Program

 

 

TECHNICAL PROGRAM

Time/Day

Monday 30 June

08:30 - 09:30

Registration

09:30 - 10:30

Opening Remarks 

10:30 - 11:00

Coffe Break

11:00 - 12:30

Technical Session I

12:30 - 14:00

Lunch Break

14:00 - 14:40

Keynote Session

14:50 - 16:00

Technical Session II

16.00 - 16.05

Closing Remarks

 

 

09:30 – 10:30   Welcome Remarks

Introduction to the Workshop: Pasquale Pace, Giuseppe Ruggeri

Title of the speech: An Evolutionary network architecture for smart and sustainable cities: The STEM-Net framework

 

 

11:00 – 12:30   Technical Session I

 

SESSION I: Data Collection and Forwarding over Smart Cities

Session Chair: Pasquale Pace, University of Calabria, Italy

 

1)    Self-organizing TCP with Multiple Wireless LAN    

Alvin Lim (Auburn University, USA); Song Gao (Auburn University, USA)

 

2)    Adaptive Sink Selection for WSNs Using Forwarder Set Based Dynamic Duty Cycling

Sila Ozen (Istanbul Technical University, Turkey); Sema Oktug (Istanbul Technical University, Turkey)

 

3)    NDN-Q: An NDN Query Mechanism for Efficient V2X Data Collection in Smart Cities

Wassim Drira (Qatar Mobility Innovations Center, Qatar); Fethi Filali (QMIC, Qatar)

 

4)    Maximizing the Route Capacity in Cognitive Radio Networks       

Angela Sara Cacciapuoti (University of Naples Federico II, Italy); Marcello Caleffi (University of Naples "Federico II", Italy); Francesco Marino (Università di Napoli Federico II, Italy); Luigi Paura (Università di Napoli Federico II, Italy)

 

 

 

 

14:00 – 14:40    Keynote Session

Keynote Speaker: Justin Dauwels

Title of the speech: "The key role of ICT in Smart Cities: real-time large-scale urban traffic prediction and related problem"

 

Abstract:
Advanced sensing and surveillance technologies can collect traffic information from various sources with high temporal and spatial resolution. Recorded data is essential for many real-time applications related to traffic management systems. However, the volume of the data collected severely limits the scalability of these systems for large networks. In this talk, we consider the problems of compression, estimation and prediction in the context of large and diverse networks.
Although methods such as principal component analysis (PCA) can efficiently compress traffic data sets, the low-dimensional models created by these methods are not readily interpretable.
In this study, we propose an alternative approach to compress the recorded data and enhance the scalability of traffic management systems. We compress the network by representing it in terms of a small subset of the road segments present in the network. This formulation allows us to efficiently store collected data in an intuitive way. Furthermore, we utilize the compressed representation to estimate the current state of the network by collecting data from a small subset of road segments.
Similarly, we perform traffic prediction for the whole network, by developing prediction models for only the representative subset of road segments. For the analysis, we consider a large network comprising 17,967 road segments. Numerical results show that our method can achieve competitive compression performance compared to PCA. Results further demonstrate significant reduction in prediction time

Bio:
Justin Dauwels is an Assistant Professor with School of Electrical & Electronic Engineering at the Nanyang Technological University (NTU) in Singapore. His research interests are in Bayesian statistics, iterative signal processing, and computational neuroscience. He obtained the PhD degree in electrical engineering at the Swiss Polytechnical Institute of Technology (ETH) in Zurich in December 2005. He was a postdoctoral fellow at the RIKEN Brain Science Institute (2006-2007) and a research scientist at the Massachusetts Institute of Technology (2008-2010). He has been a JSPS postdoctoral fellow (2007), a BAEF fellow (2008), a Henri-Benedictus Fellow of the King Baudouin Foundation (2008), and a JSPS invited fellow (2010,2011).

His research on Intelligent Transportation Systems (ITS) has been featured by the BBC, Straits Times, and various other media outlets.

His research on Alzheimer's disease is featured at a 5-year exposition at the Science Centre in Singapore.

His research team has won several best paper awards at international conferences.

He has filed 5 US patents related to data analytics.

 

14:50 – 16:00   Technical Session II

 

SESSION II: Network Infrastructures for Smart Cities

Session Chair: Giuseppe Ruggeri,  University of Reggio Calabria, Italy

 

 

1)    Integrating Wireless Sensor Networks within a City Cloud

Riccardo Petrolo (Inria Lille - Nord Europe, France); Nathalie Mitton (Inria Lille - Nord Europe, France); John Soldatos (AIT, Greece); Manfred Hauswirth (DERI Galway, Ireland); Gregor Schiele (Insight Galway, National University of Ireland Galway, Ireland)

 

2)    Simulating Dynamic Spectrum Access using ns-3 for Wireless Networks in Smart Environments              

Abdulla Al-Ali (Northeastern University, USA); Kaushik Chowdhury (Northeastern University, USA)

 

3)    Database Access Strategy for TV White Space Cognitive Radio Networks            

Marcello Caleffi (University of Naples "Federico II", Italy); Angela Sara Cacciapuoti (University of Naples Federico II, Italy)

 

 

 

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