective Route Planning and Optimization of Electric Vehicles", in Proc. of ACM IMWUT 2017.
• Guang Wang, Xiaoyang Xie, Fan Zhang, Yunhuai Liu, Desheng Zhang, "bCharge: Data-Driven Real-Time Charging Scheduling for Large-Scale Electric Bus Fleets", in Proc. of IEEE RTSS 2018.
• Predictions and Inferences for Transportation:
• Xian Zhou, Yanyan Shen, Yanmin Zhu, Linpeng Huang, "Predicting Multi-step Citywide Passenger Demands Using Attention-based Neural Networks", in Proc. of ACM WSDM RTSS 2018.
• Chuishi Meng, Xiuwen Yi, Lu Su, Jing Gao, Yu Zheng, "City-wide Traffic Volume Inference with Loop Detector Data and Taxi Trajectories", in Proc. of ACM SIGSPATIAL 2017.
• Huaxiu Yao, Xianfeng Tang, Hua Wei, Guanjie Zheng, Zhenhui Li, "Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction", in Proc. of AAAI 2019.
• Bing Yu, Haoteng Yin, Zhanxing Zhu, "Spatio-temporal graph convolutional networks: a deep learning framework for traffic forecasting", in Proc. of IJCAI 2018.
• Reinforcement Learning in Networks and Systems:
• Hongzi Mao, Ravi Netravali, Mohammad Alizadeh, "Neural Adaptive Video Streaming with Pensieve", in Proc. of ACM SIGCOMM 2017.
• Teng Li, Zhiyuan Xu, Jian Tang, Yanzhi Wang, "Model-Free Control for Distributed Stream Data Processing Using Deep Reinforcement Learning", in Proc of VLDB 2018.
• Zhiyuan Xu, Jian Tang, Jingsong Meng, Weiyi Zhang, Yanzhi Wang, Chi Harold Liu, Dejun Yang, "Experience-Driven Networking: a Deep Reinforcement Learning Based Approach", in Proc. of IEEE INFOCOM 2018.
• Leye Wang, Wenbin Liu, Daqing Zhang, Yasha Wang, En Wang, Yongjian Yang, "Cell Selection with Deep Reinforcement Learning in Sparse Mobile Crowdsensing", in Proc. of IEEE ICDCS 2018.
• Deep Learning for IOT:
• Shuochao Yao, Yiran Zhao, Aston Zhang, Shaohan Hu, Huajie Shao, Chao Zhang, Lu Su, Tarek Abdelzaher, "Deep Learning for the Internet of Things", in IEEE Computer Magazine 2018.
• Shuochao Yao, Yiran Zhao, Aston Zhang, Lu Su, and Tarek Abdelzaher, "DeepIoT: Compressing Deep Neural Network Structures for Sensing Systems with a Compressor-Critic Framework", in Proc. of ACM SenSys 2017.
• Shuochao Yao, Yiran Zhao, Huajie Shao, Chao Zhang, Aston Zhang, Shaohan Hu, Dongxin Liu, Shengzhong Liu, Lu Su, and Tarek Abdelzaher, "SenseGAN: Enabling Deep Learning for Internet of Things with a Semi-Supervised Framework", in Proc. of ACM IMWUT 2018.
• Shuochao Yao, Yiran Zhao, Huajie Shao, Shengzhong Liu, Dongxin Liu, Lu Su, and Tarek Abdelzaher, "FastDeepIoT: Towards Understanding and Optimizing Neural Network Execution Time on Mobile and Embedded Devices", in Proc of ACM SenSys 2018.
• Mobile Sensing:
• Sheng Shen, Mahanth Gowda, Romit Roy Choudhury, "Closing the Gaps in Inertial Motion Tracking", in Proc. of ACM MobiCom 2018.
• Kongyang Chen, Guang Tan, "BikeGPS: Accurate Localization of Shared Bikes in Street Canyons via Low-Level GPS Cooperation", in Proc. of ACM MobiSys 2018.
• Tuo Yu, Haiming Jin, Klara Nahrstedt, "WritingHacker: Audio-based Eavesdropping of Handwriting via Mobile Devices", in Proc. of UbiComp 2016.
• Security and Privacy:
• Weina Wang, Lei Ying, Junshan Zhang, "The Value of Privacy: Strategic Data Subjects, Incentive Mechanisms and Fundamental Limits", in Proc. of ACM SigMetrics 2016.
• Chenglin Miao, Qi Li, Houping Xiao, Wenjun Jiang, Mengdi Huai, and Lu Su, "Towards Data Poisoning Attacks in Crowd Sensing Systems", in Proc. of ACM MobiHoc 2018.
• Nirupam Roy, Sheng Shen, Haitham Hassanieh, Romit Roy Choudhury, "Inaudible Voice Commands: The Long-Range Attack and Defense ", in Proc. of USENIX NSDI 2018.