Technical Program
Monday, October 12 14:00 - 15:30
I1: ICT4PPRR'20
- Network slicing for Mission Critical communications
- SKATES: Interoperable Multi-Connectivity Communication Module for Reliable Search and Rescue Robot Operation
- IRONMAN: Infrastructured RSSI-based Opportunistic routiNg in Mobile Adhoc Networks
- CELIDON: Supporting First Responders through 3D AOA-based UWB Ad-Hoc Localization
ST1: STWiMob
- A Stochastic Approach for an Enhanced Trust Management in a Decentralized Healthcare Environment
- Improving Health Information Exchange through Wireless Communication Protocols
- A Proposed Access Control-Based Privacy Preservation Model to Share Healthcare Data in Cloud
- Proxemic Interactions in Mobile Devices to Avoid the Spreading of Infections
Monday, October 12 15:50 - 17:20
C1: CWN+ST
- On-demand Quality-of-Service for Crucial Vehicle-to-Pedestrian Communication
- Cluster Formation in Scalable Cell-free Massive MIMO Networks
- Analysis of A&F Mobile Relay Nodes with Power Control and Link Selection in HSR Scenarios
- An Entropy-Based WLAN Channel Allocation using Channel State Information
ST2: STWiMob
- Analysis of methods for prioritizing critical data transmissions in agricultural vehicular networks
- Physical and MAC Layer Design for Active Signaling Schemes in Vehicular Networks
- A Multiple Linear Regression Model for Predicting Congestion in Heterogeneous Vehicular Networks
- Efficient Airborne Network Clustering for 5G Backhauling and Fronthauling
Monday, October 12 17:30 - 19:00
ST3: STWiMob
Tuesday, October 13 13:45 - 14:00
Opening Ceremony
Tuesday, October 13 14:00 - 15:00
Keynote1: Reinforcement Learning for Resource Management in Space-Air-Ground (SAG) Integrated Vehicular Networks
Abstract
Space-Air-Ground integrated Vehicular Network (SAGVN) is a prominent paradigm, which can simultaneously guarantee ultra-reliability low-latency communications (URLLC) and deliver high-bandwidth traffic anywhere, any environment condition, and any event at anytime. However, it is challenging to manage and allocate the terrestrial network, aerial network (UAV), and space (satellite) resources simultaneously and efficiently, as they have heterogeneous access features in terms of delay, throughput, and coverage range. In addition, high vehicle mobility and real-time decision requirement further render the problem intractable. In this talk, we advocate the usage of reinforcement learning for resource management in SAGVN, which can enable model-free and fast decision makings for adaptive access control, on-demand UAV deployment, and UAV trajectory design. We will also show the detail development of our SAG simulator and some demos.
Biography
Xuemin (Sherman) Shen is a University Professor, Department of Electrical and Computer Engineering, University of Waterloo, Canada. Dr. Shen's research focuses on wireless resource management, wireless network security, 5G and vehicular ad hoc and sensor networks. He was the Editor-in-Chief of IEEE IoT J, and served as the General Chair for Mobihoc'15, the Technical Program Committee Chair for IEEE Globecom'16, IEEE Infocom'14, IEEE VTC'10, the Symposia Chair for IEEE ICC'10, the Technical Program Committee Chair for IEEE Globecom'07, the Chair for IEEE Communications Society Technical Committee on Wireless Communications. Dr. Shen was an elected IEEE ComSoc Vice President - Publications, the chair of IEEE ComSoc Distinguish Lecturer selection committee, and a member of IEEE ComSoc Fellow evaluation committee. Dr. Shen received the Excellent Graduate Supervision Award in 2006, and the Premier's Research Excellence Award (PREA) in 2003 from the Province of Ontario, Canada. Dr. Shen is a registered Professional Engineer of Ontario, Canada, an IEEE Fellow, an Engineering Institute of Canada Fellow, a Canadian Academy of Engineering Fellow, a Royal Society of Canada Fellow, a Chinese Academy of Engineering Foreign Fellow, and a Distinguished Lecturer of IEEE Vehicular Technology Society and Communications Society.
