ACM MSWiM 2023 Technical Program
(Tentative)
Important Notes
- Sessions Time is based on Eastern Daylight Time Zone (EDT) [GMT-4] |
Sunday, October 29
All Day
Concurrent Symposia I
Monday, October 30
All Day
Concurrent Symposia I
8:00 - 8:30
Opening and Welcome Address by GC and TPC
08:30 - 09:30
Session 1: Indoor Positioning
- Accurate E-CID Framework for Indoor Positioning in 5G using Path Tracing and Machine Learning.
- Assessing the Impact of Coupling RTT and RSSI Measurements in Fingerprinting Wi-Fi Indoor Positioning.
09:30 - 10:30
Keynote Speech 1
- Research Directions in Network Architectures and Protocols for Intelligent Digital Infrastructures
- JJ Garcia-Luna-Aceves (University of Toronto, Canada)
10:30 - 11:00
Coffee break
11:00 - 12:30
Session 2: Wireless Communications and Networks
- On the Dynamics of Single-Orbit Requester-Provider Systems.
- QUICL: A QUIC Convergence Layer for Disruption-tolerant Networks.
- Simple and Efficient Loop-Free Multipath Routing in Wireless Networks.
12:30 - 13:30
Lunch Break
13:30 - 14:30
Panel Discussion
- Panelists
- JJ Garcia-Luna-Aceves (University of Toronto, Canada), Douglas Blough (Georgia Institute of Technology, USA), Ahmed Helmy (University of North Carolina, USA)
14:30 - 15:00
Coffee break
15:00 - 17:15
Session 3: Scheduling and Offloading
- Efficient and Effective Proactive Scheduling for mmWave WLANs
- Scheduling ``Last Minute" Updates for Timely Decision-Making
- Offloading Augmented Reality Tasks with Smart Energy Source-Aware Algorithms at the Edge.
- Learning Optimal Edge Processing \\ with Offloading and Energy Harvesting
- A Low-Cost Open-Source Testbed for Experimental Analysis of Ultra-Dense Wireless Networks.
Tuesday, October 31
08:30 - 09:30
Session 4: Task offloading and Edge Computing
- Managing Edge Offloading for Stochastic Workloads with Deadlines
- Task offloading optimization in Mobile Edge Computing based on Deep Reinforcement Learning.
09:30 - 10:30
Keynote Speech 2
- Quantum Leap: Exploring the Potential of Quantum Machine Learning for Communication Networks
- Soumaya Cherkaoui (Polytechnique Montreal, Canada)
10:30 - 11:00
Coffee break
11:00 - 12:30
Session 5: Modeling and Performance Analysis
- Performance analysis of MAC energy-saving strategies for WLANs .
- Modeling and Performance Analysis of Slotted ALOHA with Interference Cancellation for mMTC.
- Blind Modulation Classification of Wi-Fi 6 and 5G signals for Spectrum Sensing
12:30 - 13:30
Lunch Break
13:30 - 15:15
Session 6: Security and Privacy
- IoDAPM: A Reinforcement Learning Approach for Dynamic Assignment of Protection Mechanisms in IoD
- Federated Learning for V2X Misbehavior Detection System in 5G Edge Networks.
- SLOW-Based Pseudonym Changing Schemes for Location Privacy in Vehicular Networks.
- A VeReMi-based Dataset for Predicting the Effect of Attacks in VANETs
15:15 - 15:45
Coffee Break
15:45 - 17:15
Session 7: Modeling and Simulation
- SimEdge: Towards Accelerated Real-Time Augmented Reality Simulations Using Adaptive Smart Edge Computing
- Repairing a Service Composition with Graph Embedding and Planning Graph in a Cloud-Edge Environment
- High Fidelity Fast Simulation of HIL-HIP systems
- Impact of the Burst Size on the FTM Procedure Run in Android Phones
Wednesday, November 1
All Day
Concurrent Symposia IV
08:00 - 09:00
Tutorial
09:00 - 10:30
Session 9: IoT, Sensors and Embedded Systems
- Exploring the Tradeoffs Between Systematic and Random Exploration in Mobile Sensors.
- Analysis of the influence of terrain on LoRaWAN-based IoT deployments
- Signal Leakage in Fat Tissue-Based In-Body Communication: Preserving Implant Data Privacy
10:30 - 11:00
Coffee break
11:00 - 12:15
Session 10: Wireless Networks Embedded Systems
- Determining the Ordering of a Line Topology under Correlated Shadowing and Fast Fading.
- Djenne: Dependable and Decentralized Computation for Networked Embedded Systems.
- Fast Transmission of Massive Concurrent Alarm Messages in LoRaWAN
12:15 - 13:30
Lunch Break
13:30 - 16:00
Session 11: IoT and Wireless Networks
- Power Minimization in Federated Learning with Over-the-air Aggregation and Receiver Beamforming.
- DCH: A Deep Learning Approach To Universal Header Compression For The Internet of Things
- In-Band Multi-Connectivity with Local Beamtraining for Improving mmWave Network Resilience.
- Identification of RF Interference in Astronomical Observations Using Weakly Supervised Machine Learning Classifiers .
- How Fresh is the Data? An Optimal Learning-Based End-to-End Pull-Based Forwarding Framework for NDNoTs
16:00 - 16:15
Coffee Break
16:15 - 17:15
Session 12: Federated Learning and Wireless Networks
- Supporting Dynamic IDS Deployment with Load Balancing Strategy for SDN-enabled Drones in Emergency Scenarios
- Strategies to plan the number and locations of RSUs for an IEEE 802.11p-based infrastructure in urban environment
- Redefining the Driver's Attention Gauge in Semi-Autonomous Vehicles.
- RealFL: A Realistic Platform for Federated Learning.