WiFiUS: Scalable Edge Architecture for Massive Location-Aware Heterogeneous IoT Systems

Massive IoT

Project description

The project addresses essential research problems on network design and Internet of Things (IoT) system development, by defining an efficient security and scalability enhancing edge architecture that moves data processing close to users minimizing data transfer latencies in the network.

The fusion of sensor data from different sources can improve the efficiency of many existing systems significantly, and the massive bandwidth is about to become available to cellular and WiFi networks at the millimeter wave bands.

Smart traffic and connected (autonomous) cars are an example application area enabled by the new bandwidth, which requires combining these different approaches in the architectural design of large-scale IoT systems.

Integrating IoT with edge/fog computing, millimeter wave (mmWave) technologies and distributed processing enables optimizing the system level performance considering system capacity, reduced network bandwidth for data and control traffic, increased system level programmability and automation, accurate location-awareness, virtualization, low latency, scalability, and enhanced security.

Project provides contributions in several essential areas of IoT network architectures and security:

- Edge computing using distributed IoT processing and storage to make IoT networks substantially more efficient and robust

- Secure exchange of user IoT data when using edge computing

- Simulation-to-deployment enabling automated deployment of large scale IoT networks (up to millions of nodes)

- Indoor positioning based on collective intelligence of IoT nodes

Finnish partners study how processing and storage of IoT data can be distributed intelligently and securely using edge computing. The focus is on methods for discovering available processing resources in networks, optimizing the aggregation of processing tasks, and migrating services and applications between devices and network nodes, while taking into account the system requirements for performance, resource-efficiency, privacy, security and scalability.

Columbia University is investigating how to make authentication, authorization, security and privacy of IoT devices, particularly if deployed at scale, more user-friendly and scalable.  In addition, research is done on IoT lifecycle emulator with emulate-and-deploy approaches to design and build reliable largescale systems utilizing physical hardware and networks, simulation and emulation, and distributing them into physical hardware.

NYU will focus in the project on Millimeter Wave indoor channel measurement and modeling from 28 through 140 GHz,  implementation of Indoor mmWave channel modeling in the open source NYUSIM simulator and to the study and development of position location algorithms for indoor mmWave IOT applications.

Project status and overview (WiFiUS PI meeting Boston June 11th 2018)

Overall, this has been a very succesfull project, having great impacts for the project partners.

At NYU WIRELESS, research was developed for IoT and future wireless communications with new fundamental knowledge and approaches being successfully implemented in the following major areas:
1. Indoor position location at mmWave and sub-Terahertz frequencies;
2. Measurements and channel models for indoor channels at 140 GHz, including THz scattering models, penetration loss models, calibration methods, and large-scale path loss models.
3. Creation of spatial consistency channel models for outoor communications, useful for high density wireless nodes, and improvements that will be implemented in the popular NYUSIM open source channel simulator.
Accomplishments in these areas include the publication of many papers, presentations, and a landmark invited paper for "6G and Beyond" in IEEE ACCESS, as well as the successful graduation of a MS student working on this grant. 3 NYU WIRELESS graduate students have been supported, with all 3 continuing well into their Ph.D programs.

Project results

Articles in journals

 Articles in conference proceedings

Edited Books

  • M. Liyanage, I. Ahmad, A. Abro, A. Gurtov, M. Ylianttila,(eds). ”A comprehensive Guide to 5G Security”, Wiley and Sons, 2018.
  • M. Liyanage, A. Braeken, P. Kumar, M. Ylianttila,(eds). "IoT Security: advances in authentication", Wiley and Sons, to appear 2019.

 Book chapters

  • E. Harjula, T. Mekonnen, M. Komu, P. Porambage, T. Kauppinen, J. Kjällman, M. Ylianttila. ”Energy Efficiency in Wireless Multimedia Sensor Networking: Architecture, Management and Security”. In, A Popescu (eds) Greening Video Distribution Networks: Energy-Efficient Internet Video Delivery, Springer, Heidelberg, 2018.

 

Partners

FINLAND
University of Oulu/Centre for Wireless Communications (Academy of Finland decision # 311773), PI Associate prof. Mika Ylianttila, Erkki Harjula
VTT (Academy of Finland decision # 311773), PI Jukka Mäkelä, Pekka Karhula, Olli Mämmelä

USA
Columbia University (NSF Award # 1702952), PI Prof. Henning Schulzrinne,  Jan Janak
New York University (NSF Award # 1702967), PI Prof. Theodore Rappaport, Yunchou Xing, Ojas Kanhere, Shihao Ju

People

Mika Ylianttila

Associate professor (tenure track)

Erkki Harjula

Project Manager / Postdoctoral researcher
Tanesh Kumar

Tanesh Kumar

Researcher and Doctoral Candidate