Tuesday, October 13 15:10 - 16:40
S1: Wireless networks
- Robustness and Scalability Improvements for Distance Vector Routing in Large WMNs
- A Color Adjustment Method for HDR Display of Video Content Received Over Wireless Multimedia Networks
- Impact of Slice Function Placement on the Performance of URLLC with Redundant Coverage
- Analysis and Power Scheduling Algorithm in Wireless Powered Communication Networks
S2: Vehicular networks
- The Deployment of Roadside Units in Vehicular Networks Based on the V2I Connection Duration
- Modelling V2V message generation rates in a highway environment
- Towards Intelligent and Dynamic Road Speed Adaptation Model in Smart Cities
- Multi-Lane Detection and Tracking Using Vision for Traffic Situation Awareness
Tuesday, October 13 16:50 - 18:20
S3: Internet of Things
- Leveraging Reinforcement Learning for Adaptive Monitoring of Low-Power IoT Networks
- Data Reduction and Cleaning Approach for Energy-saving in Wireless Sensors Networks of IoT
- A Data Cleansing Approach In Smart Home Environments Using Artificial Neural Networks
- And QUIC Meets IoT: Performance Assessment of MQTT over QUIC
S4: LoRA
Tuesday, October 13 18:30 - 20:00
S5: Physical layer
S6: Mobility
- Second Order Time-Frequency Modulation in Satellite High-Mobility Communications
- Learning congestion over millimeter-wave channels
- UDMSim: A Simulation Platform for Underwater Data Muling Communications
- A Q-learning Approach for the Support of Reliable Transmission in the Internet of Underwater Things
Wednesday, October 14 14:00 - 15:00
Keynote2: Security of 4G and 5G cellular networks
Abstract
As the world moves to 4G and 5G cellular networks, security and privacy are paramount importance and new tools are needed to ensure them. For example, LTEInspector is a model-based testing approach that combines a symbolic model checker and a cryptographic protocol verifier in the symbolic attacker model. Using it, researchers have uncovered 10 new attacks along with 9 prior attacks, categorized into three abstract classes (i.e., security, user privacy, and disruption of service), in three procedures of 4G LTE. Notable among the findings is the authentication relay attack that enables an adversary to spoof the location of a legitimate user to the core network without possessing appropriate credentials. To ensure that the exposed attacks pose real threats and are indeed realizable in practice, 8 of the 10 new attacks have been validated and their accompanying adversarial assumptions have been put through a real testbed. On-going work in addressing some of those vulnerabilities points the way toward an agenda of further research.
Biography
Elisa Bertino is professor of Computer Science at Purdue University. She serves as Director of the Purdue Cyberspace Security Lab (Cyber2Slab). Prior to joining Purdue, she was a professor and department head at the Department of Computer Science and Communication of the University of Milan. She has been a visiting researcher at the IBM Research Laboratory in San Jose (now Almaden), at the Microelectronics and Computer Technology Corporation, at Rutgers University, at Telcordia Technologies. She has also held visiting professor positions at the Singapore National University and the Singapore Management University. Her main research interests include security, privacy, database systems, distributed systems, and sensor networks. Her recent research focuses on cybersecurity and privacy of cellular networks and IoT systems, and on edge analytics for cybersecurity. Elisa Bertino is a Fellow member of IEEE, ACM, and AAAS. She received the 2002 IEEE Computer Society Technical Achievement Award for "For outstanding contributions to database systems and database security and advanced data management systems", the 2005 IEEE Computer Society Tsutomu Kanai Award for "Pioneering and innovative research contributions to secure distributed systems", and the 2019-2020 ACM Athena Lecturer Award.
Wednesday, October 14 15:10 - 16:40
S7: Wireless networks 2
- Broadcast-Multicast Single Frequency Network versus Unicast in Cellular Systems
- Mobility Prediction via Sequential Learning for 5G Mobile Networks
- Medium Access Probability Model Based on CSMA/CA for a DSRC Network Driven by Poisson Line Process
- Cost-optimal V2X Service Placement in Distributed Cloud/Edge Environment
S8: Applications
- An Intelligent Malware Detection and Classification System Using Apps-to-Images Transformations and Convolutional Neural Networks
- Counting calories without wearables: Device-free Human Energy Expenditure Estimation
- On the Latency of Multipath-QUIC in Real-time Applications
- Mobile Malware Detection with Imbalanced Data using a Novel Synthetic Oversampling Strategy and Deep Learning
Wednesday, October 14 16:50 - 18:20
S10: Physical layer 2
- Characterization of the Indoor-to-Outdoor Wireless Channel in Air-to-Ground Communication Systems
- Machine Learning-Based Methods for Path Loss Prediction in Urban Environment for LTE Networks
- Diversity-Multiplexing Tradeoff for Indoor Visible Light Communication
- Sensor Self-location with FTM Measurements
S9: Channel Measurement and Characterization
- Theoretical Performance of the Gradient-Based Tone Reservation PAPR Reduction Algorithm
- RNN-Based User Trajectory Prediction Using a Preprocessed Dataset
- Joint Beamforming and PAPR Reduction in Massive MIMO: Analysis of Gain in Energy Efficiency
- A Study of Delay and Doppler Spreads at 24 GHz ISM band
Wednesday, October 14 18:30 - 20:00
SP: Poster&Short Papers
- Data Stream Query Processing on Mobile Devices
- Innovative Dynamic SRAM PUF Authentication for Trusted Internet of Things
- Towards the Complexity of the Widest Path Problem in Hybrid Multi-Channel WMNs
- Video-assisted Overtaking System Enabled by C-V2X Mode 4 Communications
- A Smart Grid WSN Research Testbed
- Rethinking the Design of Wearable Expert Systems: The Role of Network Infrastructures